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Review of innovative methods for
retrofitting purposes
Deliverable D.3.3
Component 3- Analysis- Desk research
Phase 3.3 - Analysis of innovative retrofitting methods applied in the technoeconomical study stage
Contract No.: 1C-MED12-73
Axe2: Protection of the environment and promotion of a sustainable territorial
development
Objective 2.2: Promotion and renewable energy and improvement of energy
efficiency
Authors: George M. Stavrakakis, Christoforos Perakis and Konstantinos
Anagnostopoulos
Centre for Renewable Energy Sources and Saving (CRES)
with the support of: Municipality of Piraeus, AViTeM, NCA, IVE, AER, DEMOCENTER,
ERR, EIHP and ZADRA.
Submission date: 31st March 2014
Status: Final
March 2014
Table of contents
Table of contents............................................................................................................................. 0
Abstract .......................................................................................................................................... 7
1. Introduction ................................................................................................................................ 8
2. Physical models ......................................................................................................................... 10
2.1 Building thermal behaviour modelling ..................................................................................... 10
2.1.1 Field models for indoor airflow assessments ......................................................................... 11
2.1.2 The multi-zonal (nodal) approach ......................................................................................... 12
2.1.3 Comparative analysis of physical modelling methods ............................................................ 14
2.1.4 Building energy simulation tools ........................................................................................... 16
2.1.4.1 Autodesk Green Building Studio ......................................................................................... 17
2.1.4.2 BEAVER .............................................................................................................................. 17
2.1.4.3 BSim .................................................................................................................................. 18
2.1.4.4 DeST .................................................................................................................................. 19
2.1.4.5 DOE-2 ................................................................................................................................ 20
2.1.4.6 ECOTECT ............................................................................................................................ 20
2.1.4.7 ENER-WIN .......................................................................................................................... 21
2.1.4.8 EnergyPlus ......................................................................................................................... 22
2.1.4.9 eQUEST.............................................................................................................................. 23
2.1.4.10 ESP-r ................................................................................................................................ 23
2.1.4.11 IDA Indoor Climate and Energy (IDA-ICE) .......................................................................... 24
2.1.4.12 IES Virtual Environment (IESVE)........................................................................................ 25
2.1.4.13 SUNREL ............................................................................................................................ 26
2.1.4.14 TAS .................................................................................................................................. 27
2.1.4.15 TRNSYS ............................................................................................................................ 27
1
2.2 Urban Heat Island modelling.................................................................................................... 44
2.2.1 Energy balance models ......................................................................................................... 45
2.2.2 Computational fluid dynamics............................................................................................... 46
2.2.2.1 Meso-scale modelling ........................................................................................................ 47
2.2.2.2 Micro-scale modelling ........................................................................................................ 48
2.2.3 The role of urban physics in urban energy and environmental studies .................................. 49
2.2.3.1 Urban wind comfort........................................................................................................... 49
2.2.3.2 Urban thermal comfort ...................................................................................................... 51
2.2.3.3 Urban energy demand ....................................................................................................... 53
2.2.3.4 Urban pollutant dispersion................................................................................................. 55
2.2.4 Comparative analysis of UHI modelling methods .................................................................. 57
2.2.5 UHI simulation tools ............................................................................................................. 58
2.2.5.1 Energy balance modelling tools.......................................................................................... 59
2.2.5.1.1 Urban heat storage model (UHSM) ................................................................................. 59
2.2.5.1.2 Town energy budget (TEB) .............................................................................................. 60
2.2.5.1.3 SOLWEIG......................................................................................................................... 61
2.2.5.1.4 Rayman........................................................................................................................... 61
2.2.5.2 CFD tools ........................................................................................................................... 62
2.2.5.2.1 ENVI-met ........................................................................................................................ 62
2.2.5.2.2 ANSYS-Fluent .................................................................................................................. 63
2.2.5.2.3 ANSYS-CFX ...................................................................................................................... 65
2.2.5.2.4 Phoenics ......................................................................................................................... 66
2.2.6 CFD and multi-zonal coupling for building energy assessments ............................................. 76
3. Decision making through optimization algorithms ..................................................................... 79
4. Level of use of assessment tools ................................................................................................ 84
2
4.1 Level of use of BES tools for building energy performance assessment .................................... 85
4.2 Level of use of field modelling tools for urban microclimate assessment.................................. 87
4.3 Level of use of CFD/BES coupled simulations for building energy assessment .......................... 89
5. Discussing the reasons of limited use of urban and building physics tools .................................. 89
6. Conclusions ............................................................................................................................... 94
Annex: Application of innovative methods in the partner Countries .............................................. 96
Annex 1: Review of innovative methods for retrofitting purposes - Greece .................................... 97
Executive Summary ....................................................................................................................... 98
1.
Introduction .......................................................................................................................... 99
Scope of the Review .................................................................................................................. 99
Objectives ................................................................................................................................. 99
2.
Identification and presentation of innovative tools .............................................................. 100
Building Energy Simulation Tools ................................................................................................. 101
ECOTECT .................................................................................................................................. 101
ENER-WIN ............................................................................................................................... 102
EnergyPlus............................................................................................................................... 102
ESP-r........................................................................................................................................ 103
TRNSYS .................................................................................................................................... 103
Open Space – Urban Heat Island Simulation Tools ....................................................................... 104
ENVI-MET ................................................................................................................................ 104
3.
Applicability in Greek cases - Review & classification ........................................................... 105
4.
Conclusions ......................................................................................................................... 120
5.
References........................................................................................................................... 121
Annex 2: Review of innovative methods for retrofitting purposes - France .................................. 122
Buildings: Definition of technical innovative methods .................................................................. 123
3
Guidelines for the review process ................................................................................................ 123
Keywords and key-phrases ...................................................................................................... 123
Clarification of methods reviewing and classification ............................................................... 123
Content expected ........................................................................................................................ 124
Review of innovative methods for retrofitting purposes .................................................................. 124
Simulation tools: range of application.......................................................................................... 124
Presentation of some BES tools analyzed ..................................................................................... 125
ArchiWIZARD ........................................................................................................................... 125
DesignBuilder v3.4 ................................................................................................................... 126
DOE-2 ...................................................................................................................................... 126
Ecotect .................................................................................................................................... 127
EnergyPlus............................................................................................................................... 127
ESP-r........................................................................................................................................ 128
IES Virtual Environment (IES VE) .............................................................................................. 128
PHPP ....................................................................................................................................... 129
PLEIADES+COMFIE ................................................................................................................... 130
TRaNsient SYstem Simulation Program (TRNSYS 17) ................................................................ 131
Comparative synthesis of BES tools ............................................................................................. 131
Limitations of BES tools ............................................................................................................... 132
References .................................................................................................................................. 133
Open spaces: Definition of technical innovative methods ............................................................ 134
Guidelines for the review process ................................................................................................ 134
Keywords and key-phrases ...................................................................................................... 134
Clarification of methods .......................................................................................................... 134
Content expected ........................................................................................................................ 135
4
Assessment criteria ......................................................................................................................... 135
Thermal indices ........................................................................................................................... 135
Others indices ............................................................................................................................. 135
Review of innovative methods for retrofitting purposes .................................................................. 135
Presentation of some microclimate simulations tools analyzed ................................................... 136
BioKlima .................................................................................................................................. 136
CONFORT -EX........................................................................................................................... 137
ENVI-met ® .............................................................................................................................. 138
OTC Model ®............................................................................................................................ 139
OUTCOMES ............................................................................................................................. 139
RayMan ................................................................................................................................... 140
SOLWEIG-model ...................................................................................................................... 140
TownScope .............................................................................................................................. 141
Urbawind ................................................................................................................................ 141
Comparative synthesis of Microclimate Simulation tools ............................................................. 142
Limitations of Microclimate Simulation tools ............................................................................... 142
References .................................................................................................................................. 142
Annex 3: Review of innovative methods for retrofitting purposes – Spain ................................... 144
Buildings...................................................................................................................................... 144
Open spaces ................................................................................................................................ 158
Annex 4: Review of innovative methods for retrofitting purposes – Italy ..................................... 170
Review of innovative methods for public buildings retroffitting purpose ..................................... 171
Short description of tools and methods ....................................................................................... 172
Representative Case Studies ........................................................................................................ 173
Review of innovative methods for open spaces ........................................................................... 174
5
Innovative methods in the General Plans..................................................................................... 175
Innovative method from research point of view .......................................................................... 177
Conclusions ................................................................................................................................. 178
SIMULATION TOOLS (source: UHI CE project) .............................................................................. 179
6
Abstract
This report stands for a review of models and decision making methods, with applications found
mainly in the international scientific literature, which could be used for conducting technoeconomical studies in order to determine the optimal blends of retrofit measures for building energy
upgrading and Urban Heat Island mitigation in open spaces. The capabilities of innovative
computational tools targeted to the assessment of building energy performance and of microclimate
in open spaces are discussed in detail. Additionally, coupled simulation approaches between energy
and microclimate simulation models in order to evaluate the impact of the Urban Heat Island effect
on building energy performance, are presented as well. In parallel, decision making methods based
on the combination of the impact assessment models and optimization algorithms are described.
Finally, conclusions on the usefulness of the approaches found will be drawn in relation to the level of
use of these approaches in the partner Countries, while reasons that such methods are not widely
applied in practice will be identified.
7
1. Introduction
The building sector in the Europen Union is considered as the largest consumer of energy using up to
40% of the final energy consumption1. To evaluate the energy performance of both residential and
tertiary buildings, many parameters are required, such as the thermo-physical properties of the
envelope, ventilation, passive solar systems, indoor-outdoor physical interactions, energy end-uses,
building systems’ operating schedules, etc. Considering all these influencing factors, building energy
upgrading is not an easy task. Especially now with more strict regulations 1, building energy renovation
plans should be based on precise estimations of energy indicators as specific thresholds of these
indicators should be satisfied, and at the same time least-cost renovation measures should be
suggested.
On the other hand it is observed that over the last decade, heat waves have occurred across Europe,
particularly in Southern Europe. High densely built-up areas trap the heat, especially at night, causing
the so-called Urban Heat Island (UHI) effect in which city centers can be up to 10°C warmer than
surrounding rural areas2. A significant consequence of UHI is that energy consumption rises with the
increased use of air conditioners and refrigeration appliances. This means that a holistic
confrontation over the elevation of building energy efficiency should not disregard the impact of UHI
on energy consumption. Apart from benefiting building energy performance, UHI-mitigation projects
ensure comfortable and healthy open spaces for pedestrians.
The last decade, EU has presented efforts in terms of energy savings especially in the building sector.
For instance, the European Union established specific actions by introducing the EPBD (Energy
Performance of Building Directive)1, which suggests each EU state to target own energy efficiency
objectives. In addition, regarding the renovation of public buildings, the new directive 2012/27/EU 3
forces Member States to renovate each year 3% of the total floor area of public buildings in order to
achieve the energy efficiency objectives. As a consequence, different projects of passive building
emerged in Germany with PassivHaus, in Switzerland with Minergie and in France with Effinergie4,5.
To deal with the requirements of the latest EU directives, Member States have developed their own
methodologies and computational tools aiming to assess building energy performance in the prerenovation (or pre-construction) and the post-renovation (or post-construction) situation in order to
determine renovation measures. On the contrary, no such approach is adopted in case of UHI
mitigation in open spaces. Apart from traditional guidelines for spatial urban planning, no
computational tools and/or concrete methodologies are recommended to estimate microclimate and
environmental indicators in the study phase.
1
EPBD.On the energy performance of buildings. Official Journal of the European Union, Directive 2010/31/EU of the European Parliament
and of the Council; 2010.
2
http://www.urbanheatisland.info/
3
DIRECTIVE 2012/27/EU OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 25 October 2012 on energy efficiency.
4
Proposal-EPBD. Low energy building in Europe: current state of play, definitions and best practice; 2009.
5
Jean-Loup Bertez, The PASSIVE stake. Strategic overview on a global, structured and sustainable way for ‘‘efficient building’’. Zenergie;
2009.
8
Considering the issues raised above it becomes obvious that in order to comply with the latest energy
efficiency policies as well as to obtain sustainable built and urban environments, accurate methods
and computational tools to estimate the impact of retrofit options based on the aspects of building
and urban physics are required. The use of such methods is considered crucial even in the early study
phase, especially for major renovation projects, for the following reasons:
 They assess the pre-renovation situation revealing the energy consumption level of buildings
and microclimate conditions of open spaces. This capability contributes to the recognition of
vulnerable areas, energy savings potential and, generally, actual needs of the renovation
cases under consideration. The provision of such estimations contributes in determining and
prioritizing the interventions.
 They can be used to assess the impact of various interventions in a desk-study (fast and with
no cost) manner, i.e. computational tools may be executed for various design configurations
and calculate the corresponding values of performance indicators (energy indicators for
buildings and microclimate indicators for open spaces).
 In a more advanced level aiming at improving estimations’ accuracy, many computational
tools offer the possibility to conduct coupled simulations in order to account for the impact of
the UHI effect, i.e. of the local microclimate rather than relying on the wider climate zone, on
building energy consumption.
 In combination with optimization schemes and algorithms they support decision making
towards the determination of cost-effective renovation measures that ensure minimum
requirements of performance indicators, either energy or microclimate ones.
The present report provides an overview of commercial or commercially available computational
tools that can be used to assess building energy performance and UHI effect in open spaces. Initially,
the major categories of physical models are presented, i.e. multi-zonal or nodal models for building
energy performance assessments and field models for UHI assessments. The capabilities of the most
popular computational tools of each category will be presented together with case studies found in
scientific literature. Furthermore, nodal/field models coupling possibilities to assess UHI effect on
building energy consumption are discussed. In addition, integrated methodologies for decision
making based on optimization schemes and algorithms are presented. Finally, the research-oriented
level of use of computational tools, especially in partner Countries of the REPUBLIC-MED project, is
estimated based on scientific databases, and the major reasons of their limited applications for
building design purposes are identified.
In summary, the main goals of this review are the following:
 Revealing of innovative computational tools that can be used to assess building energy
performance and Urban Heat Island in open spaces
9
 Unfolding and contrasting the capabilities of computational tools
 Coupled simulation possibilities to account for the impact of UHI on indoor energy
consumption
 Decision making utilizing impact assessment computational tools and optimization algorithms
 Research-based level of use of innovative computational methods
Reasons of limited use of computational tools by building designers
2. Physical models
2.1 Building thermal behaviour modelling
Physical models are used to simulate the thermal behaviour in various buildings with their own
specific needs and uses, e.g. dwellings, offices, schools, etc. Some of them include models of space
heating6, natural ventilation7, air conditioning systems8, passive solar systems9, Photovoltaic panels10,
occupants’ behaviour11, etc. The physical modelling techniques are based on the solving of heat
transfer equations.
To solve such physical problems, a large number of numerical software are available. Many authors
proposed benchmarks to compare these software tools. Theoretically, each building software is able
to include thermal physical phenomena encounterred in buildings. Most computational tools provide
the choice to users to select the physical mechanisms and the associate equations required. However,
Crawley et al. (2008)12 showed that some tools omit moisture influences and, generally, the effects of
latent heat are neglected.
There are two major thermal building models categories currently used13:
 Field models, such as Computational Fluid Dynamics (CFD) models
 Multi-zonal or nodal models
6
Z. Liao & A.L. Dexter, A simplified physical model for estimating the average air temperature in multi-zone heating systems, Building and
Environment 39 (2004) 1013–22.
7
S. Louis et al., Optimizing opening dimensions for naturally ventilated buildings, Applied Energy 88 (2011) 2791-801.
8
W. Shengwei, Dynamic simulation evaluation of building VAV air-conditioning system and of EMCS on-line control strategies, Building
Simulation 34 (1999) 681-705.
9
I. Pyonchan et al., Estimation of lighting energy savings from daylighting, Building and Environment 44 (2009) 509-514.
10
J.A. Clarke et al., The simulation of photovoltaic-integrated building facades, Building Simulation 1997 (2) 189-195.
11
E. Azar & C.C. Menassa, A comprehensive analysis of the impact of occupancy parameters in energy simulation of office buildings,
Energy and Buildings 55 (2012) 841-853.
12
D.B. Crawley et al., Contrasting the capabilities of building energy performance simulation programs, Building and Environment 43 (2008)
661-673.
13
A. Foucquier et al., State of the art in building modelling and energy performances prediction: A review, Renewable and Susta inable
Energy Reviews 23 (2013) 272-288.
10
Since the REPUBLIC-MED project is focused on the application of the multi-zonal method in case of
building energy simulation, an extensive presentation of the principles of this method and available
computational tools to assess building energy performance is provided. As far as field models are
concerned, the project is focused on their uses for simulating the UHI effect in open spaces.
Therefore, an extensive overview of field modelling principles and computational tools targeted to
open spaces only is presented in section 2.2 below, while only a short presentation of their uses for
indoor airflows and building thermal simulation is provided.
2.1.1 Field models for indoor airflow assessments
The most complete field modelling approach in the thermal building simulation is the CFD method.
This is a microscopic approach of the thermal transfer modelling providing a detailed resolution of the
airflow pattern. It is based on the discretization of a building zone into a large number of control
volumes in the form of structured or unstructured mesh14.
The CFD approach is essentially based on the solution of the so-called Navier-Stokes equations14. A
large number of CFD software exists such as Fluent, COMSOL Multi-physics, MIT-CFD, Phoenics, etc,
most of them possessing additional capabilities to simulating indoor airflows and building thermal
behaviour. In general, they can be applied to every system involving fluid flow phenomena.
Advantages and application field of the CFD method
The CFD method is mainly employed for its ability to solve for mass, momentum, heat, chemical
species and turbulence parameters conservation equations. As a result, a CFD analysis produces a
detailed description of the airflow field within indoor environments including velocity vector
distribution (magnitude and direction), temperature distribution, chemical species dispersion, etc.
The prediction of the aforementioned properties of the flow field is very useful even in the early
design stages as it reveals areas with unpleasant draft and thermal discomfort, areas of pollutants’
confinement, for different design alternatives; hence, it helps the building designer to decide among
the design alternatives.
14
G.M. Stavrakakis et al., “Evaluation of thermal comfort in indoor environments using Computational Fluid Dynamics (CFD)”, In: Harris R.G.,
Moore D.P. (editors), Indoor Work and Living Environments: Health, Safety and Performance. Nova Science Publishers Inc., 2009, pp. 97166, ISBN: 978-1-61728-521-9.
11
Limitations of the CFD method
The main disadvantage of the CFD method is computational time due to the fact that a complete
detailed 3 dimensional description of a building with a very fine mesh is most often required.
However, given that the airflow in at least the 75% of the building volume is almost stagnant (velocity
magnitude below 0.5m/s)13, it is not always necessary to apply the CFD approach for the entire
building but only to specific parts, e.g. within spaces affected by installed Heating Ventilating and AirConditioning (HVAC) systems. This allows to reduce computational time significantly. For this reason,
the CFD is frequently coupled with less time-consuming thermal building simulation coupling
techniques, such as multi-zonal techniques or other statistical ones. For example, Tan and Glicksman
(2005)15 compared the full CFD simulation results with those obtained by the coupling between CFD
and a multi-zonal tool for modelling natural ventilation across large openings or atrium. They
demonstrated that the full CFD simulation would take more than 10 hours to converge, whereas the
coupled method needed less than one hour exhibiting similar accuracy.
2.1.2 The multi-zonal (nodal) approach
The multi-zonal approach assumes that each building zone is a homogeneous volume characterized
by uniform state variables. Thus, each zone is approximated as a node with a unique temperature,
pressure, pollutant concentration, etc. Generally, a node represents a room, a wall or the exterior of
the building, but it can also include more specific loads, such as internal occupancy, equipment gains,
heating/cooling systems, etc. The heat transfer equations are solved for each node and it can be
considered as one dimensional approach. A schematic representation of the multi-zonal approach is
illustrated in Figure 1.
Figure 1: Schematic representation of the multi-zonal method13.
15
G. Tan, L.R. Glicksman, Application of integrating multi-zone model with CFD simulation to natural ventilation prediction, Energy and
Buildings 37 (2005) 1049–57.
12
In international literature, one can find two main methods used for the multi-zonal approach13:
 Solution of the state variables transfer equations
 Finite difference method
Most software are designed based on the first technique. The finite difference method is notably
applied for nodal approaches using a description of heat transfer from electrical analogy, which has
been introduced by Rumaniovski et al. (1989) 16. The usefulness of this method lies on the fact that it
drastically simplifies the mathematical representation of the physical problem through a linearization
of the equations and thus reduced computational time.
Advantages and application field of the multi-zonal method
The major advantage of this method resides in its ability to describe the behaviour of a multiple-zone
building on a large time scale within reasonable computational resources and time. It is a particularly
well adopted technique for the estimation of energy consumption and the time evolution of the
space-averaged temperature into a room. Moreover, it can be used to predict air change rates and
the airflow-properties distribution between different rooms of a building. Some other applications,
such as the ventilation efficiency or the pollutant transport for entire buildings can also be studied by
this method17.
Limitations of the multi-zonal method
Due to the major simplification of disregarding the effects of non-uniform airflows within buildings,
the multi-zonal method presents the following limitations:
 The study of thermal comfort and air quality in thermal zones is difficult, as the variety of
physical (air velocity, relative humidity, temperature, etc.) and of personal parameters
(metabolic rates, clothing insulationa and occupancy density) within building zones are
considered negligible.
 The impact of heating and cooling loads on their close environment is not adequetely
addressed (for example, a radiator causing bouyant plumes, or an air blower causing air
drafts).
16
P. Rumaniovski et al, An adapted model for simulation of the interaction between a wall and the building heating system, In: Poceedings of
the thermal performance of the exterior envelopes of buildings IV conference Orlando, USA; 1989. p. 224–33.
17
Q. Chen. Ventilation performance prediction for buildings: a method overview and recent applications, Building and Environment 44
(2009) 848–858.
13
 Despite the fact that it is a well-adopted method to study multiple zone building, it is risky to
apply it in large spaces where significant non-uniformities of indoor airflow are expected.
Although it is a good option to visualize the distribution of pollutant concentration between building
zones, it prevents the assessment of local effects by a heat or pollutant source.
2.1.3 Comparative analysis of physical modelling methods
The previous paragraphs described two major methods to deal with building physics modelling. It
may be completed that the most complete method is the CFD. It provides a detailed view of the
physical mechanisms occurred in building systems. It is particularly adopted to solve for the
convective phenomenon that takes place in large building spaces. In such spaces, the convective
phenomenon, which causes airflow-parameters non uniformity, is well analyzed providing an
accurate prediction of the Convective Heat Transfer Coefficient (CHTC) and, thus, of heat trasnfer. On
the contrary, the multi-zonal approach underestimates CHTC and other variables heterogeneity in
these specific cases. However, it should be pointed out that it is difficult to conduct entire building
simulations using CFD due to the associated huge computational time. This is the major reason why it
is usually coupled with multi-zonal computational tools15.
On the other hand the multi-zonal method is really well adopted to treat global building physics
resolution assuming uniform airflow field in each thermal zone. The main objective of this method is
to simplify as far as possible the resolution system by linearizing the major part of the governing
conservation equations (when it is physicalle possible). As a result the technical complexity is
substantially reduced and so is the required time of computations. The multi-zonal method is more
appropriate when more “macroscopic” variables are of interest, such as building energy
consumption, rather than when assessing the airflow pattern is the main goal. It should be mentioned
however, that the airflow properties variations significantly affect indoor-outdoor interactions, and in
this way the envelope thermal behaviour, causing variations in systems’ operation schedules, which
in turn influences building energy consumption. In this sense the computational tool or method used
to conduct a building energy study requires experience to understand which tool is more appropriate
or to know when coupled multizonal/field modelling approaches are required for more accurate and
reliable studies. A summary of the capabilities of the methods discussed above is reported in Table 1.
Table 1: Summary of building-physics simulation methods.
Method
Technical approach
Application field
Advantages
Drawbacks
CFD
A building zone is further
discretized into control
Contaminant
distribution;
Indoor air quality;
Detailed
description of
the airflow field
High
computational
time;
14
Multizonal
volumes.
HVAC systems.
within large
spaces in
buildings.
requirements for
high
computational
resources;
modelling
complexity.
A building is discretized into
thermal zones, often being
rooms. The state variables are
considered uniform in each
zone.
Determination of
total energy
consumption;
indoor average
temperature;
cooling/ heating
loads; Time
evolution of
energy
consumption.
Whole building
energy
simulation over
long time
periods;
reasonable
computatio-nal
time within
modest
computatio-nal
resources.
Difficulty to study
large volume
systems; Unable
to study local
effects as heat or
pollutant source.
It should be clarified that the techniques described above need input parameters, such as the
meteorological data, thermo-physical properties of the building envelope, occupancy parameters,
systems’ operating schedules, etc. Obviously, all these parameters are interpreted with a degree of
uncertainty. In addition to these uncertainties, there are certain assumptions adopted in order to
reduce the complexity of building physical mechanisms. The combination of uncertainties in
interpreting collected data (physical, materials and occupancy-related) with the adoption of
assumptions often leads to discrepancies between the simulated results and reality. The major
challenge scientists and engineers currently face is to reduce uncertainties without compromizing
simulations’ time, practicability and accuracy.
Several solutions consisting in decreasing the system size exist and some of them have been
described in scientific literature18,19. Another idea is to reduce the detail of building geometry by
merging rooms or merging walls. Such simpli- fications should speed up significantly the
computational time. Generally, an important drawback of the physical formulation is the fact that it
suggests a detailed description of the physical behaviour. Therefore, it implies expensive knowledge
on the physical system, especially on the mechanisms occurring inside and outside the building
geometry. Within the scope of the REPUBLIC-MED project is to understand the available methods to
18
S. Goyal, P. Barooah, A method for model-reduction of non- linear thermal dynamics of multi-zone buildings, Energy and Buildings 47
(2012) 332–40.
19
I. Hazyuk etal., Optimal temperature control of intermittently heated buildings using model predictive control: Part I—building modelling,
Building and Environment 52 (2012) 379–87.
15
assess building energy performance and to acknowledge the most appropriate computational tools
and their combinations in order to balance accuracy and practicability in terms of easiness to use and
of calculation time. In the next subsection the most popular and widely used building energy (mainly
multi-zonal) simulation tools are described highlighting their strengths and weaknesses.
2.1.4 Building energy simulation tools
There is indeed a vast amount of available computational tools for building energy simulation
purposes. The US Department of Energy has developed a directory of building energy software tools20
which reports 402 building software tools for evaluating energy efficiency, renewable energy and
sustainability in buildings. The energy tools listed in the directory include databases, spreadsheets,
component and systems’ analysis and whole building energy simulation programs. The current report
is focused on the most popular tools used mainly for whole building energy or/and thermal
performance assessments purposes. A short description of the capabilities of each tool is provided
and a summary of their characteristics (Strengths, Weaknesses and special features) is reported in
Table 2. The tools of interest are:
 Autodesk Green Building Studio
 BEAVER
 BSim
 DeST
 DOE-2
 ECOTECT
 ENER-WIN
 Energy plus
 eQUEST
 ESP-r
 IDA Indoor Climate and Energy (IDA-ICE)
 IES Virtual Environment (IESVE)
 SUNREL
20
http://apps1.eere.energy.gov/buildings/tools_directory/
16
 TAS
 TRNSYS
2.1.4.1 Autodesk Green Building Studio
The Autodesk Green Building Studio web-based service21 allows users to perform fast, whole building
energy, water, and carbon emission analyses of a building design. This analysis can be performed by
architects directly over the Internet from within their own design environment. This streamlines the
entire analysis process and allows architects to get immediate feedback on their design alternatives—
making green design more efficient and cost effective.
Based on the building’s size, type, and location (which drives electricity and water usage costs), the
web-based service determines the appropriate material, construction, system and equipment
defaults by using regional building standards and codes to make intelligent assumptions. Using simple
drop-down menus, architects can quickly change any of these settings to define specific aspects of
their design; a different building orientation, a lower U-value window glazing, or a 4-pipe fan coil
HVAC system for example.
The service uses precise hourly weather data, as well as historical rain data as inputs. It also uses
emission data for electric power plants across the United States and includes the broad range of
variables needed to assess carbon neutrality. Usually within minutes, the service calculates a
building’s carbon emissions and the user is able to view the output in a web browser, including the
estimated energy and cost summaries as well as the building’s carbon neutral potential. Users can
then explore design alternatives by updating the settings used by the service and rerunning the
analysis, and/or by revising the building model itself. The output also summarizes the water usage
and costs and electricity and fuel costs, calculates an ENERGY STAR score, estimates photovoltaic and
wind energy potential, calculates points towards LEED daylighting credit, and estimates natural
ventilation potential. Unlike most analysis output, the Autodesk Green Building Studio report is very
easy to understand—giving architects and other users the information they need to make greener
design decisions.
2.1.4.2 BEAVER
BEAVER22 is a WINDOWS environment for the APEC ESPII Building Energy Estimation Program. It
provides user friendly input of data, processing and viewing of the results. The program estimates the
energy consumption of a building over a given period of time taking into account the site location, the
building structure and the type of building services installed to maintain the desired environmental
21
22
http://usa.autodesk.com/green-building-studio/
http://members.ozemail.com.au/~acadsbsg/
17
conditions. It enables a designer to investigate alternatives and make energy comparisons quickly and
effectively for a very wide range of building configurations and air conditioning systems using actual
measured climatic data.
Data input is interactive (mouse driven) via WINDOWS dialogue boxes, selection lists drop down lists
and entry fields on a series of screens running through general Project information to individual space
data and for all the building services plant, capacities, operating schedules, etc.
A comprehensive range of air handling systems, primary plant and control strategies enable
modelling of a wide range of building services. The Air Handling system type is selected from a series
of graphics which display the details included with the unit. To this basic system various extra
components or operating strategies can be added including Heat Recovery, Preheat Coils, Exhaust
Fan, Temperature reset on heating and cooling coils, etc.
An extensive application study of BEAVER for assessing building energy performance was presented
by ACADS-BSG Pty Ltd in conjuction with Elms Consulting Engineers23. The software was used to
review and provide comments on suitability of the climate zones proposed in terms of the theoretical
energy use as well as to propose a principal location within each zone that can be used to represent
the thermal response of the predefined buildings within that zone and identify the minimum number
of other locations needed to define the upper and lower extremes of thermal response within each
zone. The substrates used for the review of zones were various types of office buildings with and
without infiltration conditions. The software was successfully used for the revision of climate zones
used as inputs to assess building energy performance.
2.1.4.3 BSim
BSim24 provides user-friendly simulation of detailed, combined hygrothermal simulations of buildings
and constructions. The package comprise the modules: SimView (user interface and graphic model
editor), tsbi5 (simultaneous thermal and moisture building simulation tool), XSun (dynamic solar and
shadow simulation and visualisation), SimLight (daylight calculation tool), SimDXF (CAD import
facility) and SimPV (building integrated PV-system calculation). Furthermore there are export facilities
to external tools: Be06 (Danish compliance checker), Radiance (advanced light simulations), boundary
conditions for CFD simulations and visualisation in tools using DirectX input files.
BSim has been used extensively over the past twenty years and it is the most commonly used tool in
Denmark, and with increasing interest abroad, for energy design of buildings and for moisture
analysis12. BSim applies the quasi-steady approach in building modelling, and it is often used for
phase change materials modelling using the heat capacity method 25. The simulation time-step has to
23
ACADS-BSG Pty Ltd, ABCB Energy modelling of office buildings for climate zoning, Australian Building Codes Board, May 2002.
www.bsim.dk
J. Rose et al., Numerical method for calculating latent heat storage in constru ctions containing phase change material building simulation
2009, In: 11th international IBPSA conference. Glasgow, Scotland; 2009.
24
25
18
be small for accurate predictions. The BSim software has been successfully applied for the
determination of the effect of the basic heat gains on building energy consumption by Sikula et al.
(2012)26 and it was demonstrated that the highest heat gain comes from solar radiation. Model
validation procedures showed a deviation of only 8% between the simulated annual energy
consumption and the measured one. Finally, applications of the BSim, among other tools used, may
be also found in a report under the International Energy Agency (IEA) Programme for energy
conservation in buildings and Community systems27. The software was used mainly to simulate
energy performance of typical residences located in different locations (climatic zones) in the prerenovation situation in order to assess the impact of different climatic conditions on building energy
consumption.
2.1.4.4 DeST
Designer’s Simulation Toolkits (DeST)28 allows detailed analysis of building thermal processes and
HVAC system performance. DeST comprises a number of different modules for handling different
functions: Medpha (weather data), VentPlus (natural ventilation), Bshadow (external shading),
Lighting and CABD (CAD interface). The BAS (Building Analysis and Simulation) performs hourly
calculations for indoor air temperatures and cooling/heating loads for buildings, including
complicated building geometries with high number of rooms.
It is an annual building energy consumption tool and it has five main simulation stages: building
thermal process, system scheme analysis, Air Handling Units (AHU) analysis, duct/pipe networks and
plant analysis. These simulation stages provide accurate results to fulfill the needs for different stages
of building system design. An advanced multi-zone heat and mass balance methodology based on
state space method is applied in building thermal environment simulations with high accuracy. In
addition, a three-dimensional dynamic heat trasnfer methodology for annual simulation which is easy
to compute the heat transfer of a ground-coupled envelope. A significant strength of DeST is that it
provides coupling with CFD with hourly building simulation.
The main objective, structure and core programs of DeST are described by Yan et al. (2008a) 29. The
analytical verifications, interprogram comparisons and validation of the software are also presented.
Examples from a pilot building are presented to demonstrate the entire process of aiding design with
DeST are presented by Yan et al. (200b)30.
26
O. Sikula et al., Numerical simulation of the effect of heat gains in the heating season, Energy Procedia 14 (2012) 906-912.
G. Zweifel, Retrofit simulation report- IEA ECBCS Annex 50 “Prefabricated systems for low energy renovation of residential buildings,
Energy Conservation in Buildings and Community Systems Programme, March 2011.
28
www.dest.com.cn
29
D. Yan et al., DeST-An integrated building simulation toolkit, Part I: Fundamentals, Building Simulation 1 (2008a) 95-110.
30
D. Yan et al., DeST-An integrated building simulation toolkit, Part II: Applications, Building Simulation 1 (2008b) 193-209.
27
19
2.1.4.5 DOE-2
DOE-231 predicts the hourly energy use and energy cost of a building given hourly weather
information, a building geometric and HVAC description, and utility rate structure. It has one
subprogram for translation of input (BDL processor) and four simulation subprograms (LOADS,
SYSTEMS, PLANT and ECON). LOADS, SYSTEMS and PLANTS modules are executed in sequence, with
the output of LOADS becoming the input of systems, etc. The output then becomes the input to the
ECONOMICS module. Each of the simulation subprograms also produces printed reports of the results
of its calculations.
DOE-2 has been used extensively for more than 25 years for both building design studies, analysis of
retrofit opportunities, and for developing and testing building energy standards in the US and around
the world. Lam et al. (2008)32 used DOE-2 for the energy analysis of office buildings in the five major
climatic zones in China. Zhou and Park (2012)33 used DOE-2 to demonstrate how much energy use is
reduced when a building energy management and control system is applied in a representative large
office building. Using DOE-2 the optimal temperature schedule that saves the most energy was
identified. In terms of accuracy, it was shown that a difference of only 6% was observed between the
simulated and actual annual average hourly electric demand profile.
2.1.4.6 ECOTECT
ECOTECT34 is a highly visual architectural design and analysis tool that links a comprehensive threedimensional modeler with a wide range of performance analysis functions covering thermal, energy,
lighting, shading, acoustics and cost aspects. Whilst its modelling and analysis capabilities can handle
geometry of any size and complexity, its main advantage is a focus on feedback at the earliest stages
of the building design process.
In addition to standard graph and table-based reports, analysis results can be mapped over building
surfaces or displayed directly within the spaces. This includes visualization of volumetric and spatial
analysis results, including imported 3D CFD data. Real-time animation features are provided along
with interactive acoustic and solar ray tracing that updates in real time with changes to building
geometry and material properties.
ECOTECT is driven by the concept that environmental design principles are most effectively addressed
during the conceptual stages of design. The software responds to this by providing essential visual
and analytical feedback from even the simplest sketch model, progressively guiding the design
process as more detailed information becomes available. The model is completely scalable, handling
31
doe2.com
J.C. Lam et al., Building energy efficiency in different climates, Energy Conversion and Management 49 (2008) 2354-2366.
33
D. Zhou & S.H. Park, Simulation-assisted management and control over building energy efficiency-A case study, Energy Procedia 14
(2012) 592-600.
34
www.ecotect.com
32
20
simple shading models to full-scale cityscapes. Its extensive export facilities also make final design
validation much simpler by interfacing with many focused analysis tools, such as EnergyPlus.
Carlos and Nepomuceno (2012)35 used ECOTECT for producing simulated hourly values of energy
demand in order to validate several simplified methodologies for building energy performance
assessments. Knight et al. (2007)36 applied ECOTECT for the energy analysis of an educational building
and compared simulated data with actual energy consumption measurements. They highlighted the
following reasons of the observed discrepancies:
 Rough estimation of the internal gains or activities in each space
 Imprecise interpretation of the schedules of occupancy and equipment use
 Uncertainties in estimating ventilation rates
 Imprecise estimation of equipment loads in use
 Weather data were taken from the wider climate zone
2.1.4.7 ENER-WIN
The ENER-WIN37 software originally developed at Texas A&M University. It simulates hourly energy
consumption in buildings, including annual and monthly energy consumption, peak demand charges,
peak heating and cooling loads, solar heating fraction through glazing, daylighting contribution and a
life-cycle cost analysis. Design data are tabulated by zones, also providing duct sizes and electric
power requirements.
The software is composed of several modules-an interface module, a weather data retrieval module,
a sketching and an energy simulation module. The interface module includes a rudimentary buildingsketching interface. ENER-WIN requires the following inputs: the building type, location and
geometrical data, external ground condition, internal use patterns and load densities (e.g. for
occupancy, lighting, small equipment and domestic hot water), and heating and cooling inputs
(ventilation rate and schedules, thermostat settings and heating/cooling equipment types, systems’
efficiency and set points).
ENER-WIN was applied by Soebarto & Williamson (2001) 38 for the development of a multi-criteria
decision-making approach based on the “Reference Building” concept. Using the databases of
35
J.S. Carlos & M.C.S. Nepomuceno, A simple methodology to predict heating load at an early design state of dwellings, Energy a nd
Buildings 55 (2012) 198-207.
36
I. Knight et al., Assessing the operational energy profiles of UK educational buildings: findings from detailed surveys and modelling
compared to measured consumption, 2 nd PALENC Conference and 28 th AIVC Conference on Building Low Energy Cooling and Advanced
Ventilation Technologies in the 21st Century, September 2007, Crete, Greece.
37
http://pages.suddenlink.net/enerwin/
38
V.I. Soebarto & T.J. Williamson, Multi-criteria assessment of building performance: theory and implementation, Building and Environment
36 (2001) 681-690.
21
building materials, climate conditions and systems, incorporated in the ENER-WIN tool, they
integrated an approach of creating a reference building which satisfies ASHRAE Standard 90.139
requirements. The energy performance of the actual building was evaluated based on the deviations
between the actual and reference building and it was concluded that the approach was useful for
testing different design strategies.
2.1.4.8 EnergyPlus
EnergyPlus40 is a modular, structured code based on the most popular features and capabilities of
BLAST41 and DOE-2. It is a simulation engine with input and output of text files. Loads are calculated
by a heat balance engine at a user-specified time-step and they are passed to the building systems
simulation module at the same time-step.
The EnergyPlus building systems simulation module, with a variable time-step, calculates heating and
cooling system and electrical system response. This integrated solution provides more accurate space
temperature prediction, which is crucial for system and plant sizing, occupant comfort and occupant
health calculations. Integrated simulation also allows users to evaluate realistic system controls,
moisture adsorption and desorption in building elements, radiant heating and cooling systems and
interzone airflow.
Tsikaloudaki et al. (2012)42 used EnergyPlus to evaluate the cooling performance of a wide variety of
geometrical, thermo-physical and optical properties of windows. The analysis showed that the
contribution of the windows in determining cooling loads is maximized when their solar
transmittance is high and their thermal transmittance is low. It was demonstrated that in the
Mediterranean regions the increased thermal efficiency of transparent elements in buildings with
controlled ventilation, such as in offices, prohibits the dissipation of heat towards the ambient
environment and ultimately result in higher cooling energy loads.
Goia et al. (2013)43 used EnergyPlus within the context of developing a methodology to determine the
optimal transparent percentage in a façade module for low energy office buildings. The investigation
was carried out in temperate oceanic climate for three different design versions of the office building
and with different HVAC system’s efficiency. It was shown that, regardless of the orientation and of
the façade area of the building, the optimal configuration is achieved when the transparent
percentage is between 35% and 45% of the total façade module area.
39
ASHRAE Standard 90.1. Energy efficient design of new buildings except low-rise residential buildings. American Society of Heating
Refrigerating and Air-conditioning Engineers, Inc. Atlanta, GA, 1989.
40
www.energyplus.gov
41
www.bso.uiuc.edu/BLAST
42
K. Tsikaloudaki et al., Assessing cooling energy performance of windows for office buildings in the Mediterranean zone, Energy and
Buildings 49 (2012) 192-199.
43
F. Goia et al., Optimizing the configuration of a façade module for office buildings by means of integrated thermal and lighting simulations
in a total energy perspective, Applied Energy 108 (2013) 515-527.
22
2.1.4.9 eQUEST
eQUEST44 is an easy to use building energy analysis tool which provides high quality results by
combining a building creation wizard, an energy efficiency measure wizard and a graphical results
display module with an enhanced DOE-2 derived building energy simulation program. The building
creation wizard directs a user through the process of creating a building model. Within eQUEST, DOE2 performs an hourly simulation of the building based on walls, windows, glass, people, plug loads
and ventilation. The incorporated DOE-2 simulation module also simulates the performance of fans,
chillers, boilers and other energy consuming devices. eQUEST allows users to create multiple
simulations of alternative designs and view the corresponding results in side-by-side graphs
(parametric analysis). It offers energy-cost estimating, daylighting and lighting system control as well
as automatic implementation of energy efficiency measures (by selecting preferred measures from a
list).
Azar & Menasa (2012)45 used eQUEST to conduct a sensitivity analysis on the occupancy behavioural
parameters of typical office buildings of different size and in different climate zones. Significant
sensitivity levels were observed, varying according to both building size and weather conditions. The
highest sensitivity was obtained when varying the “heating temperature set point” parameter in
small-size buildings located in dry climatic conditions.
2.1.4.10 ESP-r
ESP-r46 is a general purpose, multi-domain- building thermal, interzone airflow, intra-zone air
movement, HVAC systems and electrical power flow- simulation environment which has been under
development for more than 25 years. ESP-r has the objective of simulation building performance in a
manner that: (a) is realistic and adheres closely to actual physical systems, (b) supports early-throughdetailed design stage appraisals, and (c) enables integrated performance assessments. By addressing
all design and systems’ aspects simultaneously, ESP-r allows the designer to explore the complex
relationships between a building’s form, fabric, airflow, plant and control.
ESP-r is based on a finite volume conservation approach in which a problem is transformed into a set
of conservation equations (for energy, mass, momentum, etc.) which are then integrated at
successive time-steps in response to climate, occupant and control system influences. It comprises a
central Project Manager around which are arranged support databases, a simulator, various
performance assessment tools and a variety of third party applications for CAD, visualization and
report generation.
44
http://www.doe2.com
E. Azar & C.C. Menassa, A comprehensive analysis of the impact of occupancy parameters in energy simulation of office buildings,
Energy and Buildings 55 (2012) 841-853.
46
http://www.esru.strath.ac.uk/
45
23
Hoseggen et al. (2008)47 applied ESP-r to conclude whether a double-skin façade should be applied to
the east façade of an office building in Trodheim, Norway, towards the reduction of heating demand.
The paper also demonstrates how a double-skin façade with controllable windows and hatches for
natural ventilation can be implemented in the simulation program. It was concluded that in case of a
standard window, the energy demand for heating was 20% higher for the single-skin façade in
comparison to the double-skin one. However, in case of windows with improved U-value, the
difference in energy demand was almost evened out between singe- and double- skin façade
configurations. Bourgeois et al. (2006)48 studied the occupancy behavioural patterns on building
energy consumption using ESP-r as a building energy simulation tool. They demonstrated the
implementation and integration of a sub-hourly occupancy-based control model which enabled
advanced behavioural models. It was shown that building occupants that actively seek daylighting
rather than systematically relying on artificial lighting can reduce overall primary energy expenditure
by more than 40% in comparison with occupants relying on constant artificial lighting. As far as the
impact of window-related behaviour is concerned, Rijal et al. (2007)49 presented a research study
focusing on the interpretation of window-related behaviour, its modelling and the exploration of its
effects on comfort and energy consumption. Initially, a field survey provided the behavioural
patterns, and based on this information a logistic regression analysis was followed to formulate an
adaptive algorithm to predict the likelihood that windows are open. This algorithm when embedded
in simulation software provided insights not emerged by common simulation methods, and it allowed
the quantification of the effect of building design on window opening behaviour on energy
consumption.
2.1.4.11 IDA Indoor Climate and Energy (IDA-ICE)
IDA ICE50 software is based on a general simulation platform for modular systems, the IDA simulation
environment. It is a whole year detailed and dynamic multi-zone simulation application for the study
of indoor climate as well as energy. The physical models of IDA ICE reflect the latest research and best
models available, and results compare well with measured data. While serving a global market, IDA
ICE is adapted to local languages and requirements (climate data, standards, special systems, special
reports, and product and material data). The IDA ICE user interface is designed to make it easy to
build and simulate both simple and advanced cases, and the real-time 3D environment, in
combination with comprehensive tables, provides optimal feedback. A simple procedure for
calculating and reporting cooling, heating, air demand, and energy, together with a built-in version
handling system, makes it easy and efficient to compare different systems and results.
R. Hoseggen et al., Building simulation as an assisting tool in decision making. Case study: With or without a double-skin façade?, Energy
and Buildings 40 (2008) 821-827.
48
D. Bourgeois et al., Adding advanced behavioural models in whole building energy simulation: A study on the total energy impact of
manual and automated lighting control, Energy and Buildings 38 (2006) 814-823.
49
H.B. Rijal et al., Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings,
Energy and Buildings 39 (2007) 823-836.
50
www.equa.se/ice
47
24
Physical systems from several domains are in IDA described using symbolic equations, stated in either
or both of the simulation languages Neutral Model Format (NMF) or Modelica. IDE ICE offers
separated but integrated user interfaces to different user categories:
 Wizard interfaces lead the user through the steps of building a model for a specific type of
study. The internet browser based IDA Room wizard calculates cooling and heating load.
 Standard interface for users to formulate a simulation model using domain specific concepts
and objects, such as zones, radiators and windows.
 Advanced level interface- where the user is able to browse and edit the mathematical model
of the system.
 NMF and/or Modelica programming for developers.
Salvalai (2012)51 used IDA ICE as a building energy simulation platform within which a water-to-water
heat pump model was implemented. Results obtained were in good agreement with experimental
data. Hesaraki and Holmberg (2013) also used IDA ICE to investigate the impact of low-energy heating
systems in newly built semi-detached dwellings in Stockholm, in relation to the Swedish building
regulations. They demonstrated that the installation of heating systems in combination with underfloor and ventilation radiators not only met energy requirements of regulations but also provided
thermal comfort. Numerical results were validated with measured data.
2.1.4.12 IES Virtual Environment (IESVE)
IESVE52 is a powerful, in-depth suite of building performance analysis tool. It allows the design and
operation of comfortable buildings that consume significantly less energy. Whether working on a new
building or existing building renovation project, IESVE offers the ability to test different options,
identify best passive solutions, compare low-carbon and renewable technologies and draw
conclusions on building energy indicators.
There are various tools in the suite, each designed to provide sustainable analysis at levels suitable
for different design team members and design stages. The main modules included in this software are
the following:
 Model-IT- geometry creation and editing
 ApacheCalc- loads analysis
 ApacheSim- thermal
51
G. Salvalai, Implementation and validation of simplified heat pump model in IDA-ICE energy simulation environment, Energy and
Buildings 49 (2012) 132-141.
52
http://www.iesve.com/
25
 MacroFlo- natural ventilation
 Apache HVAC- component-based HVAC
 SunCast- shading visualization and analysis
 MicroFlo- 3D CFD
 FlucsPro/Radiance- Lighting design
 DEFT- model optimization
 LifeCycle- life cycle energy and cost analysis
 Simulex- building evacuation
Murray et al. (2012)53 applied IESVE to plan a retrofitting project of a case study building located at
Cork University College, for which both modelling and actual interventions were applied. This
approach allowed the comparison between simulated and measured data and a good agreement
between them was concluded. Ouedraogo et al. (2012)54 used IESVE to investigate the impact of
climate change on future trends of electricity demand for air-conditioning in public buildings within
the period 2010-2080. Their study highlights the fact that the predicted mean temperature using a
specific climate change data scenario will increase by about 2 0C by 2050 and a significant increase in
air-conditioning energy consumption was demonstrated for case-study buildings in the Burkina Faso
built environment. For this specific region, they concluded that shading devices could reduce the
cooling load by 40%, thus they could play an important role in climate change adaptation.
2.1.4.13 SUNREL
SUNREL55 developed by the National Renewable Energy Laboratory (NREL)56 is a hourly building
energy simulation program that aids in the design of small energy efficient buildings where the loads
are dominated by the dynamic interactions between the building envelope, environment and
occupants. It has a simplified multi-zonal airflow algorithm that can be used to calculate infiltration
and natural ventilation. Users can enter exact optical interactions of windows with identical layers of
clear or tinted glass and no coatings on the layers. Thermal properties are modelled with a fixed Uvalue and fixed interface coefficients.
SUNREL is especially well suited for passive solar buildings and includes algorithms for Trombe walls,
advanced glazings, schedulable window shading, active-charge/passive-discharge thermal storage
53
S.N. Murray et al., Static simulation: Asufficient modelling technique for retrofit analysis, Energy and Buildings 47 (2012) 113-121.
B.I. Ouedraogo et al., Future energy demand for public buildings in the context of climate change for Burkina Faso, Building and
Environment 49 (2012) 270-282.
55
http://www.nrel.gov/buildings/sunrel/
56
http://www.nrel.gov/
54
26
and natural ventilation. The model representation of the building is a thermal network solved with
forward finite differencing among other techniques. In addition, a simple graphical interface aids in
creating input and viewing output.
Elzafraney et al. (2005)57 used SUNREL to demonstrate the benefit of enhanced concretes containing
coarse aggregates of recycled plastics. The tool was used to simulate the thermal and building energy
performance of two building configurations with and without polymer aggregates and it was founf
that the former one led to a substantial reduction of of heating and cooling loads while ensured
thermal comfort.
2.1.4.14 TAS
TAS58 is a suite of software products, which simulate the dynamic thermal performance of buildings
and their systems. The main module is the TAS Building Designer, which performs dynamic building
simulation with integrated natural and forced airflow. It has a 3D graphics-based geometry input that
includes a CAD link. TAS systems is a HVAC systems/controls simulator, which may be directly coupled
with the building simulator. It performs automatic airflow and plant sizing and total energy demand.
The third module, TAS Ambiens, is a robust and simple to use 2D CFD package which produces a cross
section of microclimate variation in space.
TAS combines dynamic thermal simulation of the building structure with natural ventilation
calculations, which include advanced control functions on aperture opening and the ability to
simulate complex mixed mode systems. The software has heating and cooling plant sizing procedures,
which include optimum start.
Wong at al. (2009)59 used Tas to investigate the impact of vertical greenery systems on the
temperature and energy consumption of buildings. The results revealed a linear correlation between
shading coefficient and leaf area where a lower shading coefficient leads to a greater thermal
insulation. As far as the use of TAS for understanding the influence of different architectural
strategies in energy demand is concerned, Pino et al. (2012) 60 demonstrated its efficient use for such
purposes especially for office buildings.
2.1.4.15 TRNSYS
TRNSYS (Transient system simulation program)61 is a program with modular structure that
implements a component-based approach. Its components may be as simple as a pump or pipe, or as
57
Elzafraney et al., Development of energy-efficient concrete buildings using recycled plastic aggregates, Journal of Architectural
Engineering DOI: 10.1061/(ASCE)1076-0431(2005)11:4(122)
58
http://www.edsl.net/
59
N.H. Wong et al., Energy simulation of vertical greenery systems, Energy and Buildings 41 (2009) 1401-1408.
60
A. Pino, Thermal and lighting behaviour of office buildings in Santiago of Chile, Energy and Buildings 47 (2012) 441-449.
61
http://sel.me.wisc.edu/trnsys
27
complex as a multi-zone building model. The components are configured and assembled using a fully
integrated visual interface known as the TRNSYS Simulation Studio, while building input data is
entered through a dedicated visual interface (TRNBuild).
The simulation engine then solves the system of algebraic and differential equations that represent
the whole energy system. In building simulations, all HVAC system components are solved
simultaneously with the building envelope thermal balance and the air network at each time-step. In
addition to a detailed multi-zone building model, the TRNSYS library includes components for solar
thermal and photovoltaic systems, low energy buildings and HVAC systems, renewable energy
systems, cogeneration, fuel cells, etc.
The modular nature of TRNSYS facilitates the addition of new mathematical models to the program.
New components can be developed in any programming language and modules implemented using
other software (e.g. Matlab/Simulink, Excel/VBA) can also be directly embedded in a simulation.
TRNSYS can generate redistributable applications that allow non-expert users to run simulations and
parametric studies.
Ibanez et al. (2005)62 used TRNSYS to simulate the impact of Phase Change Materials (PCM)
integrated in walls, ceiling and floor of an experimental room built with concrete panels with PCM, on
the whole building energy balance. An acceptable agreement between the simulated and
experimental results was obtained. Beausoleil-Morrison et al. (2012)63 demonstrated an ESPr/TRNSYS co-simulator which was applied for evaluating the performance of a solar-thermal system in
a low-energy building. It was shown that this co-simulation environment is an effective tool for
studying and designing solar buildings, particularly when architectural and energy conversion and
storage systems are integrated.
62
M. Ibanez et al., An approach to the simulation of PCMs in building applications using TRNSYS, Applied Thermal Engineering 25 (2005)
1796-1807.
63
I. Beausoleil-Morrison et al., Demonstration of the new ESP-r and TRNSYS co-simulator for modelling solar buildings, Energy Procedia
30 (2012) 505-514.
28
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
Strengths
Weaknesses
Autodesk
Green
Building
Studio
> Provision of
hourly whole
building energy,
carbon and
water analysis
> Reduces
design and
analysis costs,
allowing more
design options
to be explored
> Accelerates
analysis for LEED
compliance
> Resulting DOE2 and EnergyPlus
models can be
very detailed
Handling of
climate
conditions
> Input available
data of specific
climate zones
> User-defined
climate-data
time series
Handling of
building systems
operating
schedules and
occupancy
> User-defined
schedules
Building systems
> Common
building
systems for
heating, cooling,
Domestic Hot
Water (DHW),
etc.
> Determination
of renewable
energy potential
(Photovoltaic
and wind)
Most
common
applications
Whole
building
thermal
performance
Availability
Subscription
web-based
service
29
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
BEAVER
Strengths
Weaknesses
> Hourly whole
building energy
consumption
> Estimation of
building
structure and
systems' types
to maintain
specific
environmental
conditions
> Modelling of a
wide range of
building services
> inputting of
data can be very
rapid compared
to most other
similar programs
> Some system
types are not
included and it
does not model
chilled and
condenser water
loops
> limited range
of windows
available for
selection
> It cannot
model natural
ventilation or
daylighting
Handling of
climate
conditions
> Input available
data of specific
climate zones
> User-defined
climate-data
time series
(measured or
simulated)
Handling of
building systems
operating
schedules and
occupancy
> User-defined
schedules
Building systems
> Detailed
representation
of heating and
cooling systems
> Various extra
components or
operating
strategies can be
added including
Heat Recovery,
Preheating Coils,
Exhaust Fan,
Temperature
reset on heating
and cooling coils,
etc.
Most
common
applications
Whole
building
energy
performance
Availability
Commercial
30
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
Bsim
Strengths
> Easy-to-use and
flexible programs
for evaluating the
indoor climate and
energy conditions
as well as the
designing of the
heating, cooling
and ventilation
plants
> Simultaneous
simulation of
energy and
moisture transfer
in building
constructions
> Multi zone air
flow simulations.
Intuitive graphic
user interface
> Accurate
representation of
building systems
Weaknesses
> No
standardized
result reports
> No support of
geometrical
input from CAD
tools
Handling of
climate
conditions
> It has a built-in
function for
converting text
formatted hourly
data to the
binary format
> User-defined
climate-data
time series
> Pre-defined
climate zone
data
Handling of
building systems
operating
schedules and
occupancy
> Default library
of
systems'
schedules
> User-defined
schedules
Building systems
> Automatic
control
strategies for
each ventilation
plant
> heating and
cooling radiators
> Ventilators
Most
common
applications
> Phase
Change
Materials
> Whole
building
energy
performance
Availability
Commercial
31
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
DeST
Strengths
Weaknesses
> Annual building
energy
consumption
> An advanced
multi-zone heat
and mass balance
methodology
based on state
space method is
applied
> Adoptation of a
three-dimensional
dynamic heat
transfer
methodology for
annual simulation
> overall
simulation
capabilities
through scientific
calculation
method
> Coupled indoor
CFD simulations
> Relatively slow
in exporting
resulting reports
Handling of
climate
conditions
Handling of
building systems
operating
schedules and
occupancy
> Predefined
climatic zone
data
> User-specified
climate-data
time series
> Default library
of
operating
schedules
> User-defined
schedules
Building systems
> Default library
of HVAC
equipment and
control
> Common
systems for
heating, cooling
and DHW
Most
common
applications
Availability
> Mainly for
Free
HVAC
systems
design
> Systems
scheme
analysis
> Air Handling
Units
(AHU)
analysis
> Whole
building
energy
perforamance
32
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
DOE-2
Strengths
> Detailed hourly
whole building
energy
analysis
> multiple zones
in buildings of
complex
design
> Widely
recognized as
the industry
standard
Weaknesses
> Requires high
level of user
knowledge
Handling of
climate
conditions
> Predefined
hourly weather
files of the
climate zone
> User-defined
climate-data
time series
Handling of
building systems
operating
schedules and
occupancy
> User-defined
operating and
utility rate
schedules
Building systems
> HVAC
equipment and
controls
Most
common
applications
> Whole
building
energy
simulation
> Widely used
for office
buildings
Availability
Commercial
33
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
ECOTECT
Strengths
Weaknesses
> Couples an intuitive
3D modelling interface
with extensive solar,
thermal, lighting,
acoustic and cost
analysis functions
> Whole building
energy and
environmental analysis
> Handling of simple
shading models to fullscale city-scapes
> Provision of essential
analysis feedback from
even the simplest
sketch model
> It progressively
guides the user as
more detailed design
information becomes
available
> It includes
visualization of
volumetric and spatial
analysis results,
including imported 3D
CFD data
> Relatively high
complexity level
> It requires
expertise in CAD
design and
simulation
Handling of
climate
conditions
> User-defined
climate-data
time series
Handling of
building systems
operating
schedules and
occupancy
> User-defined
operating
schedules
Building systems
> It interprets
building
equipment
mainly as
thermal loads
> It is focused
mainly on
building thermal
performance
Most
common
applications
> It is mainly
used to
determine
energy
demand
Availability
Commercial
34
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
Strengths
Weaknesses
ENER-WIN
> Hourly whole
building energy
analysis
> HVAC loads
calculations
> Energy
consumption
and demand
> Life cycle cost
analysis
> Graphic sketch
input interface
> Libraries for
windows, wall
materials,
profiles, costs,
lights, etc.
> It uses
simplified
algorithms
> Only nine
HVAC systems
available
> Not
recommended
for HVAC design
analysis
Handling of
climate
conditions
> Hourly
weather data
generator based
on data for 1500
cities
worldwide
Handling of
building systems
operating
schedules and
occupancy
> Limited
interpretation of
building systems
schedules
impact on
electrical energy
use
Building systems
> Equipment
mainly
handled as
thermal loads
Most
common
applications
> Large
commercial
buildings
Availability
Commercial
35
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
Strengths
EnergyPlus > It includes
innovative
simulation
capabilities
including time
steps of less than
an hour
> Simulation
modules that are
integrated with a
heat balancebased zone
simulation
> It facilitates third
party interface
development
> Inclusion of
multizone airflow,
electric power
simulation
including fuel cells
and other
distributed energy
systems
Weaknesses
Handling of
climate
conditions
> Relatively high
level of
complexity
> Energy
simulation
expertise is
required
> Library of predefined weather
of specific
locations
> User-defined
climate-data
time series
Handling of
building systems
operating
schedules and
occupancy
> User-defined
systems'
schedules
Building systems
> The majority of
systems (HVAC,
Air handling
units and
control, DHW,
etc.) of various
building types
can be employed
Most
common
applications
> Whole
building
energy
analysis for
various
building types
Availability
Free
36
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
eQUEST
Strengths
> User friendly
building energy
analysis tool
> It provides
interactive
graphics,
parametric
analysis, and rapid
execution
> Simulation
analysis
throughout the
entire design
process, from the
earliest
conceptual stages
to the final stages
of design
> It offers detailed
analysis
throughout the
construction
documents,
commissioning,
and
postoccupancy
Weaknesses
> IP units
> Groundcoupling and
infiltration/
natural
ventilation
models are
simplified and
limited
Handling of
climate
conditions
> Library of predefined weather
data
in US areas
> User-defined
climate-data
time
series
Handling of
building systems
operating
schedules and
occupancy
> User-defined
systems'
schedules
Building systems
> It contains a
relatively large
database of
HVAC systems
Most
common
applications
> Whole
building
energy
analysis for
various
building types
> It is
particularly
useful to
assess
occupants'
behaviour in
tertiary
buildings
Availability
Free
37
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
ESP-r
Strengths
Weaknesses
> Provision of indepth appraisal of
the factors which
influence the energy
and environmental
performance of
buildings
> It supports earlythrough-detailed
design stage
appraisals
> ESP-r is flexible
and powerful
enough to simulate
many innovative or
leading edge
technologies
including daylight
utilisation, natural
ventilation,
combined heat and
electrical power
generation and
photovoltaic
facades, CFD, multigridding, and control
system
> It is a general
purpose tool and
the extent of the
options and level
of detail slows
the learning
process.
Specialist
features require
knowledge of
the particular
subject.
> It is focused
mainly on
thermal
performance
Handling of
climate
conditions
> User-defined
climate-data
time series
Handling of
building systems
operating
schedules and
occupancy
> Limited
interference
with thermalrelated building
systems
Building systems
> Handled as
thermal loads
mainly
Most
common
applications
> Used to
estimate
energy
demand
> Often used
to study
behaviour
relevant to
daylighting
Availability
Free
38
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
IDA-ICE
Strengths
Weaknesses
> whole year
detailed and
dynamic
multi-zone
simulation
application for
the study of
indoor climate
as well as energy
>- Early Stage
Building
Optimization
> Complete
energy and
design studies
> Accessibility to
incorporate
userdefined models
> Time
consuming
calculations due
to airflow
network
modelling which
requires a large
number of zones
Handling of
climate
conditions
> Library of
climate data
> User-defined
climate-data
time
series
Handling of
building systems
operating
schedules and
occupancy
> User-defined
systems'
schedules
> Adjustable
windows
modelling is also
included
Building systems
> HVAC systems
may be analyzed
> DHW
> Renewable
energy systems
Most
common
applications
> It is widely
used
to assess the
efficiency of
heating
systems
Availability
Commercial
39
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
IESVE
Strengths
Weaknesses
> Provision of indepth suite of
building
performance
analysis tools
> Useful to
identify best
passive options
and renewable
energy measures
> HVAC system
modelling
> Natural
ventilation
modelling
> Daylight and
shading analysis
> CFD analysis
> Energy and
building physics
expertise is
required
> Linux
environment is
not supported
Handling of
climate
conditions
> Library of
climate data
> User-defined
climate-data
time
series
Handling of
building systems
operating
schedules and
occupancy
> Default HVAC
schedules
> User-defined
schedules
Building systems
> pre-defined
HVAC
component
libraries and
Manufacturer
tools
Most
common
applications
> Whole
building
energy
simulation
> Often used
for
renovation
projects
Availability
Commercial
40
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
SUNREL
Strengths
> Well suited for
passive solar
buildings
and includes
algorithms for
Trombe walls,
advanced
glazings,
schedulable
window shading,
active-charge/
passivedischarge
thermal storage,
and natural
ventilation
Weaknesses
> Lack of HVAC
modelling
Handling of
climate
conditions
Handling of
building systems
operating
schedules and
occupancy
> Default hourly
weather data
> User-defined
hourly weather
data
> User-defined
schedules only
for envelope
parameters,
such as windows
Building systems
> No HVAC is
incorporated
Most
common
applications
> Building
thermal
performance
> Shading
analysis
> Insulation
performance
analysis
Availability
Commercial
41
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
TAS
Strengths
> Prediction of
energy
consumption, CO2
emissions, operating
costs and occupant
comfort
> Building thermal
simulation
> Plant and systems
operation modelling
> Offers
comprehensive
capabilities for all
types of energy
modeling
> User-defined
special building
physics models, such
as evaporation and
evapotranspiration
Weaknesses
> Energy and
building physics
expertise is
required
Handling of
climate
conditions
> User-specified
detailed weather
data
> Default
weather files
Handling of
building systems
operating
schedules and
occupancy
Building systems
> User defined
systems and
occupancy
schedules
> Default
schedules
based on
building type
> HVAC systems
with HVAC
manufacturers
databases
> DHW systems
> Daylighting
> Renewable
energy systems
Most
common
applications
> Whole
building
energy
analysis
> Uses to test
planted roofs
and walls
Availability
Commercial
42
Table 2: Important strengths, weaknesses and special features of computational building energy simulation tools.
Special features
Tool
TRNSYS
Strengths
Weaknesses
> Whole building
energy analysis
> HVAC analysis and
sizing, multizone
airflow analyses,
electric power
simulation, solar
design, building
thermal
performance,
analysis of control
schemes
> It interfaces with
various other
simulation packages
such as FLUENT for
airflow impact on
energy
consumption,
GenOpt and
MATLAB for
optimum building
control
> Energy and
building physics
expertise is
required
> Detailed
information for
building thermophysical
properties and
systems is
required
Handling of
climate
conditions
> User-specified
detailed weather
data
> Default
weather files
Handling of
building systems
operating
schedules and
occupancy
Building systems
> User defined
systems and
occupancy
schedules
> Default
schedules
based on
building type
> HVAC systems
with HVAC
manufacturers
databases
> DHW systems
> Daylighting
> Renewable
energy systems
Most
common
applications
> Whole
building
energy
analysis
> Often used
to test PCM
performance
> Coupling
with CFD
tools
Availability
Commercial
43
2.2 Urban Heat Island modelling
The global trend towards urbanization explains the growing interest in the study of urban climate
change due to the Urban Heat Island (UHI) effect and global warming, and its impact on pedestrians’
wind and thermal comfort, perception of air quality and energy demand of buildings. Urban physics is
a well established science discipline which deals with the assessment of the UHI impact on the
aforementioned aspects of the urban environment. The REPUBLIC-MED project acknowledges the
role of urban physics and its substantial contribution in evaluating the implications of UHI in both
building energy demand and daily life of inhabitants (building occupants, workers and pedestrians).
The present section reviews the methods and popular computational tools that can be used to
quantify the physical variables comprising UHI in open spaces, such as wind speed, temperature,
relative humidity, pollutant dispersion, including comfort and air quality indicators of pedestrians.
The Urban Heat Island effect is related to higher urban temperatures in city centres compared to the
surrounding rural or suburban areas64. This situation is mainly caused by anthropogenic heat releases
in the urban environment, i.e. vehicles, power plants, air-conditioners and other heat sources, as well
as by other heat stresses produced by the use of ground or building materials of poor thermal
behaviour, the lack of heat sinks (e.g. water surfaces) and of vegetation65. The adverse effects of UHI
include the deterioration of living environment and increase in energy consumption in buildings,
especially during the summer period. Landsberg (1981)66 states that the UHI phenomenon is the most
obvious climatic manifestation of urbanization.
Possible causes of the UHI were suggested by Oke (1982) 67 and their relative importance was
determined in numerous follow-up studies:
 Trapping of short and long-wave radiation in areas between buildings
 Decreased long-wave radiative heat loss due to reduced sky-view factors
 Increased storage of sensible heat in the construction materials
 Anthropogenic heat released from fuel combustion (domestic heating, vehicles, etc.)
 Reduced potential for evapotranspiration, which implies that energy is converted into
sensible rather than latent heat
 Reduced convective heat removal due to the reduction of wind speed
64
Santamouris et al., Using advanced cool materials in the urban built environment to mitigate heat islands and improve thermal comfort
conditions. Solar Energy 85 (2011) 3085–3102.
65
G.M. Stavrakakis et al., A computational methodology for effective bioclimatic-design applications in the urban environment, Sustainable
Cities and Society 4 (2012) 41-57.
66
H.E. Landsberg, The Urban Climate, Academic Press Inc.,New York, US, 1981.
67
T.R. Oke, The energetic basis of the urban heat island, Quarterly Journal of the Royal Meteorological Society 108 (1982) 1–24.
44
Studies of the UHI usually refer to the heat island intensity, which is the maximum temperature
difference between the city and the surrounding area. The intensity is mainly determined by the
thermal energy balance of the region and is, therefore, subject to diurnal variations and short-term
weather conditions68,69. Santamouris (2001)68 compiled data from a large number of heat island
studies worldwide. Based on this report, heat island intensities for European cities range between
2.50C (London) and 140C (Paris). Especially in warm climates, heat islands can seriously affect the
overall energy consumption of the urban area, as well as comfort and air quality perception of
inhabitants. Indicatively, based on measurements from almost 30 meteorological stations in urban
and suburban areas and on consumption data in Athens, Greece, a doubling of the cooling load of
buildings and a tripling of the peak electricity load for cooling was observed for buildings within dense
urban areas70. Besides affecting the energy demand, increased air temperatures also contributes to
heat stresses. These stresses, in turn, lead to thermal discomfort, while they can contribute to
reduced mental and physical performance as well as to physiological and behavioural changes71. The
present section focuses on the analysis of well-known simulation methods and approaches of urban
physics to quantify the impact of urban design features on the thermal performance of the urban
fabric, which reflects on the manifestation of UHI. There are two major simulation methods often
used to assess UHI72:
 Energy balance models
 Computational Fluid Dynamics (CFD) models
In the following subsections, the background of the simulation methods and a comparative analysis
between them is discussed, while the most popular computational tools of each method are briefly
described in terms of their strengths and weaknesses.
2.2.1 Energy balance models
The energy balance budget for a building complex was first suggested by Oke (1982) 67. This method
uses the law of energy conservation for a given control volume, and considers the atmospheric
phenomena, turbulence fluctuations and velocity field as heat fluxes. These fluxes are generally
defined by analytical or empirical equations.
In the last two decades the energy balance budget concept has been enhanced to the so-called Urban
Canopy Model (UCM), which is derived from the energy balance equation for a control volume which
contains two adjacent buildings. The model considers the energy exchanges between solid surfaces of
68
M. Santamouris, Energy and climate in the urban built environment, James & James Ltd, London, UK, 2001.
P. Moonen et al., Urban physics: Effect of the microclimate on comfort, health and energy demand, Frontiers of Architectural Research 1
(2012) 197-228.
70
M. Santamouris et al. On the impact of urban climate on the energy consumption of buildings, Solar Energy 70 (2001) 201–216.
71
G.W. Evans, Environmental Stress, Cambridge University Press, 1982.
72
P.A. Mirzaei & F. Haghighat, Approaches to study Urban Heat Island- Abilities and limitations, Building and Environment 45 (2010) 21922201.
69
45
the domain and the urban canopy. The UCM approach predicts the ambient temperature and
surfaces temperature of buildings, pavements and streets. However, the airflow is decoupled from
the temperature field, and has to be defined as a separate input into the control volume. For this
purpose, the logarithmic- or the power- law73 is widely used in order to represent airflow in the
domain of interest.
In the UCM approach, all surfaces and control volumes are connected to each other like electrical
nodes. The energy balance equation72 is then applied to each node, and the matrices of temperature
and humidity of the surfaces are formed. By solving these matrices, the temperature and relative
humidity of the domain are emerged. Single layer74 and multi-layer75 schemes are related to the
number of nodes on the building walls, while such models can be also developed in one-three
dimensions. This approach is generally very quick as it only approximates building canopies with
limited nodes. It provides also acceptable accuracy for large-scale energy consumption studies.
The absence of air velocity fields stands for the major weakness of the energy balance models as the
velocity field information is necessary in order to study the effect of the flow pattern (e.g. eddy
circulation, wake region and turbulence), to study formation of the atmospheric phenomena (e.g.
precipitation and stratification), and to determine the sensible and latent heat fluxes. The assumption
of these fluxes, therefore, with empirical correlations does not appropriately represent the
interaction between velocity and temperature fields. Providing database for three dimensional
geometry of building canopies and urban structures in a city is very expensive in terms of time and
computer load. Therefore, the city is usually replaced with homogeneous columns of similar
buildings. The geometry and complexity of buildings are also approximated with limited grids on
ground, roof and walls. This makes the spatial resolution of the energy conservation technique very
weak, especially when it is required to study thermal comfort at the pedestrian level.
2.2.2 Computational fluid dynamics
Unlike the energy balance models in which velocity and temperature fields are separated, CFD
simultaneously solves all the governing equations of airflow within the urban fabric, i.e. conservation
equations of mass, momentum, thermal energy, chemical species and turbulence parameters for
single and multi-phase flow phenomena. As a result, CFD is capable to obtain more accurate
information about the UHI effect within and above building canopies compared to the energy balance
models. Consideration of complex details in addition to complicated atmospheric interactions of a
city nonetheless is computationally and theoretically a challenging problem. The computational
problem is related to the number of the control volumes or required nodes to simulate the airflow
73
G.M. Stavrakakis et al., Evaluation of thermal comfort in indoor environments using Computational Fluid Dynamics (CFD), In: Harris
R.G., Moore D.P. (editors), Indoor Work and Living Environments: Health, Safety and Performance. Nova Science Publishers Inc., 2009, pp.
97-166, ISBN: 978-1-61728-521-9.
74
H. Kusaka et al., A simple single-layer urban canopy model for atmospheric models: comparison with multi-layer and slab models,
Boundary-Layer Meteorology 101 (2001) 329-58.
75
H. Condo et al., Development of multi-layer urban canopy model for the analysis of energy consumption in a big city: structure of the urban
canopy model and its basic performance, Boundary-layer Meteorology 116 (2005) 395-421.
46
within the urban fabric. On the other hand, the theoretical problem is related to the unmatched
temporal and spatial resolution of the physical mechanisms occurring within the cityscape. For
example, atmospheric and canopy-scale turbulence cannot be modelled in the same scale of time and
length. Therefore, CFD simulations are mostly separated into different scales. This means that the
simplification of Navier-Stokes is significantly different due to the scale of the study. Two scales are
generally used in UHI study literature: Meso-scale and Micro-scale (urban-scale).
2.2.2.1 Meso-scale modelling
Meso-scale models are smaller than synoptic-scale and larger than micro-scale systems. The
horizontal resolution of these models is approximately ranged from one to several-hundreds of
kilometres. These models vary vertically with the depth of Planetary Boundary Layer (PBL) between
200m and 2km. This layer exists between the earth surface and geostrophic wind. In meso-scale
modelling, large-scale interactions under the PBL are resolved, including atmospheric stratification
and surface layer treatment. In this approach the Navier-Stokes equations are either based on
hydrostatic or non-hydrostatic hypothesis to include the atmospheric stratification effect. In
hydrostatic models, the equation of motion in the vertical direction is simplified into a balanced
equation between the buoyancy and the pressure terms. On the other hand, in the non-hydrostatic
models, the equation of motion in the vertical direction is expressed with the full Navier-Stokes
equation.
Meteorological schemes mostly use Monin-Obukhov or other similarity schemes to model surface
sublayer76 and building canopies are simulated by means of aerodynamic roughness. This implies that
in meso-scale models the whole urban canopy layer with its complexity details is replaced by a
roughness value. Consequently, information about dependent variables within the canopy is not
available. This simplification helps to understand the processes occurring within the urban surface
layer and above the canopy layer, such as surface drag, shearing stress, wind profiles and turbulence.
The accuracy of a meso-scale model prediction strongly depends on database provided for the LandUse Land Cover (LULC). Detailed information of micro-scale surfaces (e.g. thermal properties,
geometry, radiative characteristics) is rarely available for the entire urban area of interest, and even
in the contrary case, applying these details to meso-scale model is very CPU-intensive. Since the
spatial resolution is in magnitude of few kilometres, it is also necessary to assume a meso-scale zone
as a homogeneous area, and estimate the surface properties with bulk values, e.g. albedo, emissivity
and roughness.
Appropriate assumptions for the PBL is another important issue in meso-scale models. The PBL is
directly influenced by its contact with a planetary surface. Therefore, in this layer many physical
phenomena are taking place which affect velocity, temperature, relative humidity and turbulence
fields. For example, when the positive buoyancy of the surface created by solar irradiance or moisture
76
T. Yamada & S. Bunker, Development of nested grid, second moment turbulence closure model and application to the 1982 ASCOT brush
creek data simulation, Journal of Applied Meteorology 27 (1987) 562-578.
47
condensation is strong, the PBL generates strong turbulence and produces positive buoyancy under
thermal instability. It is also feasible that negative buoyancy opposes turbulence and weakens vertical
mixing. This phenomenon happens typically when the earth’s surface is colder than the prevailing air.
Although many PBL models have been proposed77, the equations are considerably non linear and
influenced by properties of land surface and the free atmosphere’s interactions. Therefore, further
improvements are required in this subject area. In addition, many moisture schemes78,79 and soil
models have been developed for integration with PBL models. The interaction between cumulus and
radiation is also required for meso-scale modelling. It should pointed out that cumulus, soil, radiation
and PBL models are coupled in meso-scale models and development of these interactions, therefore,
is a wide topic of research. For example, the cumulus model provides information for calculation of
radiation absorbed by urban surfaces. Afterwards, the PBL model estimates moisture, temperature
and velocity based on the absorbed radiation. Again, these data are simultaneously used by the
radiation model to estimate upward long and short-wave radiation. Furthermore, the accuracy of
meso-scale models is a function of proper wind and surface temperature boundary condition that is
generally provided by observational techniques80.
2.2.2.2 Micro-scale modelling
Unlike the meso-scale, micro-scale CFD resolves the conservation equation inside the surface layer.
The horizontal spatial quantities are taken as bulk values in the meso-scale model, while the
quantities within the actual geometry are simulated in detail taking into account surface layer
interactions in the micro-scale model. These interactions are generally represented by the MoninObukhov similarity theory to represent the PBL in meso-scale layers. However, it is not feasible to
apply micro-scale modelling for an entire city, with all geometrical details, due to the high
computational cost. Therefore, the common approach is to limit the simulation into a small domain in
magnitude of some blocks of buildings (few hundreds of meters), as did, for example, by Stavrakakis
et al. (2012)65. On the other hand, the treatment of the PBL in micro-scale model is not as
comprehensive as in the meso-scale model, by means that micro-cale modelling does not account for
atmospheric interactions such as vertical mixing or Coriolis effect.
Observational schemes72 can significantly improve the limitations mentioned above. However,
providing boundary conditions in the micro-scale model is even more complicated than meso-scale
model. In micro-scale modelling more measurements are necessary due to high fluctuations of
airflow quantities at the surface layer. Although the assumptions of homogeneous boundary layer81
77
H. Fan & D.J. Sailor, Modelling the impacts of anthropogenic heat on the urban climate of Philadelphia: a comparison of implementations
in two PBL schemes, Atmospheric Environment 39 (2005) 73-84.
78
J. Reisner et al., Explicit forecasting of super cooled liquid water in winter storms using the MM5 meso-scale model, Quarterly Journal of
the Royal Meteorological Society 124 (1998) 1071-107.
79
P. Schultz, An explicit cloud physics parameterization for operational numerical weather prediction, Monthly Weather Review 123 (1995)
3331-43.
80
T.S. Saitoh et al., Modelling and simulation of the Tokyo urban heat island, Atmospheric Environment 30 (1996) 3431-42.
81
P.J. Richards & R.P. Hoxey, Appropriate boundary conditions for computational wind engineering models using the k-" turbulence model,
J Wind Eng Ind Aerod 46&47 (1993) 145–153.
48
and corresponding boundary conditions65 may be adopted, these approximations are physically weak
due to the stochastic nature of flow velocity, and different height and geometry of buildings. Similar
to the meso-scale modelling, the treatment of turbulent closure and radiation significantly affect on
accuracy of the micro-scale model prediction.
As far as turbulence modelling is concerned, many theories have been proposed to model turbulence,
such as the Direct Navier-Stokes (DNS) simulation, Large Eddy Simulation (LES), and Reynolds
Averaged Navier-Stokes (RANS). Although better accuracy can be achieved using LES and DNS, the
application of these schemes is computationally intensive. On the other hand, RANS models (such as
the Standard k-ε model or its modifications82) are widely used for turbulence modelling in UHI studies
as their requirements for computational resources are moderate in comparison to LES and DNS 65,83.
However, it should be mentioned that RANS modelling provides limited representation of physical
phenomena such as the so-called “horse-shoe vortex” around buildings84. This implies that accurate
modelling of turbulence phenomena is still one of the weakest points of RANS modelling.
Additionally, the scale of the study significantly affects the development of RANS as it is related to the
turbulence length-scale which describes the size of the large energy-containing eddies in a turbulent
flow.
Regarding the development of meso-scale turbulence modelling, the effect of buoyancy mostly
created by urban surface layer is as significant as viscous turbulence. In recent years, multi- and twoequation turbulent schemes, e.g. the standard k-ε and k-ε-l models have been proposed85,86.
2.2.3 The role of urban physics in urban energy and environmental studies
The present subsection addresses the role of urban physics in the study of wind comfort, thermal
comfort, pollutant dispersion and energy demand. The main physical aspects of each implication
above as well as the significance of field modelling to assess them are discussed.
2.2.3.1 Urban wind comfort
High-rise buildings can introduce high wind speed at pedestrian level, which can lead to
uncomfortable or even dangerous conditions. Lawson & Penwarden (1975)87 report the death of two
old ladies due to an unfortunate fall caused by high wind speed at the base of a high-rise building.
82
G.M. Stavrakakis et al., Modified closure constants of the Standard k-ε turbulence model for the prediction of wind-induced natural
ventilation, Building Services Engineering Research and Technology 33 (2012) 241-261.
83
N. Fintikakis et al., Bioclimatic design of open public spaces in the historic centre of Tirana, Sustainable Cities and Society 1 (2011) 54-62.
84
B. Kishan et al., A fluid mechanician’s view of wind engineering: Large eddy simulation of flow past a cubic obstacle, Journal of Wind
Engineering and Industrial Aerodynamics 67&68 (1997) 211-224.
85
E. Ferrero et al., Turbulence fields for atmospheric dispersion models in horizontally non-homogeneous conditions, Atmospheric
Environment 37 (2003) 2305-15.
86
T.C. Vu et al., Turbulence closure model for the atmospheric boundary layer inclusing urban canopy, Boundary-layer Meteorology 102
(2002) 459-90.
87
T.V. Lawson & A.D. Penwarden, The effects of wind on people in the vicinity of buildings, 4 th International Conference on Wind Effects
on Buildings and Structures, Heathrow, 1975.
49
Due to such incidences, the last decade, many urban authorities grant permission of new high-rise
buildings only after a wind comfort study (mainly in US), which led to a significant reduction of windrelated negative consequences.
The main cause of high wind speed occurred at pedestrian level is the deviation of wind-stream
direction at elevations towards pedestrian level due to the presence of high-rise buildings69. A simple
sketch that qualitatively illustrates the wind flow around a building is provided in Figure 2. The
attacking wind (streamlines 1 and 2) approaches the windward façade of the building, where it
detaches and part of the flow is directed around the vertical edges (streamlines 2 and 4), the top
horizontal edge (streamline 3), but, remarkably, the major part of the flow is directed to the ground
level (streamline 5) where a persistent vortex is created (streamline 6) that, subsequently wraps
around the vertical edges of the building (streamlines 8) and reattach to the main flow at the ground
level (streamline 9). The typical problematic areas where intense draughts occur are in the standing
vortex at the windward façade front and near the corners of the building. It should be mentioned that
further upstream a stagnant region occurs (streamline 7), since the detachment of the airflow takes
place in this area. At the leeward parts of the building, complex and strongly transient wind-velocity
patterns take place, but these are generally associated with low wind speeds and, thus, they are of
less concern in practical wind-effects studies (streamlines 10-16).
Figure 2: Schematic representation of wind flow pattern around a high-rise building69.
The aforementioned qualitative explanation of airflow around buildings reveals the typical drought
intensity areas expected around buildings. However, critical parameters, such as the flow direction,
other obstacles, heat sources, significantly affect the airflow patterns within building complexes and
further study is required in order to assess wind comfort, or even wind danger, in open spaces. Such
studies can be implemented by on-site measurements, wind tunnel or by field modelling, such as
50
CFD. One of the main advantages of the latter method is that it requires less time and cost for
purchasing equipment and it can be implemented in a desk-analysis manner, i.e. computer
simulations. Despite of its deficiencies, steady RANS modelling with the Standard k-ε turbulence
model (or other two-equation models) has become the most popular approach for pedestrian-level
wind studies. Many field modelling studies on wind impact on pedestrians have been conducted
world-wide demonstrating the use of field models to reveal areas with strong winds and to suggest
wind mitigation measures64,65.
Field models, and especially CFD, have been employed on a few occasions in the past as part of wind
comfort assessment studies88. The use of CFD for studying pedestrian perception of wind conditions is
receiving strong support from several international initiatives that specifically focus on the
establishment of guidelines for such simulations (e.g. Franke et al., 2004 89; Franke et al., 200790).
To remove the large uncertainty in studies of wind comfort (and danger) due to the use of different
sets of statistical data, different terrain-related transformation procedures and different comfort and
danger criteria, a Standard for wind comfort and wind danger (NEN 8100) and a new practice
guideline (NPR 6097) have been developed in the Netherlands91,92. To the best of the authors’
knowledge, this is the first Standard on wind comfort and wind danger world-wide. The Standard and
the Guideline contain a verified transformation model for the terrain-related contribution. The
Standard explicitly allows the user to choose between wind-tunnel modelling and CFD to determine
the design-related contribution, but requires a report specifying details of the employed wind tunnel
or CFD procedure, as a measure to achieve a minimum level of quality assurance. In relation to this
new Standard, the first published demonstration project was conducted by Blocken and Persoon
(2009)93 focused on the simulation of the airflow pattern in the wider urban area of the Amsterdam
Arena Stadium.
2.2.3.2 Urban thermal comfort
Pedestrians’ perception of thermal comfort is strongly related to wind speed, direct and diffuse solar
irradiance, the exchange of long-wave radiation between the person and the environment, as well as
air temperature and relative humidity. When considering urban planning and renovation, the
aforementioned physical parameters in combination with pedestrians’ expected activity, clothing
insulation and main routes, the understanding of the dynamic response of people to varying
environmental conditions is necessary.
88
B. Blocken et al., CFD simulation for pedestrian wind comfort and wind safety in urban areas: general decision framework and case study
for the Eindhoven University campus, Environmental Modelling and Software 30 (2012) 15-34.
89
J. Franke et al., Recommendations on the use of CFD in wind engineering, In: J.P.A.J. van Beeck (Ed.), Proceedings of the International
Conference on Urban Wind Engineering and Building Aerodynamics, COST Action C14, Impact of wind and storm on City Life Built
Environment, Von Karman Institute, Sint-Genesius-Rode, Belgium, 5-7 May, 2004.
90
J. Franke et al., Quality assurance and improvement of micro-scale meteorological models, Hamburg, Germany, 2007.
91
NEN 8100, Wind comfort and wind danger in the built environment, Dutch Standard, 2006.
92
NPR 6097, Application of mean hourly wind speed statistics for the Netherlands, Dutch Practice Guideline, 2006.
93
B. Blocken & J. Persoon, Pedestrian wind comfort around a large football stadium in an urban environment: CFD simulation, val idation
and application of the new Dutch wind nuisance standard, Journal of Wind Engineering and Industrial Aerodynamics 97 (2009) 255-270.
51
Field modelling of airflow in open spaces serves as a key instrument to study and quantify
environmental-variables variation and physical interactions between people and their environment.
The main result of field modelling is the distribution of physical variables such as temperature,
relative humidity, turbulence intensity, etc., as well as of personal parameters, such as activity level
and clothing insulation, throughout the domain of interest. These distributions may then be
elaborated by thermal comfort models towards the quantification of thermal comfort indicators at
the pedestrian level height. The obvious usefulness of this procedure is that field modelling may
provide a spatial resolution of comfort perception throughout the domain, revealing areas of
intensive heat stresses where people feel discomfort. By these means, the situation before a planned
retrofit may be analysed and according to the problematic areas revealed (heat stresses) to decide
and prioritize the interventions.
A crucial element of the analysis of thermal comfort in open spaces is the selection (and integration
to a field model) of appropriate thermal comfort indicators which reflect thermal sensation in
different points of the domain of interest. The most popular thermal comfort indicators for assessing
comfort conditions in open spaces are the following:
 Predicted Mean Vote (PMV) developed by Fanger (1970) 94 on the basis of laboratory-based
comfort investigation mainly for indoor environments, under steady state conditions. PMV is
calculated on the basis of air temperature, relative humidity, mean radiant temperature and
wind speed, for a given level of activity (metabolic rate) and clothing insulation (typical values
of metabolic rates and clothing insulation may be found in the ASHRAE Standard 55-199295).
The PMV model is really useful for assessing the expected thermal comfort in indoor and
outdoor environments; however, it should be pointed out that since it was developed under
steady and indoor conditions, it is more reliable for indoor environments.
 Standard Effective Temperature (SET*) is defined as the air temperature of a reference
environment in which a person has the same mean skin temperature and skin wettedness as
in the actual environment96. The SET* concept was developed to account for relative
humidity impact in warm environments. The SET* approach has been extended particularly
for outdoor spaces to the so-called OUT-SET* index97.
 Based on the SET* index, the PMV has been corrected to account for humidity effects in
warm environments resulting to the PMV(SET*) 98 (or PMV*) which is applicable for both
semi-outdoor and outdoor spaces. Stavrakakis et al. (2010)98 has successfully incorporated
94
P.O. Fanger, Thermal comfort analysis and applications in environmental engineering, McGraw-Hill, New York, 1970.
ASHRAE (1992) Thermal Environmental Conditions for Human Occupancy, Atlanta GA, American Society of Heating, Refrigerating and
Air Conditioning Engineers (ASHRAE Standard 55-1992).
96
R.J. De Dear & J. Spagnolo, Thermal comfort in outdoor and semi-outdoor environments, In: Tochihara Y, Ohnaka T, editors.
Environmental ergonomics – the ergonomics of human comfort, health and performance in the thermal environment, Elsevier Ltd, 2005. p.
269–76.
97
J. Pickup & R.J. de Dear, An outdoor thermal comfort index (OUT_SET*) – Part I - The model and its assumptions. In: ICB - ICUC’ 99,
Sydney, 8–12 November, 1999.
98
G.M. Stavrakakis et al., Development of a computational tool to quantify architectural-design effects on thermal comfort in naturally
ventilated rural houses, Building and Environment 45 (2010) 65-80.
95
52
the index in a CFD model towards the quantification of spatial distribution of this index in
naturally ventilated buildings.
 Physiological Equivalent Temperature (PET)99 is defined as the air temperature of a reference
environment in which the heat budget of the human body is balanced with the same core and
skin temperature as under the complex outdoor conditions of the actual environment.
The incorporation of a thermal comfort model into a field modelling computational platform provides
an integrated computational tool. This tool serves for a calculator of microclimate variables
(temperature, wind speed, relative humidity, mean radiant temperature, turbulence intensity) as a
result of design features of an open space, and of thermal comfort indicators emerged by elaborating
the results of microclimate simulation. There are many studies adopting this modelling approach in
scientific literature. For example, Stavrakakis et al. (2012)65 developed a home-made code that
quantifies the effect of special design features such as evaporation from wet surfaces and
evapotranspiration from trees and planted surfaces as well as the PMV indicator, and integrated it
into a commercial CFD platform Fluent v.6.3.26. They used this integrated model to suggest UHI
mitigation measures in a square located in the warmest climate zone of Greece and several smart
bioclimatic design and technological solutions were concluded. For the same purposes, simpler
methods may be adopted such as the SOLWEIG100 model or the Rayman101 model, both being variants
of the energy balance model in the basis of radiation modelling of the outdoor environment.
2.2.3.3 Urban energy demand
Since 2007, for the first time in human history, more than half of the world’s population lives in
cities102. Moreover, the fraction of people living in urban areas is expected to grow up to almost 70%
by 205069, and the energy consumption in cities is likely to follow that trend.
Ouedraogo et al. (2012)54 estimated the impact of a climate change scenario reported in the Special
Report on Emission Scenarios (SRES)103 on building energy consumption for air-conditioning. They
stated that even when the B2 scenario of the SRES is adopted, i.e. continuous population growth and
local, environmentally sustainable economies that have less emphasis on growth and globalization,
mean global temperature will increase by 20C by 2050. According to their predictions, this climatechange scenario implies that annual building energy consumption will experience an increase by 56%
and 99% within the periods 2030-2049 and 2060-2079, respectively.
99
P. Hoppe, The physiological equivalent temperature - a universal index for the biometeorological assessment of the thermal environment,
International Journal of Biometeorology 43 (1999) 71–75.
100
F. Lindberg et al., SOLWEIG 1.0 - modelling spatial variations of 3D radiant fluxes and mean radiant temperature in complex urban
settings, International Journal of Biometeorology 52 (2008) 697–713.
101
A. Matzarakis et al., Modelling radiant flux in simple and complex environments: basics of the Rayman model, International Journal of
Biometeorology 54 (2010) 131–139.
102
R. Madlener & Y. Sunak, Impacts of urbanisation on urban structures and energy demand: What can we learn for urban energy planning
and urbanisation management?, Sustainable Cities and Society 1 (2011) 45-53.
103
N. Nakicenovic et al., Emissions scenarios, a special report of working group III of the intergovernmental panel on climate change,
Cambridge University Press, 2000.
53
This rapid urbanization has led to urban sprawl in many EU countries, which manifests serious
implications in daily life and health as trends like the above will inevitably create problems like
resource depletion, pollution and energy consumption. Consequently, during the next decades, urban
planners and other stakeholders (energy experts, engineers and architects) will have to face major
issues in terms of building energy analysis. Minimizing the energy demand of buildings in urban areas
has a great energy-saving potential.
To that direction, it becomes obvious that the study of the UHI effect on building energy consumption
is important and challenging. This is because complex phenomena comprising building and urban
physics and their interactions should be adequately assessed in order to conclude secure conclusions
about renovation measures suggestions for building energy upgrading. When indoor-outdoor
interactions are taken into account, an increased accuracy of energy-related indicators is expected,
which, in turn, ensures the selection of least-cost renovation measures avoiding over-sizing without
compromising desirable values of energy consumption. The aforementioned statement is strongly
supported by numerous studies104,105 that highlight, for example, the improved accuracy of the
estimated energy consumption when using climate data of the local microclimate rather than using
data from the wider climate zone (which is the common method in Europe).
The consideration of local microclimate (in the vicinity of the building), i.e. UHI effect, is really
important in building energy assessments for the following reasons:
 Unlike an isolated building, a building in the urban fabric is exposed to increased maximum
ambient temperatures due to the UHI effect
 Low wind-speeds in dense urban environments significantly affect convective heat transfer
near building exterior walls
 Buildings in dense urban areas experience modified radiation balance (than stand-alone
buildings) due to interactions with neighbouring buildings
 Reduced energy losses during night hours are expected due to reduced sky view factors
occurring in the urban fabric
The aforementioned factors strongly influence energy demand, thus when conducting building
energy upgrading studies, these factors should be taken into account in order to predict as accurately
as possible the energy indicators. For this reason, a coupling of field/nodal models has been proposed
in numerous studies104. The main purpose of such studies is to capture the physical indoor/outdoor
interactions (heat transfer mechanisms mainly) through the building envelope, and predict energy
indicators as a result of the influence of actual surrounding microclimate of the building. The
REPUBLIC-MED project acknowledges the importance of this and for this reason, further discussion
104
J. Bouyer et al., Microclimatic coupling as a solution to improve building energy simulation in an urban context, Energy and Buildings 43
(2011) 1549-1559.
105
E. Bozonnet, R. Belarbi, F. Allard, Thermal behaviour of buildings: modelling the impact of urban heat island, Journal of Harbin Institute
of Technology 14 (2007) 19–22.
54
on methods to assess the impact of UHI on indoor energy consumption, associated with reports from
past studies, is provided in 2.2.6.
2.2.3.4 Urban pollutant dispersion
Air pollution in the urban environment is caused mainly by the transport sector, which is responsible
for a substantial share of emissions, industrial units, domestic heating and cooling systems as well as
by toxic agents releases (e.g. aerosols) to the atmosphere. This situation leads to adverse effects in
climate, environment and human health. After being emitted from the above sources, pollutants are
dispersed within the urban fabric over a wide range of horizontal length scales. Pollutants’ dispersion
is governed by both wind and buoyancy forces. Most commonly, pollution sources are heat sources
as well, which serve for the generation of buoyant forces near the source. Depending on wind speed
and turbulence intensity prevailing in the area of the source, buoyant forces lead to the elevation of
pollutants (formulation of pollutants’ plumes). These forces are eventually degrade, and the
dispersion is then governed by inertia (wind) forces. Apart from this physical transport process,
chemical processes also occur, e.g. many emitted chemicals by vehicle exhausts are reactive with
other substances leading to the formulation of additional products. For instance traffic-induced
pollutants such as NOx and volatile organic compounds (VOCs) are the main precursors of
tropospheric ozone (responsible for the green house effect).
In case of urban planning and renovation studies, the understanding of the main mechanisms of
pollutants’ dispersion is extremely important in order to realize the impact of pollutant sources on
both indoor and outdoor air quality. To that direction numerous studies exist in scientific literature
that employ field models in order to quantify pollutants’ concentrations within the urban fabric. The
CFD method is widely used to predict pollution plumes and concentrations towards the suggestion of
pollution reduction measures. For instance, Amorim et al. (2013) 106 demonstrate the effect of trees
orientation in two distinct urban areas in Portugal over CO concentration at the pedestrian level
height by applying a CFD model.
Table 3: Capabilities of UHI assessment approaches
Approach
UCM
CFD
Meso-scale
Governing equations
- Energy balance
equation
- Momentum
equations (NavierStokes) including
Micro-scale
- Momentum
equations (Navier-
106
J.H. Amorim, CFD modelling of the aerodynamic effect of trees on urban air pollution dispersion, Science of the Total Environment
461&462 (2013) 541-551.
55
- Assumption velocity
equation within the
urban canopy
- Heat conduction
equation on solid
surfaces
Coriolis term with
hydrostatic or nonhydrostatic
assumption
- Monin-Obukhov for
ground surface
- Heat conduction
equation for soil
Major limitations
- Decoupled velocity
field from
temperature and
moisture
Stokes)
- Monin-Obukhov for
surfaces of the urban
structures, e.g. wall,
ground.
- Heat conduction
equation for surface
- Assumption of the
urban canopy layer as
roughness
- Planetary Boundary
Layer effects are
ignored
- Representation of
city-scape using
arrays of similar
buildings
- Difficult to provide
Land-use Land-cover
database (userdefined functions are
required)
- Difficult to create
database for canopy
details (user-defined
functions are
commonly required)
- Limited resolution
of building
geometries
- Accuracy is tested
with field
measurements
- Reliable boundary
conditions are
required
- Applied for steadystate simulations
mainly
- Turbulence
modelling is required
- Turbulence
modelling is required
- Empirical
assumptions for
convective latent and
sensible heat
Maximum size of
city-scape domain
Whole City
Whole City
Building block
Spatial resolution for
grid meshing
1-10 m
1-10 km
0.2-10 m
Temporal resolution
(time-step)
Hour
Minute
Second
56
Computational cost
Medium
High
Very high (depending
on the turbulence
model applied and
grid size)
2.2.4 Comparative analysis of UHI modelling methods
Table 3 contrasts the capabilities of UHI study methods by means of the governing equations,
limitations, domain-size restrictions, spatial and temporal resolution, and computational cost. It
becomes obvious that the meso-scale method is practical when urban surface details are not
important, i.e. urban-scale energy conservation, pollutant dispersion and thermal comfort are not
adequately assessed by this method. On the contrary, for cases that such information is required,
which means that physical phenomena within the urban canopy are of interest, micro-scale CFD and
UCM methods are more useful. It should be pointed out, however, that when CFD models are applied
real time and real size simulations, i.e. small time steps and detailed geometries, may be prohibitive
due to extremely high computational costs for simulations of whole city-scapes. This implies that
major assumptions should be adopted in order to produce results for practical engineering purposes.
The main simulation differences between micro- and meso-scale modelling are illustrated in Fig. 3. It
is shown that meso-scale modelling is used for a macroscopic view of the UHI effect, i.e. urban heatreleases effects to the PBL, and simulated flow-field results for the layer far above building heights
are provided (200m-2000m). On the contrary, micro-scale modelling analyses the physical
phenomena within the urban canopy layer in detail, thus it provides flow-field results within the
urban canopy (1-200m). Consequently, micro-scale modelling facilitates the formulation of
conclusions at the pedestrian level height, i.e. perception of thermal comfort and air quality.
The most common assumptions followed when micro-scale CFD models are applied for UHI
assessments are:
 Reduction of the computational domain near the areas of interest, i.e. the rest of the actual
city is represented by roughness equations only (without detailing building geometries)
 Geometry simplifications in order to avoid high spatial resolution
 Assume homogeneous boundary layer ignoring the interactions with PBL (200m height and
above)
 Application of unstructured grids (tetrahedral) in order to avoid dense grid propagation along
Cartesian axis of the domain
57
Figure 3: Simulated phenomena using Meso-scale and Micro-scale CFD models.
Although these assumptions may cause deviations of predictions in comparison with measurements
(if available) it has been extensively demonstrated in simulated-measured data comparative studies
that the produced deviations are considered acceptable at least for practical engineering
purposes82,107.
2.2.5 UHI simulation tools
This section summarizes research-based and commercial or commercially available simulation tools
of each method discussed above. It is true that today’s scientific literature contains a plethora of field
modelling tools, which are mainly products of mathematical interpretation of the physical
phenomena encountered in the urban environment. Since the REPUBLIC-MED project focuses in the
physical analysis within the urban canopy layer, meso-scale models are beyond the scope of this
report, and the present section describes energy balance models (UCM mainly) and micro-scale CFD
tools only. The most popular tools used world-wide (but there are many more) are the following:
 Energy balance modelling tools
107
G.M. Stavrakakis et al., Natural cross-ventilation in buildings: Building-scale experiments, numerical simulation and thermal comfort
evaluation, Energy and Buildings 40 (2008) 1666-1681.
58
o
UHSM
o
TEB
o
SOLWEIG
o
Rayman
 CFD tools
o
ENVI-met
o
ANSYS-Fluent
o
ANSYS-CFX
o
Phoenics
A summary of strengths and weaknesses of simulation tools is provided in Table 4.
2.2.5.1 Energy balance modelling tools
2.2.5.1.1 Urban heat storage model (UHSM)
The Urban Heat Storage Model (UHSM) is based on the Oke’s urban energy balance equation 67 and it
was developed by Bonacquisti et al. (2006)108. The tool is based on four energy balance equations at
the ground level and at building level, namely:
 Energy balance equation at building surfaces
 Energy balance equation at the ground level
 Sensible heat balance equation
 Latent heat balance equation
The tool involves three simulation sections, i.e. atmospheric layer (maximum height above building
heights), building and ground levels. The aforementioned equations formulate a system of linearized
algebraic equations to relate four major unknown variables, i.e. building surface temperature, ground
surface temperature, air temperature and relative humidity. Ground and building aerodynamic
roughness is evaluated as function of drag coefficients of soil and of wind speed in the canopy air
space. The decrease of wind speed within the urban canopy was evaluated as a function of buildings’
density, drag coefficients and wind speeds within the atmospheric layer section. Anthropogenic heat
108
V. Bonacquisti et al., A canopy layer model and its application to Rome, Science of the Total Environment 364 (2006) 1-13.
59
is also taken into account using expressions representing heat releases by buildings (produced mainly
by electricity and fuel consumption), by transportation (vehicles exhausts) and by human metabolic
rates. The equations are spatially discretized in the domain (sub-domains) and based on the heat
storage within the urban canopy, an iterative solution procedure is followed towards the calculation
of the unknown variables in each sub-domain.
The main data used as inputs in the model are the thermal and radiative characteristics of urban
surfaces as well as atmospheric parameters. The main output of the tool is the spatial distribution (in
hourly basis) ground and building surface temperature, air temperature and relative humidity, the
mean surface temperature and mean temperature at the pedestrian level height. The tool was
applied by Bonacquisti et al. (2006)108 in case of Rome, Italy, and air temperature was used as
validation parameter, i.e. it was compared with in-situ temperature observations. Using this tool, the
same authors concluded UHI intensities (temperature increase compared to rural areas) of 20C and
50C, for winter and summer, respectively.
2.2.5.1.2 Town energy budget (TEB)
The Town Energy Budget (TEB) tool was developed in Centre National de Recherches
Météorologiques, Toulouse, France, and it was presented by Masson (2000) 109. The TEB tool is built
following the canyon approach, generalized in order to represent large horizontal scales. Due to the
complex shape of the city-scape, the urban energy budget is split into different parts, thus three
surface energy budgets are considered, i.e. for roofs, walls and roads.
The tool aims to simulate turbulent fluxes into the atmosphere at the surface of the meso-scale
atmospheric model covered by buildings, roads or any artificial material. Heat fluxes are computed
for each land type by the appropriate scheme, and then they are averaged in the atmospheric model
grid mesh, with respect to the proportion occupied by each type. The fluxes calculated are: Latent
and sensible heat fluxes, upward radiative fluxes and component momentum fluxes.
City-scape geometry is represented by buildings that have the same dimensions, with the roof level at
the surface level of the atmospheric model. Buildings are located along identical roads, the length of
which is considered far greater than their width. Finally, any road orientation is possible, all existing
with the same probability, and this hypothesis allows the computation of averaged imposition
parameters for road and wall surfaces.
In order to treat the conduction fluxes through solid surfaces, the TEB tool discretizes each surface
type into several layers. The equations applied to represent temperature evolution in these layers are
based on energy budget considerations and several prognostic equations for the surface layers of
roofs, walls and roads are emerged. The set of equations describing heat transfer mechanisms and
109
V. Masson, A physically-based scheme for the urban energy budget in atmospheric models, Boundary-layer meteorology 94 (2000) 357397.
60
turbulent fluxes is similar to that of the UHSM tool. The main difference is that the surface layer is
represented by the Monin-Obukhov equations.
2.2.5.1.3 SOLWEIG
SOLWEIG v.1.0 was developed in the Earth Sciences Centre in Göteborg University, Sweden and it is
extensively described by Lindberg et al. (2008)100. This tool is in fact a variant of the urban energy
balance method focused on radiation modelling within the urban canopy. The model simulates spatial
variations of 3D radiation fluxes and the mean radiant temperature (T mrt). The latter is one of the
most important meteorological factors governing the human energy balance in outdoor spaces
mainly, which is represented by the sum of all radiant fluxes (both direct and reflected) that the
human body is exposed to. Mean radiant temperature is derived by modelling short- and long-wave
radiation fluxes in six directions, i.e. upward, downward and from the four cardinal points (horizon)
taking into account angular factors.
The model requires a limited number of inputs, such as direct, diffuse and global shortwave radiation,
air temperature, relative humidity, urban geometry and geographical information (latitude, longitude
and elevation). The output of the model includes radiant fluxes and Tmrt distribution.
The framework theory based on which the mean radiant temperature is calculated is that introduced
by Hoppe (1992)110 in which radiation fluxes in all six directions are considered. As an energy balance
model it presents the general shortcomings of the energy balance models, e.g. it disregards the
velocity pattern in the domain of interest as well as its fluctuations (turbulence). Another significant
shortcoming is that SOLWEIG does not account for evapotranspiration from vegetation. Lindberg et
al. (2008) demonstrated its usefulness by performing mean radiant temperature simulations in an
urban area of Goteborg and validated numerical results through comparisons with field
measurements.
2.2.5.1.4 Rayman
A similar tool as SOLWEIG is the Rayman111 software, which was developed in the Meteorological
Institute of Albert-Ludwigs-University of Freiburg. The capabilities of the tool are described by
Matzarakis et al. (2010)101. Like SOLWEIG, it is a variant of energy balance models, and it is used
mainly to compute radiant heat fluxes from the human body. The inputs the user has to provide are
the following: temporal data (date and hour); Geographical data (longitude, latitude and elevation);
meteorological data (temperature, relative humidity and cloud covering); personal parameters
(clothing and activity level); Geological morphology; urban design features (buildings, trees).
110
111
P. Höppe, A new procedure to determine the mean radiant temperature outdoors, Wetter Leben 44 (1992) 147–151.
http://www.urbanclimate.net/rayman/index.htm
61
The results obtained by the model include, among others, the following: Distribution of mean radiant
temperature, radiation fluxes and thermal comfort indicators (PMV, SET* and PET). In contrast to
SOLWEIG it computes more thermal comfort indicators and it possesses a more user-friendly
environment. However, it should be mentioned that Rayman disregards special physical effects, such
as evapotranspiration, and it treats trees as simple obstacles to radiation fluxes. Wind effects and
turbulence are also ignored.
2.2.5.2 CFD tools
2.2.5.2.1 ENVI-met
ENVI-met112 is a three-dimensional non hydrostatic model for simulating microclimate, especially
within the urban canyon, taking into account the physical interactions among solid surfaces (e.g.
ground and building surfaces), vegetation and air. It is based on the theoretical background of
Computational Fluid Dynamics, and it makes use of advanced numerical algorithms for solving the
airflow governing equations, i.e. conservation of mass, momentum, thermal energy, chemical-species
concentration and turbulence parameters, as well as particle dispersion.
The main input of the model includes properties of the incoming wind of the urban domain (wind
speed, direction, temperature, relative humidity), simplified geometry of the urban domain (since
coarse structured grids are only allowed, forcing the user to simplify the urban site geometry),
thermo-physical properties of ground and building materials and of vegetation, personal parameters
of pedestrians (such as metabolic rates and clothing insulation). The ENVI-met system is then
executed and an iterative solution procedure takes place towards the production of the following
output: Distribution of temperature, relative humidity, pollutant concentration, turbulence
parameters, wind speed and thermal comfort indicators (e.g. mean radiant temperature and PMV
modified for outdoor conditions), at different heights throughout the urban area of interest.
The background of the ENVI-met system includes sub-models solving for the following physical
mechanisms:
 Long and short wave radiation fluxes, accounting for shading
 Radiation reflection from building facades, ground materials and vegetation
 Evapotranspiration and sensible heat fluxes from vegetation
 Heat and water transfer within soil mass
112
http://www.envi-met.com/
62
 Body-skin/airflow interactions (e.g. heat transfer, wettedness effect) towards the
calculation of thermal comfort indicators
ENVI-met is a useful micro-scale model for the prediction of UHI effects within the urban canopy with
acceptable accuracy for relatively simple geometries. In case of complex geometries, radical
simplifications may be required (such as building merging) in order to comply with grid-mesh
restrictions. In addition, mesh possibilities are limited to structured (and most of the times uniform)
grids with large grid-cells (typical spatial resolution: 0.5-10m), hence the effect of viscous sublayers
(near solid surfaces) may be seriously underestimated. Another drawback is that only the Standard kε model is available for turbulence modelling. In computational terms, ENVI-met in its downloadable
form does not envisage parallel processing, which implies above average computational costs.
Wania et al. (2012)113 used the ENVI-met system to study the influence of different vertical and
horizontal density of street vegetation on particle dispersion. It was demonstrated that vegetation
reduces wind speed causing inhibition of canyon ventilation and, therefore, an increase in particle
concentration. Vegetation was also found to reduce wind speed at crown-height and to disrupt the
flow field in close vicinity of the canopy. Szucs (2013)114 highlighted that comfortable and healthy
public open spaces encourage people to spend more time outdoors, socialize, exercise and
participate in re-creational events. In this framework, Szucs (2013) ENVI-met to examine whether
climatic characteristics in Dublin facilitate long-term outdoor activities during summer, and
investigate the extent to which urban planning and the resulting urban morphology of the built
environment influences the microclimate created by means of the wind profile. It was confirmed that
areas of limited long-term outdoor activities subject to high wind speeds, often at the windward
sections and around corners of buildings (see fig. 2).
2.2.5.2.2 ANSYS-Fluent
Ansys Fluent115 is a powerful CFD platform which provides comprehensive modelling capabilities for a
wide range of incompressible and compressible, laminar and turbulent fluid flow problems, under
steady or transient conditions. In the software a broad range of mathematical models for transport
phenomena (like heat transfer and chemical reactions) is combined with the ability to model complex
geometries.
Examples of ANSYS Fluent applications include laminar non-Newtonian flows in process equipment,
conjugate heat transfer in turbomachinery, pulverized coal combustion in utility boilers, external
aerodynamics in the car industry and of building complexes, etc. Among a wide variety of
applications, the platform has been widely used for assessing microclimate conditions in open spaces.
In such cases Fluent has been frequently used to simulate turbulent airflow within urban canopies. To
113
A. Wannia et al., Analysing the influence of different street vegetation on traffic-induced particle dispersion using microscale simulations,
Journal of Environmental Management 94 (2012) 91-101.
114
A. Szucs, Wind comfort in a public urban space-Case study within Dublin Docklands, Frontiers of Architectural Research 2 (2013) 50-66.
115
www.ansys.com
63
permit modelling of fluid flow and related transport phenomena in complex geometries, such porous
media (vegetation), various useful features are provided such as porosity functions and others.
Fluent solves for the majority of physical phenomena encountered in urban systems. In addition to
those simulated by ENVI-met, it includes:
 A wide variety of turbulence models (RANS, DNS and LES) providing the user the opportunity
to choose (according to the available computational resources and expertise) among different
turbulence models aiming to capture the desirable spectrum of turbulent length-scales.
 A wide variety of two-phase flow models to capture particles dispersion.
 A wide variety of radiation models to simulate short and long wave radiation
 A pluralism of grid-meshing options including structured and unstructured grids to build grids
with the minimum computational cost ensuring adequate resolution of results
 Access to input user-defined functions
In general, ANSYS Fluent is the one of the most complete platforms existing in the CFD industry
including well-known and the latest developments of fluid-flow related models. In terms of
computational requirements, Fluent envisages solutions using multiple parallel processors, thus
reduces computational costs. The latter, however, is a matter of the user’s desires of resolution level,
i.e. if a large urban area with great level of geometrical detail is considered computational cost can be
very high, as in the most micro-scale CFD tools.
The main limitation of the platform is that since it is not targeted for specific problems it requires
relatively high expertise on fluid flow and transport phenomena, for the user to formulate a specific
problem. In this sense, the software does not include evapotranspiration and thermal comfort
models, which means that for microclimate modelling the user should provide him/herself the
models via user-defined functions. Nonetheless, it can be easily used to produce the results of
parameters required to compute thermal comfort indicators (wind speed, relative humidity,
temperature, turbulence intensity) externally.
Numerous CFD studies of the UHI by using Fluent exist in the scientific literature. For example,
Stavrakakis et al. (2012)65 used Fluent for the assessment of thermal and wind comfort of pedestrians
in an urban area in Crete, Greece. Special physical models, such as evaporation from water surfaces
and evapotranspiration from vegetation as well as thermal comfort indicators were incorporated in
the CFD platform towards the formulation of a holistic model that solves for UHI effect on
pedestrians’ perception of thermal comfort. The micro-scale model developed was then used to
assess the pre-renovation situation and to indicate the optimum interventions including vegetation,
64
shading devices, cool materials, in proper locations of the urban domain. Saneinejad et al. (2012)116
studied the evaporative cooling effect on air temperature and thermal comfort within urban street
canyons. They took advantage of Fluent capability to incorporate user-defined physical models and
they developed a coupled CFD model which solves for vapour and heat transfer in the air, heat and
moisture transfer within the porous building walls and radiative heat exchange between building
walls. The effect of evaporation of building surfaces on temperature was adequately quantified and a
substantial impact of this phenomenon on pedestrian thermal comfort was shown.
2.2.5.2.3 ANSYS-CFX
CFX117 is a general purpose CFD tool which possesses the same capabilities as the ANSYS-Fluent
software reported above, at least for airflows within urban canopies. The main differences are
focused on mesh-generation algorithms, solution algorithm as well as differences in functionality and
operability of available GUIs related to user’s actions during pre- and post- processing.
By means of spatial discretization, CFX is cell-vertex while Fluent is Cell-centered. CFX assembles
control volumes around the element vertices, resulting in polyhedral control volumes and hence
there are fewer nodes than cells with a tetrahedral mesh. While this results in fewer control volumes,
there are far more integration points so the resolution of gradients is more accurate per control
volume. Concerning the comparison between the results obtained by CFX and Fluent they present
similar accuracy, however, Fluent has presented a slightly better accuracy for incompressible flows,
although it requires more computational time to converge. This happens due to the fewer
computational nodes in CFX grids in comparison to Fluent grids.
During the solution procedure, CFX presents better robustness especially for steady-state problems,
while Fluent is a bit more unstable. This implies that the user should be alert of the solution course
and proceed to appropriate tuning when necessary, e.g. when residuals’ oscillations occur (“Babysitting” of the solution). Fluent has a more functional pre-processor and thus it requires fewer actions
by the user to prepare the grid and work on available GUIs; hence less model preparation time is
required before simulation.
Priyadarsini et al. (2008)118 used CFX to investigate the UHI effect on temperature rising in the urban
canopy in Singapore. They determined the key factors causing the phenomenon and investigated the
possibilities of improving heat extraction rate by optimizing airflow in selected hot spots. The main
parameters put to the test were building geometry, façade materials and the location of airconditioning condensers and their combined effect on the outdoor air temperature. Although a
116
S. Saneinejad et al., Coupled CFD, radiation and porous media transport model for evaluating evaporative cooling in an urban
environment, Journal of Wind Engineering and Industrial Aerodynamics 104-106 (2012) 455-463.
117
www.ansys.com
118
R. Priyadarsini et al., Microclimatic modelling of the urban thermal environment of Singapore to mitigate urban heat island, Solar Energy
82 (2008) 727-745.
65
simple model was used (evapotranspiration from vegetation was ignored) good agreement between
the computed and the measured results was obtained.
2.2.5.2.4 Phoenics
Phoenics119 is a general purpose CFD platform, which at least for airflows within the urban canopy,
provides similar modelling features and capabilities as CFX and Fluent. As the other CFD programs,
Phoenics can solve for most important conservation equations of mass, momentum, heat, chemical
species and turbulent parameters, towards the provision of results of microclimate parameters such
as relative humidity, wind speed, turbulence intensity and temperature. Similarly to the other CFD
platforms provides access to the user to incorporate special physical models, such as
evapotranspiration from vegetation. A substantial advantage of Phoenics over the other CFD tools is
that it provides access to the source Fortran-based code rather than only offering the opportunity to
incorporate user-defined models.
Like previous tools, it possesses a wide variety of models to simulate turbulence, heat and radiation
transfer and due to its wide validation it can be confidently used to study microclimate in urban
areas. Since it is not just a microclimate-oriented tool, as in the previous tools, expertise above than
average on computing and transport phenomena is required in order to develop a reliable
microclimate model. The major difference is that it does not implement tetrahedral grids, and either
a Body-Fitted or a hexahedral-unstructured grid option is available for complex geometries. Finally,
computational time is usually higher than that using Fluent and CFX, although it provides higher
accuracy for especially within areas of strong buoyancy forces.
Fintikakis et al. (2011)83 used Phoenics to study the urban microclimatic conditions in the historic
centre of Tirana. They developed a microclimate model and incorporated it in the CFD platform
towards the estimation of pedestrian thermal comfort in order to decide the best retrofitting
measures (e.g. trees kind and orientation, high albedo ground materials, earth-to-air heat
exchangers) that ensure the best comfort conditions in strategic locations of the urban domain.
Although a simple model was developed (evapotranspiration and radiation were neglected in the
mathematical model and they were imposed as temperature boundary conditions taken from field
measurements, instead) it provided adequate results at least for practical purposes.
119
http://www.cham.co.uk/
66
Table 4: Important strengths, weaknesses and special features of computational urban microclimate simulation tools.
Special modelling features
Tool
UHSM
Method
UCM
Strengths
> Solution of
heat transfer
equations at
representative
heights
(ground,
building,
atmosphere)
>
Anthropogenic
heat
> Spatial
discretization
of equations
> Distribution
of temperature
and relative
humidity
> Hourly
Weaknesses
> No thermal
comfort
indicators are
incorporated
> Very
simplified
geometry
Evaporation and
evapotranspiration
User –defined
models only
Accuracy
CPU time
Availability
Radiation
Short and
long wave
radiation
models are
included
Satisfying for
weak winds
only
Low
Researchbased
> Wind-speed
decoupled
from heat
transfer
equations
> Simple
roughness
equation for
wind speed
> Turbulence is
dealt with
simple drag
67
Table 4: Important strengths, weaknesses and special features of computational urban microclimate simulation tools.
Special modelling features
Tool
Method
Strengths
temperature
results
Weaknesses
Evaporation and
evapotranspiration
Accuracy
CPU time
Availability
Radiation
equation
> Above
average urban
physics
expertise is
required
> Lack of
documentation
and tutorials
TEB
UCM
> Solution of
heat budget at
three surfaces
(ground, walls
and roofs)
> Turbulent
fluxes are
simulated in
the
PBL/Canopy
> No thermal
comfort
indicators are
incorporated
> Simplified
geometry
User-defined
models only
Short and
long wave
radiation
models are
included
Satifying for
weak winds
only
Medium
Researchbased
> Wind speed
decoupled
from heat
transfer
68
Table 4: Important strengths, weaknesses and special features of computational urban microclimate simulation tools.
Special modelling features
Tool
Method
Strengths
layer interface
equations
> Roads of any
orientation
may be placed
> Above
average urban
physics
expertise is
required
> Conduction
fluxes through
solid surfaces
> MoninObukhov
conditions for
the surface
layer
SOLWEIG UCM
Weaknesses
> Modelling of
3D radiation
fluxes
> Relatively
accurate
geometry
> Solves for
Evaporation and
evapotranspiration
Accuracy
CPU time
Availability
Radiation
> Lack of
documentation
and tutorials
> Velocity
pattern
decoupled
from heat
transfer
> By-default
models for
Evaporation
> Evapotranspiration is ignored
Short and
long wave
radiation
models are
included
Satifying for
weak winds
only
Medium
Researchbased
> Turbulence is
not modeled
69
Table 4: Important strengths, weaknesses and special features of computational urban microclimate simulation tools.
Special modelling features
Tool
Method
Strengths
mean radiant
temperature
(thermal
comfort)
Weaknesses
Evaporation and
evapotranspiration
Accuracy
CPU time
Availability
Radiation
> Limited
documentation
and tutorials
> Average
urban physics
expertise is
required
Rayman
UCM
> Modelling of
3D radiation
fluxes
> Relatively
accurate
geometry
> Solves for
radiant heat
fluxes from
solid surfaces
and from
> Velocity
pattern
decoupled
from heat
transfer
> Evaporation is
included
> Evapotranspiration is ignored
Short and
long wave
radiation
models are
included
Satifying for
weak winds
only
Medium
Free
> Turbulence is
not modeled
> Limited
documentation
and tutorials
70
Table 4: Important strengths, weaknesses and special features of computational urban microclimate simulation tools.
Special modelling features
Tool
Method
Strengths
Weaknesses
Evaporation and
evapotranspiration
Accuracy
CPU time
Availability
Radiation
human body
> Solves for
thermal
comfort
indicators
(PET, SET* and
PMV)
> User friendly
> Average
expertise in
urban physics
is required
ENVImet
Microscale
CFD
> 3D
simulation of
airflow pattern
> Solution for
most
important
conservation
> Coarse grids
> No parallel
processing
potential is
available
> By-default
models for
evaporation and
evapotranspiration
Short and
long wave
radiation
models are
included
Satisfying for
both weak
and strong
winds
Very high
Free
> Only one
turbulence
71
Table 4: Important strengths, weaknesses and special features of computational urban microclimate simulation tools.
Special modelling features
Tool
Method
Strengths
equations
> Calculation
of thermal
comfort
indicators
Weaknesses
Evaporation and
evapotranspiration
Accuracy
CPU time
Availability
Radiation
model is
included
> Moderate
documentation
and tutorials
> Relatively
accurate
geometry
> Turbulence
modelling
> Average
expertise in
urban physics
is required
ANSYSFluent
Microscale
CFD
> General
purpose CFD
platform
> Many
options of
> Since it is a
general CFD
platform, the
user has to
develop and
> User-defined
models for
evaporation and
evapotranspiration
Short and
long wave
radiation
models are
included
Satisfying for
both weak
and strong
winds
High
Commercial
72
Table 4: Important strengths, weaknesses and special features of computational urban microclimate simulation tools.
Special modelling features
Tool
Method
Strengths
turbulence
models and
radiation
models
> Flexibility
and easiness of
grid generation
Weaknesses
Evaporation and
evapotranspiration
Accuracy
CPU time
Availability
Radiation
incorporate
user-defined
models, thus it
requires high
expertise in
urban physics
> Parallel
processing
potential
> User friendly
> Extensive
documentation
with tutorials
ANSYSCFX
Microscale
CFD
> General
purpose CFD
platform
> Many
options of
> Since it is a
general CFD
platform, the
user has to
develop and
> User-defined
models for
evaporation and
evapotranspiration
Short and
long wave
radiation
models are
included
Satisfying for
both weak
and strong
winds
High
Commercial
73
Table 4: Important strengths, weaknesses and special features of computational urban microclimate simulation tools.
Special modelling features
Tool
Method
Strengths
turbulence
models and
radiation
models
> Flexibility
and easiness of
grid generation
Weaknesses
Evaporation and
evapotranspiration
Accuracy
CPU time
Availability
Radiation
incorporate
user-defined
models, thus it
requires high
expertise in
urban physics
> Parallel
processing
potential
> User friendly
> Extensive
documentation
with tutorials
Phoenics
Microscale
CFD
> General
purpose CFD
platform
> Many
options of
> Since it is a
general CFD
platform, the
user has to
develop and
> User-defined
models for
evaporation and
evapotranspiration
Short and
long wave
radiation
models are
included
Satisfying for
both weak
and strong
winds
Very high
Commercial
74
Table 4: Important strengths, weaknesses and special features of computational urban microclimate simulation tools.
Special modelling features
Tool
Method
Strengths
turbulence
models and
radiation
models
> Extensive
documentation
with tutorials
Weaknesses
Evaporation and
evapotranspiration
Accuracy
CPU time
Availability
Radiation
incorporate
user-defined
models, thus it
requires high
expertise in
urban physics
> Restricted
options of grid
generation
(e.g.
tetrahedral
cells are not
included)
75
2.2.6 CFD and multi-zonal coupling for building energy assessments
The energy balance equation for a building is expressed as follows: The heating/cooling load of the
building equals to the sum of the internal heat gain from lights, occupants and equipment, the
convective heat transfer between building’s interior surfaces and internal air, the convective heat
transfer due to air infiltration and the change of energy stored in the internal air. On the other hand,
the energy balance equation for building exterior surfaces may be expressed as follows: The
conduction heat flux through the wall equals to the sum of the transmitted solar radiation, the
absorbed solar radiation, the net long wave radiation heat flux and the convective heat flux
exchanged with the outdoor air.
The above verbal explanation of the heat exchange between indoor and outdoor space reveals that
building surrounding environment influences building energy performance. These influences may be
described as follows:
 The incident solar radiation on building walls, which is affected by the adjacent obstacles such
neighbouring buildings, trees and hills.
 The convective heat flux at the exterior surfaces, which is determined by the Convective Heat
Transfer Coefficient (CHTC) and by temperature difference between the outdoor air and
exterior surfaces.
 The intensity of incoming long wave radiation.
 The heat and moisture transfer through infiltration.
As far as the preparation of a technical study is concerned targeted to building energy assessments,
ideally all the above influences should be adequately captured. The available tools used for building
energy assessment purposes are mainly the multi-zonal modelling tools also known as Building
Energy Simulation (BES) tools (see section 2.1.4 above). These, however, present some deficiencies in
capturing all the impacts described above. These deficiencies are the following:
 They disregard the non-uniformity of the CHTC in the vicinity of the building. They rely only to
a mean value of CHTC based on climate data time-series of the wider climate zone.
 Infiltration is handled by empirical formulas rather than a more precise representation
(accounting for velocity fluctuations through openings for example).
 Surrounding trees are treated like simple obstacles on incident radiation rather than
contributors of moisture and obstructions to outdoor airflow, thus CHTC and air infiltration
effects are underestimated.
 Evaporative cooling effect emanated from water surfaces is ignored.
76
 Surrounding buildings other than being treated as obstacles on incident radiation their effect
on airflow pattern and, therefore, on CHTC is not taken into account.
 Outdoor climate data are most commonly taken from default libraries of wide climate zones
available in the tools background, which are, however, different from the actual ones
especially during summer season due to the Urban Heat Island effect.
To the best of the authors’ knowledge no tool that deals with the impact of the external microclimate
on building energy consumption exists. On the other hand, CFD tools seem very promising towards
the simulation of urban microclimate. As described in section 2.2.3 CFD micro-scale models can
simulate physical mechanisms that comprise urban microclimate and by these means they can
quantify all the influences of outdoor physical environment to indoor energy consumption.
Consequently, the drawbacks reported above can be eliminated under the perspective of CFD/BES
tools coupling. Indeed, numerous authors in scientific literature succeeded to couple these methods
through the following ways104,120:
The fully coupled approach
In this approach the CFD and the BES tool are in a constant link for each time-step throughout the
simulation procedure. The information exchanging between the two tools in each time-step usually
takes place as follows:
 An initial value of external wall temperature in the CFD model is adopted as a wall boundary
condition. Air properties of the incoming wind are taken from the nearest meteorological
station and they are set as inflow boundary condition in the CFD model. Boundary conditions
for physical features, such as trees, water surfaces, are also set as boundary conditions.
 The CFD model is executed and provides a preliminary prediction of the microclimate in the
vicinity of the building(s) of interest, i.e. air temperature, convective heat transfer coefficient
and relative humidity.
 These climate parameters are then passed to the BES tool as climate data (i.e. instead of
using the default data from the BES tool libraries) and the BES tool calculates, apart from
Energy-related indicators, external walls temperature.
 The new updated value of building external walls returns to the CFD model as a wall
boundary condition, which is executed again towards the update of microclimate surrounding
the building. The updated microclimate is then passed to the BES tool which is executed again
towards the update of the energy-related indicators and the wall temperature.
120
X. Yang et al., An integrated simulation method for building energy performance assessment in urban environments, Energy and Buildings
54 (2012) 243-251.
77
 And so on.
The iterative process above ends when the wall temperature computed by the BES tool, taking into
account its pass from the CFD tool, presents a really small change from one loop to the other
(convergence of solution). Then the solution is obtained and the building energy-related indicators
are finally calculated.
The semi-coupled approach
A more simple and practical way to consider external microclimate in the vicinity of the building is the
semi-coupled approach. The main characteristic of this approach is to utilize the outputs of the CFD
model and use them to alter the default climate data time-series used in the BES tool. The main steps
followed are:
 Incoming-wind properties are taken from the nearest meteorological station and they are set
as boundary conditions in the CFD model.
 Appropriate boundary conditions to account for evaporation and evapotranspiration are set
to water and vegetations surfaces, respectively.
 Estimations of the incident solar radiation on solid surfaces may be emerged utilizing a solar
ray tracing model, usually incorporated in CFD models, taking into account albedo and
emissivity values of materials.
 The above is used to estimate convective heat flux from exterior building walls.
 Taking into account the above boundary conditions, the CFD model is executed and provides
the microclimate in the vicinity of the building.
 The microclimate provided by the CFD model can then be transformed in the format of
weather files of the BES tool, and inserted in the BES tool instead of using the default weather
file from the BES library.
Obviously, the tactic above is one-way approach, i.e. the CFD is executed first and the microclimate
emerged is then passed to the BES tool in the format of the default weather file. It should be
mentioned that since this method treats CFD and BES models separately, more than average
expertise is required by the user in order to obtain correct estimations of initial parameters used as
boundary conditions. This means that the user should apply externally or incorporate special models
that solve for these parameters in order to provide boundary conditions, e.g. a correct “guess” of
internal temperature and solution of conduction equations to estimate external surface temperatures
taking into account incident solar radiation.
78
It may be concluded that BES/CFD coupling provides a more accurate prediction of energy-related
indicators; hence, a more accurate selection of retrofit measures. Through this coupling procedure it
becomes clear that energy-related indicators are only a symptom of the mathematical interpretation
of building and urban physics and more specifically of indoor-outdoor interactions.
3. Decision making through optimization algorithms
The concept of decision making in building design and urban planning is concentrated mainly on the
identification of the optimal combination(s) of retrofit measures so that specific goals are obtained.
As a consequence, decision making consists of the following aspects:
Problem statement
A precise definition of the objective of decision making is always a good start of the procedure to be
followed. A representative statement regarding urban and building design may be formulated as
follows: Determination of the optimal blend(s) of retrofit measures that ensure acceptable values of
living conditions (thermal comfort and air quality indicators) under minimum energy consumption
(for buildings), minimum costs and minimum attenuation periods of investments.
Recognition of goals
A decision-making strategy targeted for building and urban renovation aims to the following goals:
Ensure satisfying living conditions (comfort and pollutant concentrations within acceptable levels),
retain minimum energy consumption to achieve satisfying conditions, retain minimum installation
and operational costs of investments as well as minimum attenuation periods.
Recognition of design parameters
Once the goals have been specified, the decision maker should focus on the design parameters, i.e.
the ways to achieve the specified goals. In case of building energy upgrading and Urban Heat Island
mitigation projects, the main design parameters are the following:
 Buildings: Insulation materials; Windows; Building systems for heating, cooling, lighting and
hot water production.
 Open spaces: Ground materials; vegetation species, size and orientation; Water surfaces size
and orientation; other measures such as size and orientation of pedestrian roads.
79
Means to solve the decision making problem
It is true that regarding the aforementioned design parameters, a vast amount of technologies exist in
the market that can be applied to achieve the pre-defined goals. The challenging issue is that the
decision maker should select the optimal among these solutions. In case when several goals are set,
most of the times being trade-off variables, e.g. more expensive investments are more likely to
achieve minimization of energy consumption, a systemic procedure is required in order to rationally
weigh all goals and come-up with feasible and cost-effective solutions.
Indeed, in building energy and urban environment design problems the decision making problem is
complex since retrofit options are vast in number, while numerous limitations should be satisfied. For
this reason, the systemic procedure suggested in such problems involves the following steps:
 Formulation of a cost function: Often a cost or objective function is formulated which is
expressed as the weighted average of the target variables (goals), in which the importance of
each variable is represented by weighting factors, usually receiving values from 0 to 1
(obviously when the weighting factor is 0, the variable is no longer a goal, while when it is 1 it
is of highest importance). If the designer wishes to give priority to some variables against
others, the lowest value is inserted in the weighting factors of the latter ones. The main goal
of the designer is to minimize the cost function and according to the weighting factors
prioritizing the variables that need to be minimized by a large amount. In complex problems,
a group of cost functions may be set.
 Specification of constraints: Apart from the cost function, in such engineering problems, it is
more likely that the designer wishes that certain variables should be confined within special
limits once the decision is made. In this case special constraints are set and associate the cost
function in the whole solution procedure. This formulation stands for the so-called
(constrained) Optimization Problem or Scheme, which mathematically expresses the Decision
Making problem.
 Means to solve the optimization problem:
o
Parametric analysis: One way to solve the problem is through a parametric analysis.
In this approach the designer pre-selects the tuned design variables and performs
different runs of the physical model (being a CFD or a BES or a CFD/BES coupled
model depending on the problem considered, being a building or an open space). For
each run the designer closely monitors the results for each combination of design
variables values until the cost function is minimized adequately and the constraints
are satisfied.
80
o
Optimization algorithm: The main drawback of the tactic above is that it requires
great time and effort from the designer’s side in order to identify the optimal
solution. Additionally, depending on the narrowness of the predefined constraints
and the desired level of the cost-function minimization, a simple parametric analysis
most likely disregards other feasible solutions which may be better in terms of costeffectiveness for example. In order to avoid such problems, special algorithms are
available (either gradient-based or gradient-free) which undertake this job. In simpler
words, these algorithms undertake the monitoring of the results of parametric runs
the designer would, but they do it better in terms of accuracy, provision of all feasible
solutions and calculation speed in comparison with human intervention. Of course,
these algorithms only do what the user commands them to do, i.e. if the optimization
problem is not pre-set correctly, the algorithm will obtain peculiar results. Therefore,
an average expertise of optimization problems is required depending on the
computational tool used to solve the problem.
The most common means to solve the optimization scheme are summarized in Table 5. A brief
description of the ways to apply each method strengths and weaknesses are tabulated. In any case,
the selection of the method to be applied depends on the desired accuracy of the solution (blend of
retrofit measures) and it is up to the working team to decide. From an engineering point of view, the
2nd and the 4th method seem more promising as they both provide the group of optimal solutions and
they are applicable for problems with high number of design and (trade-off) target variables.
Stavrakakis et al. (2011)121 and Stavrakakis et al. (2012)122 adopted the 4th method reported in Table 5
below. The studies were focused on the optimization of architectural features (openings’ size,
number and orientation) in case of a test building and of a student dormitory so that the best
conditions of comfort and hygiene are ensured within the occupied zones. They demonstrated the
usefulness of the optimization method in decision making for architectural design renovation
purposes.
121
G.M. Stavrakakis et al., Selection of window sizes for optimizing occupational comfort and hygiene based on computational fluid
dynamics and neural networks, Building and Environment 46 (2011) 298-314.
122
G.M. Stavrakakis et al., Optimization of window-openings design for thermal comfort in naturally ventilated buildings, Applied
Mathematical Modelling 36 (2012) 193-211.
81
Table 5: Means to solve the optimization scheme.
Method
Application
Strengths
Weaknesses
User selection through parametric
analysis
Parametric analysis => Database=>
Selection of (usually one) optimal
design
> User friendly-limited expertise is
required
> Not applicable for multi-criteria
schemes with trade-off variables
> Relatively good accuracy for small
problems, i.e. low number of design
and target variables
> Limited accuracy of the near
optimal solution
> Applicable to multi-criteria
problems of high dimensions (high
No. of variables) and with trade-off
variables
> Limited accuracy of the near
optimal solution(s)
Discrete database-handling
algorithms
Parametric analysis => Database=>
Database-handling algorithms of
discrete variables (gradient-free
algorithms) towards the selection of
the best parapetric cases that
satisfy the cost function and
constraints
> Other feasible solutions may be
disregarded
> In order to deal with the above
drawback a larger database is
produced through (over)simplifying the physical problem
> Above than average knowledge of
discrete database-handling
algorithms is required.
82
Development of metamodels
(correlate design and target
variables) following linear or nonlinear algorithms (e.g. artificial
neural networks)
Parametric analysis => Database=>
Regression=> Metamodels=>
Selection of optimal solution ranges
> Applicable to multi-criteria
problems with trade-off variables
but for relatively low number of
design and target variables
> Caution to select the optimal
design variables ranges is required
> The near-optimal solutions are
still “hiding” in the continues
domain of the selected ranges
> Above than average knowledge
on regression algorithms is required
Combination of meta-models and
Continues and/or Discrete
optimization algorithms
Parametric analysis => Database=>
Regression=> Metamodels =>
Database-handling algorithms of
continues (gradient-based) and/or
of discrete (gradient-free) variables
> Applicable to multi-criteria
problems of high dimensions (high
No. of variables) and with trade-off
variables
> Relatively high computational cost
> Above than average knowledge of
discrete and continues databasehandling algorithms
> Improved accuracy of the near
optimal solution
83
4. Level of use of assessment tools
This section is focused on the level of use of energy and microclimate assessment methods for
research purposes mainly originated both in partner Countries and worldwide. The main source of
information to produce the results was the Scopus123 database of peer-reviewed literature. The
results of the investigation are presented in the subsections below.
Table 6: No. of studies using BES tools in partner Countries and elsewhere.
Source: Scopus
(www.scopus.com)
Software/Country
No. of studies found
Croatia
France
Greece
Italy Spain
Elsewhere
Antherm
0
0
0
0
0
0
Autodesk Green Building Studio
0
0
0
0
0
6
BEAVER
0
0
0
0
0
0
Bsim
0
1
0
1
0
22
DeST
0
1
0
0
0
87
DOE-2
0
5
1
2
3
234
ECOTECT
0
1
0
1
1
57
ENER-WIN
0
0
0
0
0
17
EnergyPlus
0
23
12
43
8
514
eQUEST
0
0
0
0
1
42
ESP-r
0
4
5
7
3
222
IDA-ICE
0
1
0
4
0
27
IES Virtual Environment (IESVE)
0
0
0
1
0
37
SUNREL
0
1
0
0
0
7
123
www.scopus.com
84
TAS
0
0
0
1
1
38
TRNSYS
1
60
16
41
14
318
4.1 Level of use of BES tools for building energy performance assessment
Herein the number of published studies that used the Building Energy Simulation (BES) tools listed in
section 2.1.4 is reported. The results of the analysis are listed in Table 6. Among partner Countries, a
nearly zero level of use of BES tools (only one study using TRNSYS was found) is observed for Croatia.
The tools most frequently used in the other partner Countries are TRNSYS and EnergyPlus. The results
are further analysed towards the calculation of percentage of use of each one of the two BES tools
(see Fig. 4) and it is seen that TRNSYS presents a higher preference in the MED area, especially in
France. The classification of partner Countries based on the level of use of all BES tools is presented in
Figure 5. Figures 4 and 5 reveal that France and Italy hold the primacy of BES tools use, Greece and
Spain follow, while a nearly zero BES use frequency is observed for Croatia. It should be pointed out
that the advanced search utility of the Scopus system was used, and the results were obtained based
on the following filters:
 For all fields of manuscripts (abstract, title, keywords, main text) the following key words
were used: “Name of the software” and “building simulation”
 In order to determine the origins of each study the following keys were used for affiliation:
“Croatia or France or Greece or Italy or Spain” or “NOT Croatia AND NOT France AND NOT
Greece AND NOT Italy AND NOT Spain” to find studies originated in partner Countries or
elsewhere, respectively.
EnergyPlus
Level of use in partner Countries and Worldwide
France Greece
4%
2%
Italy
7% Spain
1%
Elsewhere
86%
(a)
85
TRNSYS
Level of use in partner Countries and Worldwide
Greece
4%
France
13%
Elsewhere
71%
Italy
9%
Spain
3%
(b)
Figure 4: Level of use of: (a) EnergyPlus and (b) TRNSYS.
120
100
80
60
40
20
0
Italy
France
Greece
Spain
Croatia
Figure 5: Number of studies conducted using BES tools in partner Countries.
86
4.2 Level of use of field modelling tools for urban microclimate assessment
A similar analysis as above was performed for field modelling tools, namely UCM and micro-scale CFD
tools (see section 2.2.5 above). The results of the analysis are listed in Table 7 below. Among partner
Countries, a nearly zero level of use of field modelling tools (only one study using ANSYS-Fluent was
found) is observed for Croatia. It becomes clear that for urban environment assessments CFD models
are more frequently used in both partner Countries and worldwide, compared to UCM tools. The tool
most frequently used in partner Countries is ANSYS-Fluent. The results are further analysed towards
the calculation of percentage of use of ANSYS-Fluent (see Fig. 6) and it is seen that Fluent presents
the highest preference in Italy. The classification of partner Countries based on the level of use of any
field modelling tool is presented in Figure 7. Figures 6 and 7 reveal that France and Italy hold the
primacy of field modelling tools use, Greece and Spain follow, while a nearly zero frequency of using
field modelling tools is observed for Croatia.
It should be pointed out that the advanced search utility of the Scopus system was used, and the
results were obtained based on the following filters:
 For all fields of manuscripts (abstract, title, keywords, main text) the following key words
were used: “Name of the software” and “urban microclimate” or “urban environment”. This
set of key words was chosen as most studies using UCM tools use the characteristic phrase
“urban microclimate” mainly, while most studies using CFD tools use the characteristic
phrase “urban environment” mainly.
In order to determine the origins of each study the following keys were used for affiliation: “Croatia
or France or Greece or Italy or Spain” or “NOT Croatia AND NOT France AND NOT Greece AND NOT
Italy AND NOT Spain” to find studies originated in partner Countries or elsewhere, respectively.
Table 7: No. of studies using field modelling tools in partner Countries and elsewhere.
Source: Scopus
(www.scopus.com)
Software/Country
No. of studies found
Croatia
France
Greece
Italy Spain
Elsewhere
UHSM
0
0
0
0
0
2
TEB
0
7
0
2
2
18
SOLWEIG
0
0
0
1
0
7
Rayman
0
2
5
3
1
49
87
ENVI-met
0
1
3
6
0
50
ANSYS-Fluent
1
22
11
34
16
416
ANSYS-CFX
0
2
2
8
6
48
Phoenics
0
4
5
0
0
47
ANSYS-Fluent
Level of use in partner Countries and
Worldwide
France
Greece Italy
5%
2%
7% Spain
3%
Elsewhere
83%
Figure 6: Level of use of ANSYS-Fluent.
60
50
40
30
20
10
0
Italy
France
Greece
Spain
Croatia
Figure 7: Number of studies conducted using field modelling tools in partner Countries.
88
4.3 Level of use of CFD/BES coupled simulations for building energy assessment
As reported in section 2.2.6 above there is no tool which takes into account the impact of
surrounding microclimate on building energy consumption. To solve this kind of problems, some
studies exist in international scientific literature that demonstrate coupling possibilities of CFD and
BES tools. As regards the level of use of coupled approaches, nearly-zero frequency is observed in
partner Countries using the same searching utility, Scopus. In view of elaborating the coupling
perspective, the most useful information is to find which are the most common CFD and BES tools
being coupled, regardless of the origin of the studies. Since coupled simulations are still in their
infancy, the main focus point is to realize the feasibility of the coupling procedure and become aware
of which tools may be coupled. The feasibility of coupling CFD and BES tools is extensively described
in international literature for the following tools (see also the representative studies cited for each
approach):
 ENVI-met/EnergyPlus120
 Fluent/TRNSYS124
 Fluent/Solene105
It is encouraging that the CFD/BES coupling can be obtained even by using freely available tools such
as the ENVI-met and EnergyPlus.
5. Discussing the reasons of limited use of urban and building physics tools
According to various studies125,126,127 it appears that building and urban design professionals use
computational tools for urban and building physics simulation purposes very rarely. The main reasons
for this observed lack of use of the available plethora of tools in practical cases are summarized as
follows:
 Complexity: Many designers consider most computational tools complex and not user
friendly.
 Time consuming: Simulations (iterative calculations) take too much time to converge,
especially when CFD tools are used.
124
J. Allegrini et al., Analysis of convective heat transfer at building facades in street canyons and its influence on the prediction of space
cooling demand in buildings, Journal of Wind Engineering and Industrial Aerodynamics 104-106 (2012) 464-473.
125
S. Burke, Building physics tools: Needs, use and the lack of use in the building process. Modelling non-isothermal moisture flow and frost
penetration, PhD thesis, Lund University, Lund, 2009.
126
M.W. Ellis & E.H. Mathews, A new simplified thermal design tool for architects, Building and Environment 36 (2001) 1009-1021.
127
W.N. Hien et al., The use of performance-based simulation tools for building design and evaluation-A Singapore perspective, Building
and Environment 35 (2000) 709-736.
89
 Requirement for advanced urban and building physics expertise: Despite the efforts made
from CFD and BES vendors to create user friendly simulation tools that require minimum level
of expertise, professionals still consider that advanced expertise is necessary to use these
simulation softwares.
 Lack of designers’ flexibility to adopt new approaches: Most designers who have spent many
years in their profession are strongly engaged to ways of dealing with design practices they
already know and they spend no time to get familiarized with novel methods.
 Lack of stimulating mechanisms: In Europe, although the introduction of Energy Efficiency
regulations (building energy certification, minimum requirements for energy consumption for
new and renovated buildings) stimulates the use of BES tools, more innovative tools which
account for energy behaviour and UHI impact on building energy consumption are still of very
limited use. In most Countries only the national methodology is applied even though the
results obtained may be very different in comparison to the actual energy consumption 128. As
regards urban planning, other than empirical guidelines no regulation exists to guide
designers towards the use of simulation tools in order to estimate microclimate in open
spaces.
Most of the aforementioned points are validated in the investigation via questionnaire survey
obtained by Burke (2009)125. In that study, professionals of high (PhD), medium (engineers) and low
(technicians) expertise were participated in the survey answering questions related to reasons why
innovative tools were not used. The participants were invited to perform energy assessments for
specific case studies and once finished to answer questionnaires. The findings of the survey are
summarized as follows:
 When asked whether any assessment software was used, most replied that they did use
some very basic ones.
 When asked whether other sophisticated approaches are required in order to improve their
results, only those of high-level expertise had suggestions.
 Those who did not use any tool (those of low expertise and some of medium expertise), but
only intuitive estimations or analytic calculations were applied, they replied that the tools are
too costly to buy, too difficult to learn and too much simulation time.
In order to understand more deeply the reasons that novel methods are not widely used by
designers, a contrasting between simulation tool users and designers in terms of their background
and study approaches is required.
The differences between simulation tool users and designers in terms of their intellectual and
practical knowledge in relation to the type of phenomena they assess and how these phenomena are
128
E. Dascalaki et al., D6.2: National scientific report-Greece, IEE project: TABULA, National Observatory of Athens, 2012.
90
represented are listed in Table 8129. The differences in terms of the way practitioners approach the
design problem are depicted in Table 9129. The tabulated differences reveal important aspects of
each group (tools users and designers) that need to be taken into account in the industry of
developing simulation tools which integrate better within the design process.
Table 8: Differences in knowledge between simulation tool users and designers.
Background aspects
Simulation tool users
Designers
Formal/Intellectual
knowledge
Systematic and scientifically
based
Constructivist with product
and process interrelated
Physical phenomena
propagation
Phenomena develop over
time
Phenomena develop in space
Representation of physical
phenomena
Mathematical (partial
differential equations)
Visual-Intuitive
Interpretation of reality
Thermophysical related
Leading ideas are used to
parameters and topological
derive sets of rules to test
relationships are mapped into and criticise proposals
a predefined heat balance
structure
Practical knowledge
Judgement of what to model
and why; Capability of
simplifying reality to achieve
it
Based on learning by doing;
Ability of solving the problem
at hand
It can be seen that knowledge of tool uses and of designers are complementary. Tool users are able
to explain and propose the way for a piece of design to fulfil aspects related to thermal performance
while designers are able to explain and propose the structure of this piece of design within which
human activities take place and individual and cultural expressions are addressed. The consequences
of this finding are directly related to different aims and different design actions and that is where
limitations in understanding among practitioners tend to lead to disjointed solutions.
129
C.B. de Souza, Contrasting paradigms of design thinking: The building thermal simulation tool user vs. the building designer, Automation
in Construction 22 (2012) 112-222.
91
Table 9: Differences in praxis between simulation tool users and building designers.
Approach to deal with the Simulation tool users
design problem
Designers
Approach to experiment
Similar to the one of natural
sciences: Realist/ Rationalist/
Objective
Similar to the one of
humanities and arts:
Relativist/ Constructivist/
Subjective
Hypothesis
Model, reference and desired
states
Constructed based on the
uniqueness of a situation
Test method
Structured series of
perturbations to be tested
(using the model)
Empirical “moves” to improve
a perceived situation
Assessment method
Quantifying cause/effect
relationships
Empirical prediction of the
impact of “moves”
As structure and functionality of an open or a building space are interrelated, it makes no sense to
separate actions and results obtained by the simulationist from those obtained by the designer.
Designers would benefit from a deeper understanding of building and urban physical performance
and tool users and developers would benefit in understanding more about how buildings are
structured. This observation gives rise to the following issues:
 What do designers need to know about physics in order to explain and propose the physical
structure of an artefact that fulfils aspects related to thermal performance?
 What do simulation software developers need to know about building and urban design so
that they can either take the structure of an artefact into consideration when proposing
solutions or develop interfaces to inform designers about how the proposed structure for an
artefact is fulfilling aspects related to thermal performance?
The above considerations are especially important and have been empirically approached by several
researchers and institutions since the early 90’s130,131,132. In this context, the education of building and
urban designers in building and urban physics should consider the following aspects:
130
K. Papamichael, Application of information technologies in building design decisions, Building research and information 27 (1999) 20-34.
K. Papamichael, Product modelling for computer-aided decision-making, Automation in Construction 8 (1999) 339-350.
132
Z. Yu et al., A decision tree method for building energy demand modeling, Energy and Buildings 42 (10) (2010) 1637–1646.
131
92
 Understanding that thermal phenomena are extremely complex and cannot be intuitively
assessed.
 Understanding of the simplification strategies involved in mapping physical phenomena into
predefined structures (modelling tools) that follow the laws of natural science.
 Understanding the fundamentals of the basics behind heat balance and why it calls for
systematic investigations about the role of thermo-physical properties and topological
relationships in the overall performance assessment.
The aforementioned points may seem quite obvious to a simulation tool user but are definitely not
obvious among designers who tend to be educated within a “naïve” physics environment mainly
through directly relating its content to design applications disregarding the physical mechanisms
involved in it. On the other hand, simulation tool developers and users need to understand designers
are not systematic about making design suggestions. As they deal with phenomena mainly in space,
they derive quantities directly from visual representations and therefore want information as
coherent as possible within this type of representation system. As they set up and investigate design
proposals in a non-systematic but constructivist way, they want information about how their “moves”
affect the overall performance and expect propositions from collaborators as well as simulation
inputs and outputs to be coherent with it. This means collaboration can be improved if the simulation
tool developers understand the way designers set up and evaluate design hypothesis. It also means
that tool developers should connect the meaning of performance results somehow with the structure
of the artefact if simulation outputs are to be more informative to designers.
Through analyzing the needs from the point of view of both software users and designers, clearly a
debate on rethinking and reassessing is revealed regarding which issues could potentially be
addressed to facilitate the use of simulation tools throughout the design process. This section looked
at this issue by contrasting design thinking and physics simulation. This contrasting leads to some
starting points as follows:
 Current research in the field of urban and building physics tends to be quite unilateral and
seems to be based on interpretations of what the physics simulationists community assumes
the designer needs. As this community lacks a comprehensive understanding of designer
knowledge and praxis, tools developed tend to undergo limited uptake in urban and building
design.
 Awareness raising of designers is required as regards urban and building physics
fundamentals in order to realize the usefulness of simulation tools towards the
recommendation of feasible and adequate design structures. This awareness raising may be
achieved through training seminars, informative workshops and easy-to-understand
documentation.
93
 Effective communication paths for demonstration cases to outreach designers. The latter
have not always access to scientific literature and such informative material transfer should
be ensured through other paths and communication media, such as technical reports in
newspapers, technical reports in the websites of technical associations, social media, etc.
Establishment of clustering schemes among building energy experts, urban physics experts and
designers, towards the formulation of partnerships and collaborations to deal effectively and
thoroughly with building energy upgrading and open-spaces UHI mitigation problems.
6. Conclusions
The present report stands for a review of innovative methods and simulation tools in international
level. The review is focused on the presentation of innovative building-energy and urbanenvironment assessment tools which can be used to facilitate the suggestion of feasible and costeffective retrofit measures in the techno-economical study pre-renovation phase. It is true that since
the issuing of EPBD directive, most Member States have developed their own tools and
methodologies to perform building energy assessment studies. However, in some cases crucial
physical aspects are ignored, such as the impact of urban heat island effect and of occupants’
behavioural patterns on building energy consumption. On the other hand, as regards the study of
open-spaces renovation, other than some empirical guidelines related to open-space design, there
exists no national guideline or tool or methodology to guide engineers and designers through the
quantification of the urban heat island effect on pedestrians’ wellbeing (comfort and hygiene
indicators).
This report attempts to respond to the concerns above through the review and report of innovative
methods that account for critical building and urban physics aspects and they act complementarily to
current legislation and regulatory framework. In this context the following methods were found:
 Building energy simulation tools that ensure:
o
Access to climate inputs in order for the user to provide local microclimate data
when necessary
o
Access to building-systems schedules in order to account for energy behaviour
 Field modelling tools that ensure:
o
Quantification of microclimate parameters, such as wind speed, temperature,
relative humidity, turbulence intensity distribution.
o
Computation of thermal comfort indicators, such as PMV, PET, SET*, etc.
94
o
Computation of air quality indicators, such as pollutant concentration at the
pedestrian level height.
 Coupling possibilities between building energy simulation and open-space field modelling
tools in order to account for the effect of UHI on indoor energy consumption.
 Decision-making strategies through formulating and solving optimization problems.
It was found that the innovative BES tools most commonly used in the scientific literature are TRNSYS
and EnergyPlus in both partner Countries and worldwide. As far as micro-scale CFD modelling in open
spaces is concerned ANSYS-Fluent enjoys the highest level of use, although it requires urban physics
expertise since it does not include by default tailored physical models (e.g. evapotranspiration) and
the user has to provide them him/herself. On the other hand, ENVI-met, which is also a micro-scale
CFD tool, is targeted to urban physics simulations and requires less expertise to perform simulations.
However, simulation time using ENVI-met is much higher than using Fluent and it presents less
accuracy due to its simplified model of turbulence.
In addition, studies that demonstrate BES/CFD tools coupling were found and the coupling strategies
are described. Among others, coupling approaches with the following tools combinations were found:
Fluent/TRNSYS and ENVI-met/EnergyPlus.
Decision making strategies to select the optimal blends of retrofit options were discussed from the
point of view of transforming the decision-making problem into a mathematical optimization
problem. Several options for solving the optimization problem were contrasted. It was found that the
procedure of correlating the design with target variables and solve for the optimization problem
based on iterative algorithms is the best approach in terms of accuracy and completeness of the nearoptimal solutions.
Finally, the reasons why novel simulation methods are not widely used in the techno-economical
study phase were discussed. It was found that the main reasons are concentrated on the current
regulatory framework which does not stimulate designers to use more sophisticated tools and to
their lack of awareness regarding urban and building physics. Some communication and awareness
raising paths were identified, which will be utilized during the implementation of the REPUBLIC-MED
project.
95
Annex: Application of innovative methods in the partner Countries
96
Annex 1: Review of innovative methods for retrofitting
purposes - Greece
Contribution to deliverable D.3.3
Component 3- Analysis-desk research
Phase 3.3 - Analysis of innovative retrofitting methods applied in the technoeconomical study stage
Contract No.: 1C-MED12-73
Axe2: Protection of the environment and promotion of a sustainable territorial
development
Objective 2.2: Promotion and renewable energy and improvement of energy
efficiency
Authors: Municipality of Piraeus
with the support of KiNNO Consultants Ltd.
97
Executive Summary
This report is a review of innovative technical methods and tools that can be used to conduct
improved techno-economical studies for the refurbishment of public buildings and open spaces,
deriving from the Greek scientific literature.
The main outcome of the review with regards to the buildings is that there is limited use of
computational tools, other than the national methodology & software (TEE-KENAK), which can be
found reported only in a research base. With regards to the bioclimatic design of open spaces, there
is no regulation available to push professionals towards the use of available innovative simulation
tools, other than research results and technical directives for applications in specific funding
programmes (eg. Technical guidelines of CRES for organizations conducting a techno-economic
analysis before applying for funding in Bioclimatic Upgrade for Open Spaces).
This report was created within the framework of the Project “REPUBLIC-MED: REtrofitting PUBLic
spaces in Intelligent MEDiterranean Cities”. The Project, as part of the MED Programme, is cofinanced by the European Regional Development Fund and National Funds.
The present document is the input for the activity 3.3 - Analysis of innovative retrofitting methods
applied in the techno-economical study stage, on behalf of the Municipality of Piraeus, implemented
by KiNNO Consultants Ltd.
98
1. Introduction
Scope of the Review
This report is a review of innovative technical methods and tools that can be used to conduct
improved techno-economical studies for the refurbishment of public buildings and open spaces,
deriving from the Greek scientific literature.
The methods identified and presented in this report are innovative from the technical point of view;
Innovative methods are these which could be complementary applied to the already applicable
national ones, providing adequately and cost-effectively (reasonable simulations’ time) results.
Objectives
 Identification and presentation of innovative technical methods and tools, their application
and capabilities in conducting improved techno-economical studies

Identification and presentation of Greek case studies using the innovative technical methods
and tools identified

Review, classification and assessment of the usefulness and effectiveness of the innovative
technical methods and tools identified in the Greek scientific literature

Identification of the reasons of limited use of the innovative technical methods and tools
identified in the national tools and policies for refurbishment of public buildings and open
spaces
99
2. Identification and presentation of innovative tools
This section is focused to the identification and brief presentation of innovative technical methods
and tools used to conduct improved techno-economical studies for the refurbishment of public
buildings and open spaces, found in the Greek scientific literature.
The innovative tools identified in the Greek scientific literature that can be used to assess building
energy performance and UHI effect in open spaces are summarized in the table below. Following, a
brief presentation of each tool is available.
Buildings
 ECOTECT
Open Spaces
 ENVI-met
 ENER-WIN
 EnergyPlus
 ESP-r
 TRNSYS
Innovative tools that can be used to assess building energy performance and UHI effect in open spaces
100
Building Energy Simulation Tools
ECOTECT
ECOTECT is an environmental analysis tool –
primarily intended as a conceptual design tool- that
allows designers to simulate building performance
right from the earliest stages of conceptual design.
It combines a wide array of detailed analysis
functions with a highly visual and interactive display
that presents analytical results directly within the
context of the building model, enabling it to
communicate complex concepts and extensive datasets in intuitive and effective ways.
According to the US Department of Energy, it is a “complete environmental design tool which couples
an intuitive 3D modelling interface with extensive solar, thermal, lighting, acoustic and cost analysis
functions. ECOTECT is one of the few tools in which performance analysis is simple, accurate and most
importantly, visually responsive.
ECOTECT is driven by the concept that environmental design principles are most effectively addressed
during the conceptual stages of design. The software responds to this by providing essential visual and
analytical feedback from even the simplest sketch model, progressively guiding the design process as
more detailed information becomes available. Its extensive export facilities also make final design
validation much simpler by interfacing with Radiance, EnergyPlus and many other focused analysis
tools.”
ECOTECT offers a wide range of simulation and building energy analysis functionality that can
improve performance of existing buildings and new building designs. Although it has a user-friendly
interface and powerful visual analysis tool, thermal analysis accuracy and reliability, in comparison to
other simulation tools, are questionable133.
More information available at http://usa.autodesk.com/ecotect-analysis
133
Attia, S. 2011. State of the Art of Existing Early Design Simulation Tools for Net Zero Energy Buildings: A
Comparison of Ten Tools, Technical Report, Architecture et Climat, Louvain La Neuve: Université catholique de
Louvain. Available at: http://wwwclimat.arch.ucl.ac.be/s_attia/attia_nzeb_tools_report.pdf
101
ENER-WIN
ENER-WIN is an energy design tool, mostly used for large commercial buildings.
It simulates hourly energy consumption in buildings, including annual and monthly
energy consumption, peak demand charges, peak heating and cooling loads, solar
heating fraction through glazing, daylighting contribution, life-cycle cost analysis
and floating temperatures in unconditioned zones. Design data are tabulated by
zones, also providing duct sizes and electric power requirements.
ENER-WIN also includes weather data through a database of 1500 cities. Graphical output is in form
of bar charts and graphs.
More information available at http://pages.suddenlink.net/enerwin/
EnergyPlus
EnergyPlus134 is an energy analysis and thermal load simulation program.
Based on a user's description of a building from the perspective of the
building's physical make-up and associated mechanical and other systems,
EnergyPlus calculates heating and cooling loads necessary to maintain thermal
control setpoints, conditions throughout a secondary HVAC system and coil
loads, and the energy consumption of primary plant equipment.
EnergyPlus is capable of provision of accurate, detailed simulation capabilities through complex
modeling capabilities, including time steps of less than an hour. EnergyPlus also includes simulation
modules that are integrated with a heat balance-based zone simulation and input and output data
structures tailored to facilitate third party interface development. Furthermore it includes multizone
airflow, thermal comfort, natural ventilation, and photovoltaic systems.
EnergyPlus takes into account climatic conditions, providing also weather data for more than 1250
locations worldwide available, through its web site.
More information available at http://www.energyplus.gov
134
US Department of Energy – Office of Energy Efficiency and Renewable Energy website:
http://energy.gov/eere/office-energy-efficiency-renewable-energy
102
ESP-r
ESP-r135 allows an in-depth appraisal of the factors which influence the energy and environmental
performance of buildings. The ESP-r system has been the subject of sustained developments since
1974 with the objective of simulating building performance in a manner that:
a) is realistic and adheres closely to actual physical systems, b) supports early-through-detailed design
stage appraisals, and
c) enables integrated performance assessments in which no single issue is unduly prominent.
ESP-r attempts to simulate the real world as rigorously as possible and to a level which is consistent
with current best practice. By addressing all aspects simultaneously, ESP-r allows the designer to
explore the complex relationships between a building's form, fabric, air flow, plant and control. ESP-r
is based on a finite volume, conservation approach in which a problem (specified in terms of
geometry, construction, operation, leakage distribution, etc.) is transformed into a set of
conservation equations (for energy, mass, momentum, etc.) which are then integrated at successive
time-steps in response to climate, occupant and control system influences. ESP-r comprises a central
Project Manager around which are arranged support databases, a simulator, various performance
assessment tools and a variety of third party applications for CAD, visualisation and report
generation.
More information is available at http://www.esru.strath.ac.uk/Programs/ESP-r.htm
TRNSYS
TRNSYS is probably the most commonly used energy simulation program,
used for more than 30 years for HVAC analysis and sizing, multizone airflow
analyses, electric power simulation, solar design, building thermal
performance, analysis of control schemes, etc
TRNSYS (TRaNsient SYstem Simulation Program) includes a graphical
interface, a simulation engine, and a library of components that range from various building models
to standard HVAC equipment to renewable energy and emerging technologies.
More information is available at: http://sel.me.wisc.edu/trnsys/
135
http://www.esru.strath.ac.uk/Programs/ESP-r_overview.htm
103
Open Space – Urban Heat Island Simulation Tools
ENVI-MET
ENVI-met is a three-dimensional microclimate model designed to simulate the surface-plant-air
interactions in urban environment with a typical resolution of 0.5 to 10 m in space and 10 sec in time.
ENVI-met is a prognostic model based on the fundamental laws of fluid dynamics and thermodynamics. The model includes the simulation of:
•Flow around and between buildings
•Exchange processes of heat and vapor at the ground surface and at walls
•Turbulence
•Exchange at vegetation and vegetation parameters
•Bioclimatology
•Particle dispersion and pollutant chemistry
ENVI-MET Technical Aspects & Models
More information is available at: http://www.envi-met.com/
104
3. Applicability in Greek cases - Review & classification
This section is focused on the level of use of building energy simulations and microclimate models
and assessment methods, identified in the Greek scientific literature. Desktop research was
conducted: papers, studies, technical reports, presentations in conferences and best practices were
identified and assessed in order to identify and present of Greek case studies using innovative
technical methods and tools, assess their level of use and examine their innovativeness in terms of
consideration of microclimate, environmental, personal and energy parameters, and identify the
main reasons of not widely applying these innovative methods or taken into consideration in the
most common national methodologies and tools used in the technoeconomical study phase.
A summary of the identified tools and methods can be found in the following table:
Buildings
Results in GR
literature
ECOTECT
1
EnergyPlus
3
ESP-r
1
TRNSYS
3
Open Spaces
Results in GR
literature
ENVI-MET
2
It is obvious that the most commonly used building energy simulation tools in the Greek scientific
literature are EnergyPlus and TRNSYS, where regarding open spaces, only ENVI-MET microclimate
model usage was identified.
The analysis per study identified, its scope, the hypothesis used, the simulation method, the results as
well as comparisons, evaluations and conclusions are presented below:
105
Buildings
No
1
Title:
“Bioclimatic re-design of existing office building in Attica through the EnergyPlus
software”
Karalivanos Konstantinos and Koutsialis Christos, National Technical University of
Athens, presented on July 2013
BES
Method/To
ol Used:
Short
Description:
Analysis:
Available at:
http://dspace.lib.ntua.gr:8080/bitstream/123456789/8539/1/Karalivanos_Koutsialis.pdf
EnergyPlus
In the identified Diploma Thesis, bioclimatic redesign of an existing building is being
conducted by using the EnergyPlus software. The simulation of the building and the
proposed interventions are presented in detail for the upgrade of the energy
performance of the building. Furthermore, the results of the simulation are analyzed
and the model of the building is compared before and after all the interventions.
Finally, comparative diagrams of daily temperatures and the needs of electric energy
for cooling and heating of the building are displayed.
The geometry details of the building were given as input to EnergyPlus, using the
SketchUp and Legacy Open Studio Plug-in for SketchUp. The initial input of the
internal partitions and thermal zones of the real building was simplified in order to
enable the simulation. Ten thermal zones were identified, material and construction
layers’ characteristics were inserted, internal zone surface area data were described.
No indication on the input of the external climatic conditions is given.
Specific input on schedules, and internal gains and contaminant rates were included
for occupants in the zone were used (approximated representation). ASHRAE
Standard 55 Comfort Warnings were taken into account.
Furthermore schedules of equipment use (mainly PCs) lightning schedule, HVAC
systems operation (constant cooling & heating setpoints), were taken into account.
Monthly & Annual Energy needs for cooling & heating were calculated according to
the input described above. Deviation on the monthly & annual energy needs, as well
as deviation on the daily temperature of each thermal zone after proposed
renovations: Low Emissivity glazing, exterior shading add-ons and Natural
Ventilation-Night Cooling Systems
106
No
2
Title:
“Comparative analysis of energy use in Traditional House in the prefecture of
Karditsa”
Karatsiori, Vasiliki-Kyriakoula M., National Technical University of Athens, presented
on November 2008
Available at:
http://dspace.lib.ntua.gr/bitstream/123456789/2701/1/karatsioriv_dwellings.pdf
BES
Method/To
ol Used:
Short
Description:
EnergyPlus
Analysis:
In the identified work is studied the energy attribution of traditional stone building
in the city of Karditsa and is attempted the improvement of its energy attribution
with upgrading building's wrapping. Moreover, is investigated the energy behavior
of a same geometry building but with modern structural materials. After calculations
and comparisons it is found that the traditional building is manufactured based on
the principles of bioclimatic design and from the models that were described above,
the traditional building with the upgraded wrapping have the optimum energy
behavior.
Seven thermal zones were identified; material and construction layers’
characteristics were inserted.
External climatic conditions were provided by simulations with METEONORM
software (daily av. Temperature of the external climate, average direct-diffuseglobal insolation, monthly average wind speed, relative humidity & dew point),
where the monthly av. Rainfall (mm) was provided by CRES relevant studies.
Infiltration and ventilation schedule were party calculated and included.
The energy indicators used for the comparisons between simulations for the
building current status, it’s energy performance after upgrading building's wrapping
as well as the comparison with a same geometry building but with modern
structural materials, were: monthly zone transmitted solar energy, monthly zone
window heat gain-loss energy, monthly av. opaque surface inside face conduction,
monthly zone infiltration sensible heat gain-loss energy, monthly zone ventilation
sensible heat gain-loss energy and purchased air heating energy.
107
No
3
Title:
“Energy optimization of the Lampadariou building of the school of the Agronomy
Surveyor Engineers of NTUA using the software ECOTECT”
Maria Niaou, National Technical University of Athens, presented on November 2011
Available at:
http://dspace.lib.ntua.gr/bitstream/123456789/5404/3/niaoum_bioclimatic.pdf
BES
Method/To
ol Used:
Short
Description:
ECOTECT
Analysis:
The present thesis concerns the energy optimization of the Lampadariou building which
together with wings A and B serves the needs of the Agronomy Surveyor Engineers of
NTUA. In the first part bioclimatic architecture is defined and analyzed. In the second part
the energy study of the building is presented. In the context of this study temperature
and humidity measures were taken in the building using special devices, the thermal
hygrometers. Additionally, the building was designed using the software Ecotect and
thermal analyses as well as analyses of natural lighting were performed. Based on the
above improvements were proposed and were implemented in the building. Finally an
evaluation of the proposed measures was made
Fifty eight thermal zones were identified; material and construction layers’ characteristics
were inserted.
External climatic conditions (temperature – humidity) were initially measured // 30mins
step during summer 22/7/10 – 11/10/10 and winter 3/11/10-23/11/10 periods. However,
climate data from ECOTECT library were used for the analysis.
Specific input on schedules and thermal properties (heating and cooling systems, number
of occupants) were provided.
The retrofit measures proposed were: low emissivity glazing, exterior shading add-ons,
upgrading building's wrapping, upgrading the HVAC systems creation of green roof and
color change in the northern side of the building. The measures were not assessed from a
technoeconomical point of view.
The energy indicators used for the comparisons between simulations for the building
current status and its energy performance after the proposed retrofit, were: monthly &
yearly heating and cooling loads and hourly gains (conduction loads through the fabric,
indirect solar loads through solar gains on opaque surfaces, direct solar gains through
transparent windows, ventilation and infiltration gains through crack and openings,
internal loads from lights, people and equipment, inter-zonal loads from heat flow
between adjacent zones).
Thermal, optical and acoustic comfort of the occupants took place via questionnaire
survey (the results are provided in the annex of the study), however they do not seem to
have been clearly used as input to the study.
108
No
4
Title:
“Applications of Building Energy Simulation in Designing the Envelope - Interior
Installations”
Olympia Zogou, Tasos Stamatelos, University of Thessaly, presented on February
2005
Available at: http://www.mie.uth.gr/labs/ltte/grk/pubs/Office_building.pdf
BES
Method/To
ol Used:
Short
Description:
TRNSYS
Analysis:
The role of building energy simulation in supporting the design optimization of the
building envelope and energy subsystems is demonstrated in this paper by studying
an office building with the aid of the TRNSYS simulation suite. Input data to the code
are presented and discussed and sensitivity analysis of the effect of certain design
parameters on the yearly energy consumption of the building is carried out by
means of multiple building energy simulation runs.
The geometry details of the building were given as input to TRNSYS, using the
SIMCAD 1.3. The initial input of the internal partitions and material and construction
layers’ characteristics were inserted in order to create the initialization file for
PREBID program, after the necessary pre-processing.
Input of the external climatic conditions is given, via the dataset available from the
National Meteorological Service of Greece for the area of Volos.
Specific input on schedules was included for occupants in the zone were used
(approximated representation). Furthermore schedules of equipment use (mainly
PCs) lightning schedule, HVAC systems operation (constant cooling & heating
setpoints), were taken into account.
Annual Energy needs for cooling & heating were calculated according to the input
described above. Deviation annual energy needs per cooling and heating was
calculated and described per retrofit measure proposed.
109
No
5
Title:
“Energy Efficiency in Public School – Elementary School of Limni Evias”
Alexiou Kyriaki, National Technical University of Athens, presented on October 2012
Available at:
http://dspace.lib.ntua.gr/bitstream/123456789/7661/3/alexiouk_trnsys.pdf
BES
Method/To
ol Used:
Short
Description:
TRNSYS
Analysis:
In this the characteristics of the area where the building is located are encountered
(temperature, humidity, etc) and all the information relating to the Elementary
School (components, doors, windows, orientations, heating, cooling, etc). After that,
the presentation of TRNSYS software (version 16.1), which is used to simulate the
building, the Elementary School is modeled with the help of TRNBuild. The results of
the simulation are presented, discussed and evaluated.
Furthermore, some modifications are proposed in order to improve the building’s
energy behavior. The initial files which describe the building are changed and are
executed with the TRNSYS Simulation Studio. Finally, all the results are compared
and the energy savings are calculated.
The geometry details of the building, the internal partitions, material and
construction layers’ characteristics were given as input to TRNSYS, using the
AUTOCAD & TRNBuild. Seventeen thermal zones were identified.
Input of the external climatic conditions (temperature, relative humidity, air
velocity, rainfall) is given, via the closest meteo station available from the National
Meteorological Service of Greece for the area of Skiathos.
A rather simplified schedule was included for occupants in the zone (approximated
representation). Furthermore schedules of equipment use (mainly PCs) lightning
schedule, HVAC systems operation, metabolic rated of occupants and clothing
insulation were taken into account.
Annual, Mean Hour and Mean Monthly Energy demands for cooling & heating were
calculated according to the input described above. Deviation was calculated and
described per retrofit measure proposed – Low Emissivity glazing, upgrading
building’s wrapping, replacement of light bulbs and the combination of the above
measures. The measures were not assessed from a technoeconomical point of view.
110
No
6
Title:
“Parametric Identification of buildings’ Energy demands for Heating and Cooling in
various conditions using the TRNSYS simulation”
Zoi Sagia, National Technical University of Athens, presented on February 2009
Available at:
http://dspace.lib.ntua.gr/bitstream/123456789/7661/3/alexiouk_trnsys.pdf
BES
Method/To
ol Used:
Short
Description:
TRNSYS
Analysis:
The current study determines the heating and cooling demands of a multi-use
building in the centre of Athens. The calculations are made for single and double
glazing. The calculations are also repeated as if the building was situated on the city
of Rhodes and on the city of Kozani. With this procedure is assessed the impact of
climatic conditions on the heating and cooling demands of a building. What is more,
for the current stage of the building which is situated on Athens and is equipped
with double glazing two index of thermal comfort are calculated: predicted mean
vote (PMV) and predicted percentage of dissatisfied persons (PPD).
The geometry details of the building, the internal partitions, material and
construction layers’ characteristics were given as input to TRNSYS, using the
AUTOCAD & TRNBuild. Six thermal zones were identified.
Schedule was included for occupants in the zone (representation according to ISO
7730). Furthermore schedules of equipment use (mainly PCs) lightning schedule,
HVAC systems operation, as well as themal comfort indicators for winter & summer
time (clothing insulation, metabolic rate, external work and relative air velocity)
were taken into account.
Input of the external climatic conditions for Athens, Rhodes and Kozani were
provided by simulations with METEONORM software (monthly temperature of the
external climate, average diffuse-global horizontal insolation, monthly average wind
speed, and relative humidity).
Simulation has taken place for the building with single glazing & double glazing in
each area, calculating two indexes of thermal comfort: predicted mean vote (PMV)
and predicted percentage of dissatisfied persons (PPD).
In the current study no retrofit proposals are examined.
111
No
7
Title:
“Energy Study of Multi-Use Building”
Vasilikos Panagiotis, Technical Institution of Crete, presented on December 2009
Available at:
http://nefeli.lib.teicrete.gr/browse/stef/hle/2009/VasilikosPanagiotis/attacheddocument-1266921403-211853-2936/Vasilikos2009.pdf
BES
Method/To
ol Used:
Short
Description:
ESP-r
Analysis:
On the present thesis, an energy project was carried out on the town hall of the
Municipality of Gazi Heraklion Crete. Initially, all current energy consumption was
recorded, followed by a study of the external thermal insulation of the building in
order to evaluate the energy labeling of the building.
Finally, various solutions were proposed for the energy improvement of the
building, considering all the legal, financial and technological aspects presented.
The geometry details of the building, the internal partitions, material and
construction layers’ characteristics were given as input to ESP-r, taking into account
the proposed measures for energy efficiency improvement of the building.
A rather simplified schedule was included for occupants in the zone. Furthermore
schedules of equipment use (mainly PCs) lightning schedule, HVAC systems
operation were taken into account.
Input of the external climatic conditions is given, via the closest meteo station
available from the National Meteorological Service of Greece.
The results on the Annual & Mean Monthly Energy demands for cooling & heating
were compared to the actual energy demand data which were extracted from
electricity and fuel purchase invoices.
112
No
8
Title:
“Study of the Energy Behavior of a building, with Dynamic and Static Computer
softwares (KENAK, EnergyPlus)”
Giorgos Seritoglou, Aristotle University of Thessaloniki, presented on March 2012
Available at:
http://invenio.lib.auth.gr/record/128921/files/seritoglou.pdf?version%3D1?ln=es
BES
Method/To
ol Used:
Short
Description:
TEE KENAK, Energy Plus
Analysis:
TEE KENAK
- 2 thermal zones were identified
The present thesis aims to investigate and evaluate the results obtained after energy
simulation study using static and dynamic computing model. For this reason,
simulations of the same (typical) building are performed with the software TEE
KENAK and Energy Plus.
Simulations took place for the same building in Attica & Thessaloniki. The retrofit
measures proposed and investigated are thermal insulation of building elements,
frames’ change, HVAC systems replacement and the combination of these three
measures.
-
The internal partitions, material and construction layers’ characteristics
were given as input / U-values were manually introduced (the ones that
were calculated from Energy Plus, in order to enable the comparison
between the two models
-
Infiltration & ventilation input was calculated according to TOTEE-20701-1
-
Shading coefficient is manually inserted as input data
-
Annual & Mean Monthly Energy demands for cooling & heating, as well as
for hot water production were calculated for the initial stage of the building
and for every retrofit method proposed
Energy Plus
- 36 thermal zones were identified
-
The internal partitions, material and construction layers’ characteristics
were given as input / U-values were calculated by the software
-
Infiltration & ventilation input was calculated according to TOTEE-20701-1,
in order to enable the comparison between the two models
113
-
Shading coefficient is calculated within the simulation process
-
Climate data were given, via the closest meteo station available (Mikra for
Thessaloniki & Elliniko for Athens)
-
Annual & Mean Monthly Energy demands for cooling & heating, as well as
for hot water production were calculated for the initial stage of the building
and for every retrofit method proposed
Comparisons-Evaluation
Thessaloniki
-
The difference in energy consumption for heating needs annually between
the two software scenario baseline in Thessaloniki are about 17,5 kwh / m²
with the greatest value belonging to Energy Plus.
-
The difference in energy consumption for cooling needs annually between
the two software baseline scenario in the area of Thessaloniki is about 7,78
kwh / m² with the greatest value belonging to TEE KENAK.
-
The difference in energy consumption for heating needs annually between
the two software for the scenario enhancing thermal insulation of building
elements in Thessaloniki belongs in the range of 9,58 kwh / m² with the
greatest value belonging to Energy Plus.
-
The difference in energy consumption for cooling needs annually between
the two software for the scenario enhancing thermal insulation of building
elements in Thessaloniki belongs in the range of 3,98 kwh / m² with the
greatest value belonging to TEE KENAK.
-
The difference in energy consumption for heating needs annually between
the two software for the scenario of changing frames in Thessaloniki are
about 31,09 kwh / m² with the greatest value belonging to Energy Plus.
-
The difference in energy consumption for cooling needs annually between
the two software for the scenario of changing frames in Thessaloniki are
about 5,12 kwh / m² with the greatest value belonging to TEE KENAK.
-
The difference in energy consumption for heating needs annually between
the two software for the scenario of changing HVAC systems in the region of
Thessaloniki in the range of 12,2 kwh / m² with the greatest value belonging
to Energy Plus
114
-
The difference in energy consumption for cooling needs annually between
the two software for the scenario of changing HVAC systems in the region of
Thessaloniki in the range of 5,22 kwh / m² with the greatest value belonging
to TEE KENAK.
-
The difference in energy consumption for heating needs annually between
the two software for the combined scenario in Thessaloniki are about 11,72
kwh / m² with the greatest value belonging to Energy Plus.
-
The difference in energy consumption for cooling needs annually between
the two software for the combined scenario in Thessaloniki are about 1,25
kwh / m² with the greatest value belonging to TEE KENAK.
Attica
-
The difference in energy consumption for heating needs annually between
the two software scenario baseline in Athens are about 31,02 kwh / m² with
the greatest value belonging to Energy Plus.
-
The difference in energy consumption for cooling needs annually between
the two software baseline scenario in the area of Athens is about 5,2 kwh /
m² with the greatest value belonging to TEE KENAK.
-
The difference in energy consumption for heating needs annually between
the two software for the scenario enhancing thermal insulation of building
elements in Athens belongs in the range of 14,74 kwh / m² with the greatest
value belonging to Energy Plus.
-
The difference in energy consumption for cooling needs annually between
the two software for the scenario enhancing thermal insulation of building
elements in Athens belongs in the range of 4,09kwh / m² with the greatest
value belonging to TEE KENAK.
-
The difference in energy consumption for heating needs annually between
the two software for the scenario of changing frames in Athens are about
26,6 kwh / m² with the greatest value belonging to Energy Plus.
-
The difference in energy consumption for cooling needs annually between
the two software for the scenario of changing frames in Athens are about
3,31 kwh / m² with the greatest value belonging to TEE KENAK.
-
The difference in energy consumption for heating needs annually between
115
the two software for the scenario of changing HVAC systems in the region of
Athens in the range of 22,11 kwh / m² with the greatest value belonging to
Energy Plus
-
The difference in energy consumption for cooling needs annually between
the two software for the scenario of changing HVAC systems in the region of
Athens in the range of 4,47 kwh / m² with the greatest value belonging to
TEE KENAK.
-
The difference in energy consumption for heating needs annually between
the two software for the combined scenario in Athens are about 6,05 kwh /
m² with the greatest value belonging to Energy Plus.
-
The difference in energy consumption for cooling needs annually between
the two software for the combined scenario in Athens are about 0,94 kwh /
m² with the greatest value belonging to TEE KENAK.
o
These differences were expected; the dynamic simulation model Energy Plus
program uses sophisticated algorithms for calculations of dynamic,
interactive and nonlinear phenomena thermal equilibrium in contrast to the
static model of computation software TEE KENAK.
o
Another factor which may explain the discrepancies between the results of
the two programs is the climatic data used to function. The used climate
records from different climatic data bases and may diverge climatic data
required to perform the simulation.
o
Also one more element that causes discrepancies is the different treatment
of internal heat gains of both softwares.
o
The difference in the shading coefficient calculation and stage of insertion is
a core factor of the differences observed between the two methods’ results.
o
Net present value was used for the technoeconomic evaluation of the
scenarios, resulting into the HVAC change solution as the only financially
viable retrofit.
116
Open Spaces
No
1
Title:
“Bioclimatic Approach of Urban Spaces, the cases of Kotzia and Dikaiosinis
Squares.”
Patounis Charalambos, Simos Nikolaos, National Technical University of Athens,
presented on October 2012
Available at: http://www.greekarchitects.gr/site_parts/doc_files/Patounis-Simos.pdf
Method/To
ol Used:
Short
Description:
ENVI-met
Analysis:
During the last years, bioclimatic design emerges as a promising solution for the
ever-growing demand to improve living conditions in the cities. This trend
dominated the urban areas design principles and particularly the squares, which
form places of transit of thousands of people on a daily basis. The regeneration of
these areas can be realized using various methods, including the placement of
appropriate materials, the planting vegetation etc. In recent years computational
fluid dynamics programs have been utilized, providing an asset for the best possible
reform of open outdoor spaces. Such programs offer the possibility to simulate
microclimate of an area, offering important data for the study.
The purpose of this thesis is to evaluate the reliability and accuracy of Envi-met, a
widespread program of this kind, by comparing its results with actual
measurements. For this reason a study was conducted in two squares of central
Athens, namely Kotzia square and Dikeosynis square under two main axes. Real
measurements of temperature and relative humidity for specific days and hours
took place and were complemented by simulations using Envi-met. It should be
noted that the measurement results have been visualised in the form of isotherms
with special program. Finally, a proposal concerning the regeneration of Dikeosynis
square was evaluated using Envi-met.
Measurements
Air temperature & relevant humidity measurements (1,50m over the ground) took
place, in 4 different time-basis during the day (07:00, 14:00, 18:30, 21:30). The
results were presented in equithermal & relative humidity curves, with the use of
ThanCad, a software produced by Dr. Athanasios Stamos.
Solid surfaces temperature was measured (21 measurement spots) with the use of
thermal camera.
Simulations
The input data were: Wind speed at 10m above the ground (m/s), Wind direction,
117
Initial temperature, Relative humidity at 2m, humidity at 2500m (g water / kg air),
General conclusions are presented here:
-
External heat sources significantly affect the microclimate of the squares
-
The presence of water and planting provide appreciable temperature
differences
-
The simulations that took place show that the results
provided are very close to the results of the measurement on the facade of
buildings.
The
differences can be attributed to the fact that the simulations and
measurements concerned a height of 1.50m from the ground.
-
Buildings with large glass surfaces and older buildings seem to develop
higher temperatures on the facades , thus influencing the microclimate of
the squares
Based on the above observations the ENVIMET is, at least in the range of the results,
quite reliable and valid especially in the midday and afternoon hours of the day.
Equithermal curves from ENVIMET do not correspond to the actual state but relative
humidity curves can be considered approximately acceptable.
118
No
2
Title:
“Bioclimatic Design & Environmental Comfort in Urban Areas- simulation with
ENVI-met software”
Papoutsis Dimitrios, National Technical University of Athens, presented on March
2012
Available at:
http://dspace.lib.ntua.gr/bitstream/123456789/5916/3/papoutsisd_microclimate.p
df
Method/To
ol Used:
Short
Description:
Analysis:
ENVI-met
The purpose of this thesis is to present the principles of bioclimatic design in urban
open spaces, as well as the detailed presentation of the computational fluid
dynamics software ENVI-met. This was used to study the current situation and to
evaluate the proposal for the regeneration of the central squares in the Polytechnic
University of Athens in Zografou area, submitted by the technical department of the
university. In the simulations, real climatic data were used and their results were
evaluated in order to test the reliability and the precision of the program.
The aim was the evaluation of the proposal for the regeneration of the central
squares in the Polytechnic University of Athens in Zografou area, submitted by the
technical department of the university under the Operational Programme Environment and Sustainable Development. Under this OP, it was the first time that
the use of innovative tools for the simulation and quantification of thermal comfort
indicators for the “users” was introduced as a pre-requisite for the sufficient
evaluation of the proposals for funding.
The retrofit measures proposed resulted, according to the results of ENVI-met, to:
-
The reduction of the average maximum air temperature during summer
period concerning a height of 1.80m from the ground at 1,57 0C
-
19,21 % improvement of CP before and after the retrofit (for hours 10:0018:00)
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4. Conclusions
The current report provides a strong feedback that the majority of the innovative tools identified, are
not used in retrofit projects but only in research base.
This can be attributed to a number of reasons:
-
Although many of the tools identified are widely available (commercial proprietary or free
software), their use often requires high computer literacy and advanced experience of the
user
-
The majority of the tools do not operate in user-friendly environment. Many professionals
consider most computational tools complex and not user friendly, as well as time consuming.
-
The professionals use mainly the national Methodology and relevant tools for buildings.
Regarding open spaces there is no regulation available to push the professional towards the
use of available simulation tools and the effect of microclimate factors in the bioclimatic
design.
Only in the case of ENVI-met use for the study “Bioclimatic Design & Environmental Comfort
in Urban Areas- simulation with ENVI-met software” the software was actually used for the
study of the current situation and the outcome of the retrofit measures. The aim was the
evaluation of the proposal for the regeneration of the central squares in the Polytechnic
University of Athens in Zografou area, submitted by the technical department of the
university under the Operational Programme - Environment and Sustainable Development.
Under this OP, it was the first time that the use of innovative tools for the simulation and
quantification of thermal comfort indicators for the “users” was introduced as a pre-requisite
for the sufficient evaluation of the proposals for funding.
-
Resistance to change: The professionals are not always flexible in using new approaches and
are strongly engaged to ways of dealing with design practices they already know and they
spend no time to get familiarized with novel methods.
The innovative methods and tools presented in this review are innovative from the technical
point of view; they which could be complementary applied to the already applicable national
ones, tackling the fact that in some cases crucial physical aspects are ignored, such as the impact
of urban heat island effect and of occupants’ behavioural patterns on building energy
consumption, and providing adequately and cost-effectively (reasonable simulations’ time)
results.
120
5. References
-
Attia, S. 2011. State of the Art of Existing Early Design Simulation Tools for Net Zero Energy Buildings: A
Comparison of Ten Tools, Technical Report, Architecture et Climat, Louvain La Neuve: Université
catholique de Louvain. Available at:
http://wwwclimat.arch.ucl.ac.be/s_attia/attia_nzeb_tools_report.pdf
-
US Department of Energy – Office of Energy Efficiency and Renewable Energy website:
http://energy.gov/eere/office-energy-efficiency-renewable-energy
-
http://usa.autodesk.com/ecotect-analysis
-
http://www.energyplus.gov
-
http://pages.suddenlink.net/enerwin/
-
http://sel.me.wisc.edu/trnsys/
-
http://www.envi-met.com/
121
Annex 2: Review of innovative methods for retrofitting
purposes - France
Contribution to Deliverable D.3.3
Component 3- Analysis-desk research
Phase 3.3 - Analysis of innovative retrofitting methods applied in the technoeconomical study stage
Contract No.: 1C-MED12-73
Axe2: Protection of the environment and promotion of a sustainable territorial
development
Objective 2.2:
efficiency
Promotion and renewable energy and improvement of energy
Authors: Georges Seliniotakis - NCA city partner, Mathieu Thorel - CSTB technical
partner of NCA
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Buildings: Definition of technical innovative methods
In the REPUBLIC-MED project the term “innovative methods” (from the technical point of view)
represents methods that could be complementary applied to the already applicable national ones
providing effective and reliable (with reasonable computational burden) results and deal with the
following issues:

Impact of external microclimate on indoor energy consumption: The energy simulation
approach takes into account climatic conditions within the building surrounding, instead of
using climatic data of the wider climate zone. For example, such information may be
emanated from Computational Fluid Dynamics (CFD) [1] simulations to capture the external
microclimate of the site the building belongs to. The microclimate models are expected to
account for the physical effects of the site.

Impact of occupants’ behavior patterns on energy consumption: The energy simulation
approach takes into account operation schedules of the most important systems of the
building.

Adequate representation of retrofitting measures (i.e. accurate prediction of their impact),
such as building integrated RES technologies, GHP, planted roofs and walls, insulation,
effects of roofs and walls with cool coatings, etc.
Guidelines for the review process
Keywords and key-phrases
Microclimatic effects on building energy consumption; Computational Fluid Dynamics (CFD)
prediction of microclimate; Building Energy Simulation (BES) tools to predict building energy
consumption; Coupled CFD/BES simulations; Impact of occupancy behavioral patterns on building
energy consumption; etc.
Clarification of methods reviewing and classification
The computational tools used in the studies are expected to be also reported, i.e.:
 Specification of the BES tools used in the studies, e.g. TRNSYS, Energy Plus, DOE-2, etc.
 Specification of the CFD tools used in the studies, e.g. Fluent, CFX, Envi-met, etc.
123
The tools used to perform simulations in the studies are expected to be classified as follows:
 BES tools that provide access to the climate data input fields
 BES tools that provide access to the systems’ operation schedules
 BES tools that may be used for impact assessment only
 BES tools that can be used for impact assessment and design optimization
 CFD (or other field modeling) tools that provide fast calculations
 BES tools that provide fast calculations
 CFD and BES tools most commonly used for CFD/BES coupled simulations
Content expected
The outcomes of the review analysis will include the following:
4.1) D.3.3- Review of innovative methods for retrofitting purposes:





List of appropriate zonal (BES) and field (e.g. CFD, UCM, etc.) tools to perform coupled
simulations
Methods to couple zonal and field modeling tools
Methods to account for behavioral patterns
Applications of CFD/BES to recommend optimal retrofitting measures
Reasons that innovative methods are not applied in the techno-economical design stagebarriers.
Review of innovative methods for retrofitting purposes
Building Energy Simulation (BES) tools are broadly used by building designers. They can be employed
to model and to assess technical choices for new buildings, but also to test and to find effective and
reliable retrofitting scenarios for existing constructions. BES tools can be distributed by commercial
companies or emanate from scientific researches. According to the specifications and precision of
results wished, different types of tools can be used [2-4].
Simulation tools: range of application
In practice, simulation tools can be utilized for the following functions [5]:
-
To evaluate design options and investigate design optimization.
To facilitate the investigation of new ideas (cognitive).
To check compliance with building energy codes.
To perform cost benefit analyses.
124
Even if most tools compute annual energy balance (heating, cooling, and DHW annual needs and
consumptions) others are specialized in different uses with a part of energy calculation such as
Lighting and day-lighting simulations (RADIANCE, SUPERLITE, CARNAVAL), solar system simulation
(SIMBAD, TRANSOL), technical maintenance (EPIQR) and environmental LCA (ELODIE, EQUER).
However in this study, only BES innovative tools will be reviewed in detail.
Presentation of some BES tools analyzed
For the past 50 years, a wide variety of building energy simulation programs have been developed,
enhanced, and are in use throughout the building energy community. Among the major BES programs
used in France by building designers, we can mention: EnergyPlus, TRNSYS 17, Pléiades-Comfie,
Climawin, PHPP, design builder.
Two main types of models cohabit: “full models” solving physical equations at hourly time step (using
different mathematical approaches: finite difference, transfers functions), “reduced models” solving
simplified equations (electrical analogy, gains-losses models) with static or dynamic behavior.
The present study aims to present some of them then try to give a comparative analysis of broader
set of listed tools, according different features judged as important for designers and building
researchers.
ArchiWIZARD
Thermal calculation software performs hourly simulations of buildings to provide mechanical, energy,
and architectural engineers or architects with accurate estimates of a building's energy needs and
input and output data structures tailored to facilitate architects', engineers', and design department
work.
ArchiWIZARD provides accurate solar and
lighting calculations and mapping on 3-D
graphics interface (solar mapping and heat
improvement, solar energy reception with
sensors, solar factor calculation and occultation
performance evaluation, and mapping
calculation of natural and artificial lighting).
ArchiWIZARD integrates all the
recommendations of French thermal regulations
and European standards (EN12831, EN13790…)
and determines compliance with French building
thermal regulations RT2012 (national thermal
Figure 1 - ArchiWIZARD environment
125
regulation derived from EPBD 2010 [6]) with an
additional plugin.
Strengths
User-friendly graphical interface that gives energy and light ray-tracing results in real-time.
Weaknesses
Not advanced research tool.
DesignBuilder v3.4
User-friendly modeling environment, it provides a
range of environmental performance data such as:
energy consumptions, internal comfort data,
daylighting. Output is based on detailed sub-hourly
simulation time steps using the EnergyPlus simulation
engine. DesignBuilder can be used for simulations of
many common HVAC types, naturally ventilated
buildings, buildings with daylighting control, double
facades, advanced solar shading strategies etc. A
module version can perform CFD calculations.
Figure 2 - DesignBuilder CFD interface
Strengths
EnergyPlus engine, 3D modeler
DOE-2
Developed by J. Hirsch & Lawrence Berkeley National Laboratory (LBNL), this free BES tool uses
“batch” program which requires substantial experience to learn to use effectively while offering
researchers and experts significant flexibility. Two graphical user interfaces exist: eQUEST (free
software) and PowerDOE (commercial product). Using hourly time step to simulate a full year, this
energy program computes: heat and cooling needs and consumptions, ventilation, pumps and
lighting consumptions, photovoltaic production and proposes a life-cycle cost of different scenarios
tested. Other uses include utility demand-side management and rebate programs, development and
implementation of energy efficiency standards and compliance certification.
Strengths
Detailed, hourly, whole-building energy analysis of multiple zones in buildings of complex design;
widely recognized as the industry standard.
126
Weaknesses
High level of user knowledge demanded.
Ecotect
Dedicated to architects, this BES tool integrates a 3D modeler and assesses different aspects
(daylighting, thermal, acoustic and costs) of early-stage design phase of buildings creation. Graphical
outputs are numerous. Ecotect is a program from Autodesk Company. This tool may be connected to
many advanced programs in order to import 3D models (3D studio, AutoCAD, EnergyPlus) or to
export pre-computed data (DOE-2, ESP-r, Radiance, EnergyPlus…) [7]. Simplified GIBSE admittance
method is used to perform thermal and solar calculation [8, 9].
Strengths
Friendly graphical user interface, optimized to early-stage design phases, numerous data format
exports
Weaknesses
Simplified GIBSE method, few HVAC systems modeled
EnergyPlus
EnergyPlus is a dynamic simulation tool that engineers, architects, and researchers use to model
energy and water needs in buildings. It uses model libraries of building components and physical
phenomena. Two types of mathematical model can be used by library components: transfer functions
and finite differences. It enables building professionals to optimize the building design to use less
energy and water.
This program models heating, cooling, lighting, ventilation, other energy flows, and water
consumptions including many innovative simulation capabilities such as: time-steps less than an hour,
modular systems and plant integrated with heat balance-based zone simulation, multizone air flow,
thermal comfort, water use, natural ventilation, and photovoltaic systems. More recent versions can
also compute atmospheric pollution calculations (CO2, SOx, NOx, CO, particulate matter).
Strengths
-
Importation of building 3D model from SketchUp
Precise, detailed simulation capabilities through complex modeling capabilities;
Parametric and optimization studies are possible
127
Weaknesses
-
The Graphic User Interface (GUI) is not friendly: command line interface
ESP-r
ESP-r is an open-sources BES tool created by University of Strathclyde (UK). It is primarily used in
research, as a tool for consultants or as a teaching tool. ESP-r can model the thermal, visual and
acoustic performance of a building as well as to estimate the heat, moisture and electrical power of
the modeled building. ESP-r calculates building performance values based on a finite volume
approach where it solves a set of conservation equations.
Strengths
ESP-r is flexible and powerful enough to simulate many innovative or leading edge technologies
including daylight utilization, natural ventilation, combined heat and electrical power generation and
photovoltaic facades, CFD, multi-gridding, and control systems.
Weaknesses
It is a general purpose tool and the extent of the options and level of detail slows the learning
process. Specialist features require knowledge of the particular subject. Graphical user interface is
aging.
Figure 3 - Graphical User Interface (GUI) of ESP-r BES tool
IES Virtual Environment (IES VE)
IES-VE consists of a suite of integrated analysis tools, which can be used to investigate the
performance of a building either retrospectively or during the design stages of a construction project.
128
Whether working on a new build or renovation project, this virtual environment allows designers to
test different options, to identify best passive solutions, to compare low-carbon & renewable
technologies, and to draw conclusions on energy use, CO2 emissions, occupant comfort, above
others. The software includes a module called “Radiance” that looks at the viability of day-lighting
and a module called “MacroFlo” that investigates the effectiveness of natural ventilation (CFD
program). Most commonly used is the "Apache" thermal analysis module, which provides either
steady-state or dynamic analysis of energy consumption and indoor thermal conditions. Extensive
databases (including pre-defined HVAC component libraries and Manufacturer tools) are integrated in
the tool.
Geometrical building data may be imported from a range of CAD/BIM136 systems. And software
outputs may take different forms such as: tabular, graphical, video and photorealistic images.
Figure 4 - Graphical User Interface of IES VE
Figure 5 - IES VE possible output of daylight
calculation
Strengths
-
-
Comprehensive analysis options offered across a wide range of metrics
Simulation results are linked between modules; including across component HVAC system
modeling, natural ventilation modeling, CFD analysis, daylight compensation control, solar
shading analysis, cost and value assessment
Integrated data model means that design modifications are immediately updated elsewhere
PHPP
PHPP calculates energy demand for buildings. It is compatible with international norms (ISO 13790). It
is especially adapted to high-performance buildings and can be used to prove Passive House
requirements. HVAC and DHW consumptions are computed as well as: summer comfort indicator and
CO2 emissions related to energy consumptions. This tool is broadly used around the world by
136
BIM : Building information modeling Bu
129
architects, engineers and scientists. Calculations are done through dynamic macro-embedded Excel
spreadsheets.
Strengths
Energy design and thermal comfort for high performance buildings, esp. passive houses
Weaknesses
Monthly energy balance method.
PLEIADES+COMFIE
Pléiades+COMFIE is a French dynamic simulation tool, developed by IZUBA energies. Used by
architects and building engineers, this tool allows computing parametric studies at different time step
(from 6 to 30 minutes) that give with accurate results: energy needs (heating, cooling, DHW, lighting)
and temperature profiles for made to measure periods (from week to year).
The zone models of COMFIE are based upon a finite volume method on which a modal reduction
technique is applied. The output comprises the yearly and hourly heating loads, hourly and mean
temperatures in the thermal zones. COMFIE building model is also coupled to additional modules (PV
generation, earth tube). Graphs and histograms may be obtained from PLEIADES, the user-friendly
interface of COMFIE. Pleiades-COMFIE integrates also two modules: ALCYONE and METEOCAL. First
one is used to import or to design a 3D zonal model, second help to adapt or to build compatible
meteorological files.
Strengths
COMFIE has a user-friendly interface; dynamic
simulation allows for analysis of thermal comfort
(especially summer comfort) and passive solar
structures; focusing on the envelope allows for
use by architects; COMFIE is also linked to a life
cycle assessment software (EQUER) allowing
environmental evaluation of the building.
Weaknesses
Equipment is modeled very simply (maximum
power, set point, position of the thermostat in
the building). Moisture is not accounted for.
Figure 6 - Solar masks definition with of Pleiades+COMFIE
130
TRaNsient SYstem Simulation Program (TRNSYS 17)
TRNSYS is an energy simulation program whose modular
system approach makes it one of the most flexible tools
available. It includes a graphical interface, a simulation
engine, and a library of components that range from various
building models to standard HVAC equipment to renewable
energy and emerging technologies. This simulation is used
for analysis and sizing, multizone airflow analyses, electric
power simulation, solar design, building thermal
performance, analysis of control schemes. TRNSYS is an
energy simulation program whose modular system
approach makes it one of the most flexible tools available. It
includes a graphical interface, a simulation engine, and a
library of components that range from various building
models to standard HVAC equipment to renewable energy
and emerging technologies. This simulation is used for
analysis and sizing, multizone airflow analyses, electric
power simulation, solar design, building thermal
performance, analysis of control schemes.
Strengths
Due to its modular approach, TRNSYS is extremely flexible
for modeling a variety of energy systems in differing levels
of complexity. Supplied source code and documentation
provide an easy method for users to modify or add
components not in the standard library; supplied time step,
starting and stopping times allowing choice of modeling
periods.
Figure 7 - TRNSYS environment
TRNSYS also interfaces with various other simulation
137
packages such as COMIS, CONTAM, EES, Excel, FLUENT ,
138
GenOpt and MATLAB.
Weaknesses
No assumptions about the building or system are made (although default information is provided) so the user
must have detailed information about the building and system and enter this information into the TRNSYS
interface.
Comparative synthesis of BES tools
See comparative analysis in the end of the document. Annex part.
137
Flow modeling simulation software using CFD
138
GenOpt is an optimisation program for the minimization of a cost function that is evaluated by an
external simulation program.
131
Limitations of BES tools
Using BES programs for building design has its limitations. Existing models fail to tackle issue
regarding data preparation in the face of uncertainty in the design environment. Mathews and
Richards [10] have commented that the programs available are far from ideal. Current limitations of
BES tools include [5]:
-
The program input is voluminous and scientifically detailed. Data, which is usually unavailable during
early design stages, has to be assumed when doing the analysis.
Program output consists of bulky computer printouts that confuse the user. Understanding and
interpretation of the simulation results is difficult.
Many detailed design tools are research orientated. Learning to use them is difficult and a long time is
required to become competent.
The software does not allow users the flexibility to do any programming easily to meet particular
needs.
Lacks the ability to truly model several newer concepts, such as under-floor air distribution.
Differences between measured and simulated building energy performance are often caused by
limitations of BES models and availability of required data. These limitations can be documented with
simulation approximations, assumptions, and simplifications [11, 12]. In other words, the three
fundamental limitations of BES are the quality of input data, the shortcomings of the particular use of
simulation concepts, and the shortcomings of system and component models embedded.
132
References
1.
Stavrakakis, G.M., et al., A computational methodology for effective bioclimatic-design
applications in the urban environment. Sustainable Cities and Society, 2012. 4(0): p. 41-57.
2.
Brun, A., et al., Behavioural comparison of some predictive tools used in a low-energy
building, in Eleventh International IBPSA Conference. 2009: Glasgow, Scotland.
3.
Peuportier, B., TREES : Training forRenovated EnergyEfficient Social housing - Section 2 Tools :
2.2 thermal simulation, c.E.S. IntelligentEnergy-Europe programme, Editor. 2007, Armines.
EERE, Building Energy Software Tools Directory. 2011, US Department of energy.
4.
5.
Hui, S.C.M., Simulation based design tools for energy efficient buildings in Hong Kong. Hong
Kong Papers in Design and Development, 1998. 1: p. 40-46.
6.
EPBD, Directive 2010/31/EU of the european parliament and of the council of 19 may 2010 on
the energy performance of building (recast). 2010, Official Journal of the European Union.
7.
I3ER. Ecotect. 2007; Available from: http://logiciels.i3er.org/ecotect.html.
8.
Beattie, K.H. and I.C. Ward. The advantages of building simulation for building design
engineers. in Conference of International Building Performance Simulation Association. 1999.
9.
Strathclyde. Estimating Summertime Temperatures in Buildings: The CIBSE Method. Available
from:
http://www.esru.strath.ac.uk/Reference/concepts/cibse_sum_temp/cibse_sum_temp.htm.
10.
Mathews, E.H. and P.G. Richards, An efficient tool for future building design. Building and
Environment, 1993. 28(4): p. 409-417.
11.
Maile, T., et al., Formalizing approximations, assumptions, and simplifications to document
limitations in building energy performance simulation, in CIFE Working Paper #WP126. 2010:
Standford University.
12.
Maile, T., M. Fischer, and V. Bazjanac, Building energy performance simulation tools-a lifecycle and interoperable perspective, in Working Paper #107, C.f.I.F. Engineering, Editor. 2007:
Stanford University.
133
Open spaces: Definition of technical innovative methods
In the REPUBLIC-MED project the term “innovative methods” (from the technical point of view)
represents methods that could be complementary applied to the already applicable national ones
providing adequately and cost-effectively (reasonable simulations’ time) results and deal with the
following issues:

Prediction of the airflow pattern by applying field models, such as Computational Fluid
Dynamics (CFD) or Urban Canopy Models (UCM) or other, that provide the distributions
(contours, iso-surfaces) of temperature, wind speed, relative humidity, turbulence intensity,
pollutant concentration etc.

Field models, such as CFD models, that account for important physical effects emanated
from space attributes, such as evaporation from water surfaces, evapotranspiration from
trees and vegetation, solar irradiance absorption and reflection from solid surfaces,
Atmospheric Boundary Layer (ABL) [1] assumptions to represent incoming wind, etc. Other
physical effects representing anthropogenic heat and pollutant sources may be also included
in the assessments, such as vehicles’ exhausts of heat and pollutants.
Guidelines for the review process
Keywords and key-phrases
Microclimate simulations; Computational Fluid Dynamics (CFD) prediction of microclimate; CFD
simulations urban spaces; Predictions of microclimate and environmental conditions in the urban
environment; Bioclimatic interventions for pedestrian comfort and health; Mitigation of the Urban
Heat Island (UHI) effect (using CFD); etc.
Clarification of methods
The computational tools used in the studies are expected to be also reported, i.e.:
 Specification of the CFD tools used in the studies, e.g. Fluent, CFX, Envi-met, etc.
 Other field models.
The tools used to perform simulations in the studies are expected to be classified as follows:
 Field modeling tools that solve for heat transfer mechanisms, mass and momentum
conservation, turbulence flow and chemical species concentration
 CFD tools that solve for special urban physics features, such as evaporation and
evapotranspiration.
 Field models that provide comfort and air quality indicators’ calculations (such as PMV, SET*,
CO2 concentration at the pedestrian level height, etc.)
 Tools that provide fast calculations
134
Content expected
The outcomes of the review analysis will include the following:
4.1) D.3.3- Review of innovative methods for retrofitting purposes:



List of appropriate field models to perform microclimate simulations in open public spaces
Application of CFD to recommend optimal retrofitting measures
Reasons that innovative methods are not applied in the techno-economical design stagebarriers.
Assessment criteria
Thermal indices
According to scientific literature, most assessed indicators in urban open spaces studies are thermal
comfort indices. These indices, computed either by scientific methods or commercial programs, can
be classified in the following four groups [2, 3]:




Empirical thermal indexes correlating only a few climatic parameters and usually elaborated for
specific climates, such as the wind chill Index and discomfort index
Psycho-sociological-climatic indexes, correlating subjective perception (e.g., actual sensation vote,
satisfaction indexes) of microclimatic variables and comfort index (Nikolopoulou et al. 2001)
Energy balance equation indexes based on a two-node model of the human body and on the
assessment of all relevant thermal climatic parameters, coupling the heat balance equation with a
simplified model to evaluate Mean Radiant Temperature (Hoppe 1999)
Energy balance equation based on a one-node model of the human body: perceived temperature (PT)
model based on Fanger’s (1972) equation plus an outdoor radiant evaluation model (Jendritzki et al.
1990): PVM index and COMfort FormulA-COMFA+ (Brown and Gillespie 1986; Dessì 2007) with a
simplified radiant evaluation model
Others indices
In scientific literature, only aspects related to human hygrothermal comfort are broadly developed.
Some models integrate also air pollutant dispersions such as ENVI-met.
Review of innovative methods for retrofitting purposes
Most of researches tools and commercial software concerning energy refurbishment focus on indoor
spaces. However, there are some innovative programs analyzing different performance indicators
135
(such as the thermal comfort or temperature profiles) in urban open spaces that require the
consideration of factors, as solar radiation, winds, and different activities, among others.
The urban environment is an important component of daily life. That explains the interest in methods
for assessing the quality of open spaces concerning their contribution to the quality of urban life. A
wide range of studies ranging from field experiments up to the application of numerical models have
been conducted in order to understand and predict the interactions between the urban design, local
microclimate and human comfort.
The present document focuses the main programs identified, including TownScope, CONFORT-EX,
ENVI-met, OTC Model, SOLWEIG, BioKlima and OUTCOMES [4]. This list is far from an exhaustive
scientific review but gives hints on major specific methods and tools used to assess performance
indicators concerning energy on urban open spaces.
Presentation of some microclimate simulations tools analyzed
BioKlima
Developed Stanisław Leszczycki Institute of Geography and Spatial Organization (Polish Academy of
Sciences), BioKlima is polish software which gathers different methods of bioclimatic studies. This tool
allows computing indicators such as: mean radian temperature, thermal comfort indices (UTCI139,
ECI140, PMV141). According to Krzysztof Błażejczyk, his creator, BioKlima can be used for various
purposes:
-
general evaluation of bioclimatic conditions (based on mean values of meteorological elements);
detail analysis of bioclimatic conditions (based on daily meteorological data);
general evaluation of the human heat balance;
detail analysis of the human heat balance in different environmental conditions;
Strengths
Weaknesses
Very little information is available in English on this tool and physical models used
139
UTCI: Universal Thermal Climate Index
ECI: Enthampy Comfort Index
141
PMV: Predicted Mean Vote
140
136
CONFORT -EX
This tool pretends to assist architects, landscape designers and urban planners in the microclimatic
design of outdoor spaces determining the correct strategy to follow in specific climate conditions. It
also helps to evaluate the thermal comfort sensation and to make pertinent corrections if necessary.
Thermal comfort evaluation is based on the COMFA method, developed by Brown & Gillespie [5],
modified by Ochoa [6], which provides a simplified thermal comfort index.
COMFORT-EX has three components. Each of them corresponds to one stage of the design process.
The Diagnosis part analyses
Component 1: Diagnosis: It is the analysis of
the bioclimatic needed for each site. There are
two ways to enter the information: (1) by
selecting climatic data of a specific city, (2) by
entering climatic monthly average data or
pasting a text file, containing hourly data of an
average day of each month for any location.
The required parameters are: air temperature
(Celsius degrees), relative humidity (%),
horizontal solar global radiation (W/m2), and
wind speed (m/s).
Component 2: Design Guidelines: Depending
on the diagnosis, in this section it is possible to
determine a design strategy aimed to control
microclimatic parameters.
Figure 8: Screen showing the data entries for evaluation
component
Component 3: Evaluation: This component of the program allows evaluating the thermal comfort
sensation in a selected place, when the design strategies have been applied. It will help the user to
decide if the comfort conditions are acceptable
The output computed is in a standard text file format, which can be plotted with any spreadsheet
software
Strengths
Few parameters are required, tool for the people that have no expertise in energy issues
Weaknesses
Simplified approach, graphical user interface is pretty old
137
ENVI-met ®
ENVI-met is a three-dimensional microclimate model designed to simulate the surface-plant-air
interactions in urban environment. Some of typical areas of application are urban climatology,
architecture, building design or environmental planning. Developed by Michael Bruse and his team,
ENVI-met is a prognostic model based on the fundamental laws of fluid dynamics and thermodynamics [7, 8]. The model includes the simulation of:
-
Flow around and between buildings
Exchange processes of heat and vapour at the ground surface and at walls
Turbulence
Exchange at vegetation and vegetation parameters
Bioclimatology
Pollutant dispersion
ENVI-met can simulate the surface-plant-air interactions in urban environment with a typical
resolution of 0.5 to 10 m in space and 10 sec in time. It calculates the dynamics of microclimate
during a diurnal cycle (24 to 48 hours). Outputs are: PMV-Value, mean radiant temperature,
dispersion of inert gases and particles including sedimentation of particles at leafs and surfaces [9].
ENVI-met is a Freeware program based on different scientific research projects and is therefore under
constant development. ENVI-met is NOT Open Source [7].
Strengths
Broadly used in scientific research projects, a community exists around this tool
Figure 9 - Basic data structure of ENVI-met from [10]
138
OTC Model ®
OTC Model (Outdoor Thermal Comfort Model) was
developed for modeling urban climate such as
solar flux, mean radiant temperature, surface
temperature, urban wind flow, thermal comfort
indices. These latter are calculated to assess the
relationship between meteorological,
environmental and personal variables, and also to
study how this relationship affects human health
and activities. Results of analyses are presented in
a graphical format for easy interpretation. [4]
Strengths
Weaknesses
Few information is available on this tool and
physical models used
Figure 10: Mean Daily Mean Radiant Temperature, Tmrt
(°C) 1977 , Göteborg, Sweden
OUTCOMES
The program, OUTCOMES (OUTdoor COMfort Expert
System) developed by USDA Forest Service, is a program
that was written with the goal of providing an easy to
use interface and ample on-screen help. OUTCOMES
shows the shade pattern of a tree and calculates a
human comfort index considering the full range of
weather variables, the density of a tree that shades a
person, and other features of the surrounding
neighborhood.
For advanced users, a "batch" version of OUTCOMES that
can input a file with weather data (TMY format) for any
number of times and predict comfort at one location for
all of the times with a single run of the program [11].
Strengths
Integrate tree shades in thermal comfort model
Weaknesses
Very little information is available
139
RayMan
RayMan (RAdiation on the huMAN body) is software based on radiative model (solar radiation flux).
Rayman model takes into account meteorological parameters such as air temperature and air
humidity, degree of cloud cover, air transparency and time of the day of the year [12] but also
geometrical data from urban area simulated (surrounding buildings, deciduous and coniferous tree).
Outputs calculated are mean radiant temperature profiles and thermal indices in simple and complex
environments (PMV, PET) [13]. This tool is developed by professor Matzaraki working for the Meteorological
Institute of University Freiburg [13, 14].
Figure 11: Starting window in RayMan 1.2
Figure 12: Output of graphs
SOLWEIG-model
The SOLWEIG-model (Solar LongWave Environmental Irrandiance Geometry Model), developed by
the Göteborg Urban Climate Group, simulates spatial variations of mean radiant temperature and 3D
fluxes of long-wave and short-wave radiation in complex urban settings. The SOLWEIG model can be
applied for the following targets [15]:
-
Climate estimations (shadow pattern, radiation fluxes, mean radiant temperature) in urban settings;
Analyze the interaction between urban design and thermal environment ;
Creation of thermal comfort maps.
Weaknesses
140
Little information is available on this tool and physical models used, input file format are DSM 2.5D
model files (no 3D models supported)
TownScope
This tool, developed by the LEMA (University of Liege) during the European POLIS project, proposes
services to architectural and environmental agencies in charge of the assessment of the impact of
new developments on urban microclimate, landscape and energy. TownScope is a multi-disciplinary
consultancy dedicated to urban design. Through its graphical interface and interactive analysis
modules, different outputs for one given project can be realized such as assessment of direct diffused
and reflected solar radiation, calculation of human thermal comfort in urban open spaces, critical
wind discomfort risk, opacity and daylight shadings rendering. Either simplified modules based on the
GANDMER method [16] or detailed module using CDF are available. The software provides an
integrated multi-criteria decision module to rank various alternative proposals (PROMETHEE
algorithm) [16] and may produce Preformatted reports and visualizations (perspective & spherical
projections) and synthetic graphics (stereographical projections, etc.).
Strengths
Preliminary urban design studies, early decision-making,
geometrical analyses, no training needed to handle the tool.
Weaknesses
Dimensioning, optimization or detailed simulations are not
afforded by the software[17].
Urbawind
Urbawind is a CFD software for wind modeling in urban areas, or any built environments. This
commercial program is composed of three modules [18]:
-
outdoor pedestrian comfort module: to determine the areas of possible wind discomfort to make
outdoor spaces more pleasant and safer for its users;
Natural Ventilation module: It estimates and optimizes natural ventilation of buildings and evaluates
the indoor comfort and air quality;
Energy module: assessing the potential of a site and the location of wind turbines, to optimize the
production and lifetime of machinery.
The user needs to define the buildings and vegetation with computer assisted documents (STL
format). The topography can be input as STL format if the terrain is not flat. The ground roughness
can be designed in a grid point format (x,y,z) to define the ground type (water, asphalt, or grass). The
141
computation mesh and the boundary conditions are automatically generated. A wind database is
already integrated in the software for the whole world. The user can also use its own on-site
measurements (as a text file with statistics of speeds and directions) [19].
UrbaWind provides tabular or graphical outputs. Aspects assessed include:
- Solar radiation maps
- Wind speed distributions over urban open spaces
- Average pressure coefficients on surrounding buildings
- Outdoor air comfort Natural
- Small wind energy potential
Strengths
Solver is robust and adapted in CDF wind modeling in urban open spaces, calculation are fast
according [19].
Comparative synthesis of Microclimate Simulation tools
See comparative analysis in the end of the document. Annex part.
Limitations of Microclimate Simulation tools
Current microclimate simulations tools to model open-spaces UHI mitigation retrofit projects can be
classified in two groups: Full tool integrating CFD model coupled with thermo-radiative model and
Simplified approach based on thermo-radiative model. Both require a lot of meteorological and
geometrical data to assess thermal comfort indices and provide little information on physical models
used behind graphical user interfaces. Main uses are to compute urban microclimate during heat
waves in summertime but no many UHI mitigation retrofit measures are embedded in these
programs.
Concerning solutions for alleviating urban heat islands, literature provides hints and already tested
retrofit measurements in pilot sites: planting trees or setting “green roofs” (bringing solar shades and
natural air cooling by evapotranspiration phenomenon) [11, 20].
References
1.
2.
Richards, P.J. and R.P. Hoxey, Appropriate boundary conditions for computational wind
engineering models using the k-ε turbulence model. Journal of Wind Engineering and
Industrial Aerodynamics, 1993. 46 & 47: p. 145-153.
Scudo, G. Thermal comfort. in Built environment sciences & technology (BEST). 2002.
Politecnico di Milano.
142
3.
Latini, G., R.C. Grifoni, and S. Tascini, Thermal Comfort and Microclimates in Open Spaces.
2010.
4.
OTC. Comparison of Urban Climate Tools. 2014; Available from:
http://otcmodel.com/index.php?option=com_content&view=article&id=19:comparison&cati
d=9&Itemid=227.
5.
Smithson, P.A., MICROCLIMATIC LANDSCAPE DESIGN: CREATING THERMAL COMFORT AND
ENERGY EFFICIENCY. R. D. Brown and T. J. Gillespie, John Wiley & Sons Inc. (New York), 1995.
No. of pages: xi + 193. Price: £29.95. ISBN 0-471-05667-7 (paperback). International Journal of
Climatology, 1997. 17(2): p. 225-226.
6.
Ochoa, J., I. Marincic, and H. Villa, Designing outdoor spaces with COMFORT-EX, in
International Workshop on Energy Performance and Environmental Quality of Buildings, U.o.
Sonora, Editor. 2006: Greece.
7.
Bruse, M. ENVI-met 3. Available from: http://www.envi-met.com/.
8.
Huttner, S., M. Bruse, and P. Dostal, Using ENVI-met to simulate the impact of global warming
on the microclimate in central European cities, in 5th Japanese-German Meeting on Urban
Climatology. 2008. p. 307-312.
9.
Elnabawi, M.H., N. Hamza, and S. Dudek. Use and evaluation of the envi-met model for two
different urban forms in cairo, egypt: measurements and model simulations. in 13th
Conference of International Building Performance Simulation Association. 2013. Chambéry,
France.
10.
Ozkeresteci, I., et al. Use and evaluation of the envi-met model for environmental design and
planning: an experiment on linear parks. in ICC. 2003.
11.
USDA. OUTCOMES (OUTdoor COMfort Expert System). 2009; Available from:
http://www.nrs.fs.fed.us/tools/outcomes/
12.
Matzarakis, A. RayMan : radiation on the human body. 2009; Available from:
http://www.urbanclimate.net/rayman/index.htm
13.
Matzarakis, A., F. Rutz, and H. Mayer, Modelling radiation fluxes in simple and complex
environments: basics of the RayMan model. International Journal of Biometeorology, 2010.
54(2): p. 131-139.
14.
Matzarakis, A., F. Rutz, and H. Mayer, Modelling radiation fluxes in simple and complex
environments : application of the RayMan model. International Journal of Biometeorol, 2006.
51: p. 323–334.
15.
Göteborgs_Universitet. The SOLWEIG-model. 2013; Available from:
http://www.gvc.gu.se/Forskning/klimat/stadsklimat/gucg/software/solweig/
16.
Teller, J., POLIS : a Project Information System for Urban Environmental Design. 2009, LEMA
University of Liège.
17.
EERE. Building Energy Software Tools Directory. 2011; Available from:
http://apps1.eere.energy.gov/buildings/tools_directory/software.cfm/ID=232/pagename=alp
ha_list_sub.
18.
MeteoDyn. UrbaWind. Available from: http://meteodyn.com/en/logiciels/cfd-windpedestrian-comfort-safety-urbawind-software/.
19.
EERE. Building Energy Software Tools Directory : UrbaWind. 2011; Available from:
http://apps1.eere.energy.gov/buildings/tools_directory/software.cfm/ID=588/pagename=alp
ha_list_sub.
20.
Voogt, J.A. Urban Heat Islands: Hotter Cities.
2004; Available from:
http://www.actionbioscience.org/environment/voogt.html.
143
Annex 3: Review of innovative methods for retrofitting
purposes – Spain
Contribution to deliverable D.3.3
Component No.3- Analysis of innovative methods applied in the
economical study stage
techno-
Phase No.3 - Analysis- Desk research
Contract No.: 1C-MED12-73
Axe2: Protection of the environment and promotion of a sustainable territorial
development
Objective 2.2:
efficiency
Promotion and renewable energy and improvement of energy
Authors:
Supported by:
144
Buildings
List of appropriate zonal (BES) and field (e.g. CFD, UCM, etc.) tools
to perform coupled simulations
For the past 50 years, a wide variety of building energy simulation programs have been developed,
enhanced, and are in use throughout the building energy community.
The major building energy simulation programs are: BLAST, BSim, DeST, DOE-2.1E, ECOTECT, EnerWin, Energy Express, Energy-10, EnergyPlus, eQUEST, ESPr, IDA ICE, IES <VE>, HAP, HEED,
PowerDomus, SUNREL, Tas, TRACE and TRNSYS 142.
The most used of them are described in the following.
DOE-2.1E143
Hourly, whole-building energy analysis program calculating energy performance and life-cycle cost of
operation. Can be used to analyze energy efficiency of given designs or efficiency of new
technologies. Other uses include utility demand-side management and rebate programs,
development and implementation of energy efficiency standards and compliance certification, and
training new corps of energy-efficiency conscious building professionals in architecture and
engineering schools.
142
143
BRITA in PuBs European project, 2007. Energy Simulation Tools for Buildings
The information about the tools from http://apps1.eere.energy.gov/buildings/tools_directory/
145
EQUEST (FREE)
eQUEST® is a widely used, time-proven whole building energy performance design tool. Its wizards,
dynamic defaults, interactive graphics, parametric analysis, and rapid execution make eQUEST
uniquely able to conduct whole-building performance simulation analysis throughout the entire
design process, from the earliest conceptual stages to the final stages of design. eQUEST's simulation
engine, DOE 2.2, is also time-proven, well known, and widely used
ECOTECT
Complete environmental design tool which couples an intuitive 3D modelling interface with extensive
solar, thermal, lighting, acoustic and cost analysis functions. ECOTECT is one of the few tools in which
performance analysis is simple, accurate and most importantly, visually responsive.
ECOTECT is driven by the concept that environmental design principles are most effectively addressed
during the conceptual stages of design. The software responds to this by providing essential visual
and analytical feedback from even the simplest sketch model, progressively guiding the design
process as more detailed information becomes available. The model is completely scalable, handling
simple shading models to full-scale cityscapes. Its extensive export facilities also make final design
validation much simpler by interfacing with Radiance, EnergyPlus and many other focused analysis
tools.
146
EnergyPlus (FREE)
Next generation building energy simulation program that builds on the most popular features and
capabilities of BLAST and DOE-2. EnergyPlus includes innovative simulation capabilities including time
steps of less than an hour, modular systems simulation modules that are integrated with a heat
balance-based zone simulation, and input and output data structures tailored to facilitate third party
interface development. Recent additions include multizone airflow, electric power simulation
including fuel cells and other distributed energy systems, and water manager that controls and report
water use throughout the building systems, rainfall, groundwater, and zone water use.
ESP-r (FREE)
General purpose simulation environment which supports an in-depth appraisal of the factors which
influence the energy and environmental performance of buildings. The ESP-r system has been the
subject of sustained developments since 1974 and in 2002 converted to the GNU Public License.
ESP-r has the objective of simulating building performance in a manner that: a) is realistic and
adheres closely to actual physical systems, b) supports early-through-detailed design stage appraisals,
and c) enables integrated performance assessments in which no single issue is unduly prominent.
ESP-r attempts to simulate the real world as rigorously as possible and to a level which is consistent
with current best practice in the international simulation community.
147
TRNSYS
An energy simulation program whose modular system approach makes it one of the most flexible
tools available. TRNSYS (TRaNsient SYstem Simulation Program) includes a graphical interface, a
simulation engine, and a library of components that range from various building models to standard
HVAC equipment to renewable energy and emerging technologies. TRNSYS also includes a method for
creating new components that do not exist in the standard package. This simulation package has
been used for more than 30 years for HVAC analysis and sizing, multizone airflow analyses, electric
power simulation, solar design, building thermal performance, analysis of control schemes, etc.
148
DEST
DeST, or Designer’s Simulation Toolkit, is a tool developed for aiding HVAC engineers to realize
“design by analysis, design by simulation”. It can also be used to help architects optimize their
thermal performance of fabrics. It is an annual building energy consumption analyze software doing
simulation hourly for HVAC designers, applying simulation into different phases of design. DeST is
“design by simulation”, which means that DeST is designed to make it possible to apply simulation
into different parts of building design and is convenient for a designer to get sufficient aid in the
design process. In addition, DeST has incorporated different stages of the building design processes
and has five main simulation stages: building thermal process, system scheme analysis, AHU system
analysis, duct/pipe networks, and plant analysis. These simulation stages provide accurate results to
fulfill the needs for different stages of building system design. The second one is that an advanced
multi-zone heat and mass balance methodology based on state space method is applied in building
thermal environment simulations with high accuracy. The third one is that DeST has used a threedimensional dynamic heat transfer methodology for annual simulation which is easy to compute the
heat transfer of a ground-coupled envelope quickly and accurately. Dynamic simulation method
coupling CFD with hourly building simulation used in DeST is the fourth feature. And the last one is
that DeST has used system simulation methodology under uncertain inner heat gains.
149
Commercial Building Energy Asset Scoring Tool
The Commercial Building Energy Asset Score is a national standard for a voluntary energy rating
system evaluating the physical characteristics of your building as built and its overall energy efficiency
independent of occupancy and operational choices.
This Asset Scoring Tool will guide your data collection, store your building information, and generate
an Asset Score and system evaluations for your building envelope and mechanical and electrical
systems. The Asset Scoring Tool will also identify cost-effective upgrade opportunities and help you
gain insight into the energy efficiency potential of your building.
The Commercial Building Energy Asset Score program is in the pilot stage, and only Pilot Participants
are granted access to the Asset Scoring Tool at this time. This is the information avaible:






Data Collection Form
Asset Score Data Collection Priority Map
Quick Start Guide
Example Asset Score Report
Asset Score Report Guide
Operational and Equipment Sizing Assumptions
Process Asset Scoring Tool
150
Data Collection Form
151
Methods to couple zonal and field modelling tools
Zonal models have been known for their integration of airflow and thermal modeling
The actual models are based on the corresponding mass (Equation 1) and the energy conservations
(Equation 2) in different cells, and no assumptions are needed for airflow direction.
New zonal models are developed with the capability to use both types of conservation equations for
airflow and energy in the same cell. They use the specific conservation law for the part of the cell
affected by thermal plumes, jets, and boundary conditions, as well as pressure distribution equations
in the another region (part) of the same cell (Inard et al. 1996; Bouia 1998; Musy 1999; Wurtz et al.
1999; Lin et al. 1999; Haghighat et al. 2001). The balance equations describe the state of the subzones
(or cells), and the equations of transfer describe the phenomena between twoneighboring cells
through their interface.
Efforts have also been made to couple zonal and CFD. Mora (2003) and Mora et al. (2003a, 2003b)
developed an approach in which the zonal model uses the airflow structure from the results of a CFD
model in the same volume. Bellivier (2004) defined the conditions under which a CFD model can be
simplified with enlarging meshes to reach the zonal model's level.144
In reference to the modelling tools, software programs have varying levels of accuracy; they are also
intended to be used at different phases of the design process; and require very different levels of
effort and cost. For example, some tools have been designed to provide immediate feedback to the
designer or project manager during the earliest phases of a project while others such as DOE-2 or
BLAST, require more input time and detail. Consequently, they are generally reserved for later in the
design process when many architectural decisions have already been finalized. EnergyPlus is a newer
building energy simulation program for modeling building heating, cooling, lighting, ventilating, and
other energy flows—building on the most popular features and capabilities of BLAST and DOE-2. Most
energy analysis tools can be classified as being one of four generic types. Note: The software
examples listed are meant to be indicative, not exhaustive.145
The clasification that Paradis presents:
Screening Tools for use primarily during budgeting and programming of retrofits.


FRESA
FEDS
144
Megri, Ahmed Cherif; Haghighat, Fariborz , 2007 .Zonal Modeling for simulating indoor environment of buildings: review, recen t
developments, and applications.
http://www.thefreelibrary.com/Zonal+Modeling+for+simulating+indoor+environment+of+buildings%3A...-a0172427315
145
Richard Paradis , 2010.Energy Analysis Tools.National Institute of Building Sciences.
http://www.wbdg.org/resources/energyanalysis.php
152
Architectural Design Tools for use primarily during programming, schematics, and design
development of new construction and major retrofit.

Building Design Advisor

Energy Scheming
Load Calculation and HVAC Sizing Tools for use primarily during design development and construction
documentation of new construction and major retrofit.

HAP

TRACE

DOE-2

BLAST

VisualDOE

EnergyPlus
Economic Assessment Tools for use throughout the design process.

BLCC

Quick BLCC
Methods to account for behavioural patterns
The article “User behavior in whole building simulation”146 has shown that there is no realistic
general design concept, without applying extensive oversized active systems, that minimizes the
effect of different types of user behavior and with that shows robustness to this parameter.
Intended and future user behavior therefore should be assessed carefully. Improved modeling of user
behavior in numerical simulation can optimize overall building performance.
From literature, it appears clear that models for human behaviour and for energy simulation are
related to two different approaches (Boergson et al. 2008):
 Models of human behaviour are based on statistical algorithms that predict the probability of
an action or event.
146
P. Hoes , J.L.M. Hensen , M.G.L.C. Loomans , B. de Vries , D. Bourgeois , 2008. User behavior in whole building simulation
153
 Based on heat transfer and thermodynamic equations, and typically model human actions
(operation of lights, blinds and windows) basing on predefined fixed schedules or predefined
rules (the window always open if the indoor temperature exceeds a certain limit). These
tools often reproduce building dynamics using numerical approximations of equations
modelling only deterministic (fully predictable and repeatable) behaviours. In such a
 way, “occupant behaviour simulation” could refer to a computer simulation generating “fixed
occupant schedules”, representing a fictional behaviour of a building occupant over the
course of a single day (Goldstein et al, 2010). This is an important limitation of energy
simulation tools for modelling.
Flux diagram: from drivers to energy consumption and indoor environment.147
Software packages are not nowadays capable of adequate evaluation of scenarios explaining the
influence of occupant behaviour, but this is a crucial point in the efforts to minimize energy
consumption.
In the directionof a more holistic programa there is an example : the IT-Tookit for Energy Efficient
Retrofit Measures148 out of IEA Annex 46 is a collection of computer tools for public buildings. The
free of cost toolkit supports owners and planners of public buildings at the following tasks:
Identification of buildings with too high energy uses, energy efficient operation of buildings, detailed
inventory and building documentation, ideas for energy efficient refurbishments, development of an
147
Valentina Fabia; Rune Vinther Andersen; Stefano Corgnatia,Bjarne W. Olesen, 2008. Occupants' window opening behaviour: A literature
review of factors influencing occupant behaviour and models
148
Information from http://www.buildup.eu/tools/16415
154
energy efficient retrofit concept based on DIN V 18599 (compatible to EPBD CEN standards) and
economical evaluation of energy performance contracts.
In detail the toolkit consists of the following tools:
1. Performance rating for heating, electricity and water
2. Electronic building inspection protocol
3. Operation and maintenance guide
4. Energy audit protocol
5. Retrofit case studies
6. Energy conservation measures
7. Energy efficiency calculator for building retrofit
8. Guide for ESCO projects
9. Financial spreadsheet for EP contracts
10. ESCO case studies
Applications of CFD/BES to recommend optimal retrofitting measures
155
eQUEST offers several graphical formats forviewing simulation results.
Equest allows you to perform multiple simulations and view the alternative results in side-by-side
graphics. It offers energy cost estimating, daylighting and lighting system control, and automatic
implementation of common energy efficiency measures (by selecting preferred measures from a list).
Reasons that innovative methods are not applied in the technoeconomical design stage-barriers.
Simulation tools do not represent a cost itself. Generally, licences are available for free or al least for
few hundreds of euro.The main investment is represented by labour cost related to their use. An
energy study could be performed by external consultants or by the design team itself. In this case
further labor investment is required in order to aquire the know-how and skill. It can be assumed that
the cost of a energy study would range from 5% to 10% of the overall design costs. This cost could be
in part addressed to compulsory building code verification when it occurs.149
The main reasons why innovative methods are not applied in the techno-economical design stagebarriers are:
Lack of Credibility: Customers (of energy modeling services) and other stakeholders do not have
confidence in energy modeling results, for the following reasons:




Lack of Quality: Energy modeling results may not reflect realistic building energy consumption
and costs.
Lack of Reproducibility: Different practitioners do not produce the same energy modeling
results, even when using the same tools and building characterization data.
Misguided Expectations: Customers do not have a clear understanding of what modeling can
and should provide.
Difficulty in Assessing Skills: It is difficult for customers to assess the skill level of a
practitioner.
Limited Time for Critical Thinking: Currently, practitioners do not spend the majority of their time on
critical thinking and informing design.
Need for More Experienced and Skilled Practitioners: A limited number of energy modelers possess
sufficient skills and experience.
Low Market Demand: The demand for and value of energy modeling services could be much higher.
149
Marco Beccali, 2007. Energy Simulation Tools for Buildings, project BRITA in PuBs – Bringing retrofit innovation to application in public
buildings, EU 6th framework program Eco-building (TREN/04/FP6EN/S.07.31038/503135).
156
Design teams often introduce energy modeling too late in the game to really affect key design
decision and instead use it as an accounting or code compliance tool to establish that minimum
requirements are met. Used in this way, design teams overlook significant opportunities to inform
and improve building design.
Biography
PROGRAMS
Building Energy Software Tools Directory http://apps1.eere.energy.gov/buildings/tools_directory/
DOE-2.1E
http://doe2.com/
http://gundog.lbl.gov/dirsoft/d2vendors.html
EQUEST
http://doe2.com/equest/index.html
ECOTECT
http://www.squ1.com
ENERGY PLUS
http://www.energyplus.gov
ESP-r
http://www.esru.strath.ac.uk/
TRNSYS
http://sel.me.wisc.edu/trnsys/
DeST
http://www.dest.com.cn
Commercial Building Energy Asset Score
https://buildingenergyscore.energy.gov/
157
Open spaces
List of appropriate field models to perform microclimate simulations
in open public spaces
The innovative programs that analyze thermal comfort in urban space including Twonscope,
SOLWEIG, COMFA+, ENVI-met, RayMan andOTC Model. These programs are the most advanced, free
(except Twonscope) and regularly updated :
Comparison of Outdoor Thermal Programs150
150
Reference form OTC Model architecture and related software are protected by Canadian
158
TownScope
Supports urban design decision-making in a "responsive environment" perspective. TownScope II
combines a user-friendly graphical interface with powerful analysis tools. Thermal comfort, critical
wind discomfort risk and perceptive qualities of urban open spaces can be assessed very quickly via
TownScope. Additionally, the software provides an integrated multi-criteria decision module to rank
various alternative proposals.
SOLWEIG (FREE USE)
SOLWEIG is a micrometeorological model. It is able to simulate spatial variations of mean radiant
temperature and 3D fluxes of longwave and shortwave radiation in urban areas using high resolution
DEMs. The model is available through a graphical user-friendly interface that can be downloaded for
free from the Urban Climate Group (UCG) webpage
http://www.gvc2.gu.se/ngeo/urban/urban.htm
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COMFA +(FREE USE)
The COMFA model is a comfort evaluation tool based on the energy balance of the person in a given
outdoor space, originally developed by Brown and Gillespie for landscape evaluation.
In this study an upgrade of the COMFA, named COMFA+, to be applied to urban spaces is presented.
The main effetcs of the urban fabric on the heat flows between the person and the environment are
described and taken into account. Finally the COMFA+ is applied to a case study, showing the
potential and limits of the model.
ENVI MET (FREE USE)
160
ENVI-met is a three-dimensional microclimate model designed to simulate the surface-plant-air
interactions in urban environment with a typical resolution of 0.5 to 10 m in space and 10 sec in time.
Typical areas of application are Urban Climatology, Architecture, Building Design or Environmental
Planing, just to name a few.
ENVI-met is a Freeware program based on different scientific research projects and is therefore under
constant development. ENVI-met is NOT Open Source.
RAY MAN (FREE USE)
RayMan calculates atmospheric conditions and human thermaln comfort in urban areas and this
software is free for use.
161
OTC MODEL (FREE USE)
Outdoor Thermal Comfort Model (OTC Model) has been developed to evaluate outdoor comfort
conditions at the urban space. The OTC Model is useful for determining the comfort of humans in the
urban design. The OTC Model provides the analysis with an output of Universal Thermal Comfort
Index (UTCI) and Physiological Equivalent Temperature (PET).
Anothers programs:
Autodesk Ecotect Analysis
Autodesk® Ecotect® Analysis sustainable design analysis software is a comprehensive concept-todetail sustainable building design tool. Ecotect Analysis offers a wide range of simulation and building
energy analysis functionality that can improve performance of existing buildings and new building
designs. Online energy, water, and carbon-emission analysis capabilities integrate with tools that
enable you to visualize and simulate a building's performance within the context of its environment.
162
163
SkyHelios (FREE USE)
SkyHelios is a new tool for applied climatology calculating continuous sky view factor and sunshine
duration in high spatial and temporal resolution by using the graphic processor. The storage and
export of calculated data is main feature.
Autodesk® Vasari
Autodesk® Vasari is an easy-to-use, expressive design tool for creating building concepts. Vasari goes
further, with integrated analysis for energy and carbon, providing design insight where the most
important design decisions are made. And, when it’s time to move the design to production, simply
bring your Vasari design data into the Autodesk® Revit® platform for BIM, ensuring clear execution of
design intent.
164
Heliodon (FREE USE)
Heliodon2TM is a tool designed to control energetical and visual aspects of natural lighting in urban
and architectural projects.
165
RADIANCE (FREE USE)
RADIANCE is a highly accurate ray-tracing software system for UNIX computers that is licensed at no
cost in source form. Radiance was developed with primary support from the U.S. Department Of
Energy and additional support from the Swiss Federal Government.
Shading (FREE USE)
A plugin for SketchUp that enables analyzing any given design with regards to solar rights or shading
requirements. It allows the examination of the mutual shading between buildings and any other
objects. It can perform an accurate evaluation of the design of any external or internal windows'
shading devices as well. The analysis can be carried out visually and quantitatively The plugin allows
the designer to plan efficiently the various functions of spaces among buildings in an urban
environment, as well as determining the location of the passive and active solar collectors. The plugin
allows to calculate the (Geometrical) Shading/Insolated Coefficient of any surface selected from the
3D model.
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In the case of Spain, there are only 5 tools, and they are about buildings, not about open spaces:
Spanish available programs151
Application of CFD to recommend optimal retrofitting measures
The selection of an optimal combination of ERMs (energy retrofit measures ) for a particular urban
space is influenced by several factors.
The decision process is seen from a managerial point of view, emphasizing the role of the planer in
this process. The ‘ingredients’ of a strategic plan for an optimal retroffiting measures are action plans,
objectives, operative modalities, human
and capacities as opportunities This brings the step of options in the so called ”intelligence”
(Malczewski, 1999152) phase of the strategic decision.
It can be advantageous to use a combination of packages, if possible, to simulate the effects of the
ERMs on the building energy consumption. There is need a holistic programs to take into account
several aspects.
The key mitigation technologies analized in the Review and Critical Analysis of International UHI
Studies are : Cool Roofs (including Photovoltaic roofs), Cool Pavements/Roads, etc., Green
Roofs/Urban Green Areas, Vehicle Paints, Other (District cooling/ Water cooling).
151
152
Building Energy Software Tools Directory http://apps1.eere.energy.gov/buildings/tools_directory/
Malczewski, J.: GIS and Multicriteria Decision Analysis. John Wiley & Sons, New York, 1999.
167
Reasons that innovative methods are not applied in the technoeconomical design stage-barriers.
The present economic crisis due to the accumulation of massive debt, much of it in the property
sector, calls for innovative funding mechanisms to support sustainable urban development.
The role of the public sector is thedriving force and facilitator of the relationship between public
interests and private objectives. From this perspective we have demonstrated the necessity for
introducing solid administrative institutions to foster private investments.
The policies that encourage decentralization for financing and implementing redevelopment may
allow for a better response to city needs by offering more flexible tools and alternative forms of fiscal
and fund incentives to develop the needed city areas.
The application of energy efficient retrofit measures at open spaces has shown that new technologies
are rarely applied because of a lack of knowledge at the decision makers.
It is important to realise that models are not always used for the purpose that they were developed.
One of the more frequent examples is the situation of models developed to improve the scientific
understanding of some phenomena that are used for regulatory purposes. There is difference
between models developed by re-searchers for researchers, and those developed for non-expert
use153.
Before complex numerical models can become accepted regulatory tools, it is probably necessary to
define an additional set of clear instructions that reduces the users’ choice to a minimum and ensures
a uniform application of the models.
There is need developing a decentralised decision model, encompassing all actors involved in the
implementation strategy of a retrofit measure, from different backgrounds: geophysics/ engineering
seismology, (structural) engineering, architecture, economy (investment efficiency) and sociology
(consideration of user issues) is an objective for which interdisciplinary aspects are of importance.
153
Model Evaluation Group (MEG,1994)
168
Bibliography
An integrated approach to urban design http://www.holisticurbandesign.co.uk/#
Charlton, J., Giddings, B. and Horne, M. (2008) 'A Survey of Computer Software for the Urban Design
Process', Design Decision Support Systems (DDSS). Eindhoven, 7th – 10th July.
M. D. Bostenaru Dan (2004) 'Multi-criteria decision model for retrofitting existing buildings', Natural
Hazards and Earth System Sciences (2004) 4: 485–499 SRef-ID: 1684-9981/nhess/2004-4-485
INNOVATIVE PROGRAMS
Building Energy Software Tools Directory http://apps1.eere.energy.gov/buildings/tools_directory/
TownScope software http://www.townscope.com/
Envi met http://envi-met.de/
Rayman http://www.mif.uni-freiburg.de/rayman/
Autodesk Ecotect Analysis http://usa.autodesk.com/ecotect-analysis/
SkyHelios http://www.urbanclimate.net/skyhelios/
Autodesk® Vasari http://autodeskvasari.com/
Heliodon http://www.heliodon.net/heliodon/index.html
Radiance http://radsite.lbl.gov/radiance/framew.html
Shading http://ayezioro.technion.ac.il/Downloads/ShadingII/
169
Annex 4: Review of innovative methods for retrofitting
purposes – Italy
Deliverable D.3.3
Component 3 – Analysis-Desk Research
Phase 3.3 - Analysis of innovative methods applied in the techno-economical study
stage
Contract No.: 1C-MED12-73
Axe2: Protection of the environment and promotion of a sustainable territorial
development
Objective 2.2: Promotion and renewable energy and improvement of energy
efficiency
Authors: Emilia-Romagna Region
170
Review of innovative methods for public buildings retroffitting purpose
Literature on public buildings retrofitting is too wide, also if we consider only case studies. The
systematic collection of such information to build a national or regional database gathering the most
important experiences and praxis constitutes the main difficulty. The aim is to create the equivalent
of the web site www.buildup.eu at regional level. The examples involve the use of innovative
materials, the integration of plants employing renewable sources, the adoption of innovative
administrative and bargaining processes.
FRESH Project “Energy Performance Contract in Social Housing. European Handbook” constitues an
interesting example. ACER (Social Housing Company) of Reggio Emilia (one of the provinces of EmiliaRomagna Region) joined this project. The company demonstrates to be always interested in these
issues. The project chooses an EPC standard model that has to be adopted for energy retrofit
interventions, in particular employing ESCOs. Taking into consideration the same issue, Piemonte
Region provided for a obligatory EPC model at a regional level.
CTI provided with UNI CEI/TR norm “ Energy management – Energy audits – General requirements for
the energy audit service” on contracts and procedures for energy audit realization. Law defines the
requirements and the common procedure for energy diagnosis and also the requested
documentation.
REQUEST- Renovation through Quality Supply Chains and Energy Performance Certification
Standards- project; European Project financed by Intelligent Energy for Europe programme, to
enhance quantity and quality of energy retrofitting interventions of european residential buildings.
“EnERGo Energy efficiency retrofit of government buildings” project of IEA EBCS Annex 61 and Annex
46 constitutes an interesting study applied to government buildings. The main goal of the project is to
increase annual rates of building stock refurbishment and energy use reduction, for each project.
ENEA is the italian partner. The subject matter of the research are government/public non-residential
buildings: office/administrative buildings, dormitories, on storey production.
Annex 46 lead up to the elaboration of an “Energy process assessment protocol”, the building up of
an “Energy Saving Technologies for Building Retrofits” database with examples of best practices,
included a Tool-Kit for “Energy Conservation Database” (ECM), result of the elaboration of 76 case
study. The Development of “Best-Practice Guidelines for Innovative Energy Performance Contracts”
(EPC) must be added with the evaluation of financial aspects of interventions and EPC. The final result
is IT Tool-kit “EnERGo” software. The study is really interesting and provides with a ESCO guide and
also “Best Practice Guidelines for Using Energy Performance Contracts to Improve Government
Buildings”. These guides coul not be applicable to local or regional European contexts.
EnErgo project, as stated in ENEA reports, aims at giving tools and guidelines to identify energy saving
opportunities for public and government buildings, supporting leaders to evaluate efficiency and
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approving strategies for energy conservation and also finding new and more efficient contractual
forms regulating energy performance for government and public buildings.
Legambiente report (league for the Environment – the most widespread environmental organization
in Italy) Renewable Municipalities 2013, annually relates the analysis and the classification of the
activity of municipalities and also the data on public buildings renewable sources use. This report is a
mere monitoring activity, but it can fastly and diffusely communicate the country state-of-the-art and
it is an aknowledgment for virtuous municipalities.
Finally, the calculation model or the use of innovative technologies do not represent the main
problem of public buildings. On the contrary administrative procedures, the definition of standard
contracts accounting for energy efficiency, the lack of a database on virtuous municipalities constitute
the main difficulties. The spread of experiences allow the sharing of concluded interventions, in
order to learn from others without performing always the same activity in different contexts. The
same principle has been adopted by the Covenant of Mayors: learning from other experiences.
Short description of tools and methods
BES Softwares, in Italy, can be distinguished according to two criteria, on the basis of usage:
a) Thermotechnical Softwares, used for the evaluation of the energy performance in accordance with
UNITS 11300 National Standards, which is based on CEN Umbrella norms and ISO EN 13790 (monthly
method);
b) International Softwares for the evaluation of energy performance through dynamic models, such
as ENErgyplys, Trynsys, ESP-r. etc.
Softwares a) have been validated by CTI154 and used for the everyday activity of evaluation carried out
by architects and certifiers. Studies and meetings are conducted periodically on the use of these
tools, in particular by FCE, National Forum on Certification of Energy Performance (annual forum).
The CTI, the main Italian Universities, all the Regions and Autonomous Provinces and the Ministry of
Economic Development take part to the FCE.
The software certification, in force since 2008, has allowed to standardize calculation software results
with correct and comparable results (error tolerance: 5%). It has also improved the capabilities and
the products quality available on the market.155
Calculation models are based on steady-state calculation; entry data on building geometry,
transmittances, use classification and climatic data (in accordance with Italian standard UNI 10349)
Procedure for the Compliance Certificate’s Issuance provided by part 1 and 2 of UNI TS 11300 norms (2008) and part 4 of UNI T S 11300
(2012) in accordance with D.P.R. of 2 nd of April 2009 #59, link: http://www.cti2000.it/index.php?controller=sezioni&action=show&subid=34
155
Lamberto Tronchin, Kristian Fabbri, A Round Robin Test for buildings Energy performance in Italy, Energy and Buildings, Volume 42,
Issue 10, October 2010, Pages 1862-1877
154
172
are essential. From these entry data it is possible to calculate the energy need for space heating and
cooling, pursuant to Standard UNITS 11300 part 1.
The energy need for space heating and cooling represents the entry data for UNITS 11300 part 2, in
order to calculate the primary energy needs for Heating System and Domestic Heat Water (DHW)
with natural gas boiler (UNITS 11300-2 following CEN standard 15316-1, etc.).
The UNITS 11300-Part 2 determines the energy efficiency of HVAC (Heating Ventilation and AirConditioning) plant sub-systems (i.e. emission, regulation, distribution, generation) and generator in
accordance with Council Directive 92/42/EEC.
The procedure provided by UNI TS11300 part 4 (also following CEN standard 15316-1, etc.) must be
followed in case of other generators fuelled by renewable energy sources are present. This regulation
applies for the contemporary presence of more than one generator with an activation priority rule: at
first solar heating (if present), in the second place the heat pumps, then combined heat and power,
afterwards biomass boilers and finally natural gas boilers.
Softwares b) have been used mainly in the field of University research, also to compare UNITS 11300
results with actual people’s behaviour. They have been used also by the private sector in the field of
programmes for energy diagnosis, in order to evaluate the energy retrofit.
In Italy the International Building Performance Simulation Association(IBPSA)156 and the
Associazione Italiana Condizionamento dell’Aria, Riscaldamento e Refrigerazione (AICARR)157 are a
reference point for experts on these issues. They also organise national meetings in order create
cultural exchanges on this field.
Representative Case Studies
The scientific literature on the subject number several case studies. Among these, the most significant
studies to mention are: G.Dallo’O’158, A.Magrini159, I.Balarini160, M.Cellura161 and G.V.Fracastoro162.
156
http://www.ibpsa-italy.org/
http://www.aicarr.org/
158
Giuliano Dall’O’, Luca Sarto, Nicola Sanna, Angelo Martucci, Comparison between predicted and actual energy
performance for summer cooling in high-performance residential buildings in the Lombardy region (Italy), Energy and
Buildings, Volume 54, November 2012, Pages 234–242
159
Anna Magrini, Lorenza Magnani, Roberta Pernetti, The effort to bring existing buildings towards the A class: A
discussion on the application of calculation methodologies, Applied Energy, Volume 97, September 2012, Pages 438–
450 ,Energy Solutions for a Sustainable World - Proceedings of the Third International Conference on Applied Energy,
May 16-18, 2011 - Perugia, Italy
160
Ilaria Ballarini, Vincenzo Corrado, Application of energy rating methods to the existing building stock: Analysis of
some residential buildings in Turin, Energy and Buildings, Volume 41, Issue 7, July 2009, Pages 790–800
161 Maurizio Cellura, Alessandra Di Gangi, Sonia Longo, Aldo Orioli, An Italian input–output model for the assessment of
energy and environmental benefits arising from retrofit actions of buildings, Energy and Buildings, Volume 62, July
2013, Pages 97–106
157
173
The ENEA study “Survey on public buildings energy consumption (offices and schools) and their
potentialities for energy efficiency interventions” redacted by Marco Citteri and Gaetano Fasano
(ENEA) in 2009, in collaboration with MSE. This study represents the reference point of statistic
distribution of public buildings energy consumption.
The most exhaustive study on public buildings is: CRESME, “Improvement of public buildings’ energy
efficiency – Volume 1The Study” CRESME Consulting srl. “Operative Interregional Programme
“Renewable Energy and Energy Saving” 2007-2013, March 2011
Review of innovative methods for open spaces
The issues of Open Spaces, Urban Heat Islands and urban spaces microclimate are not subject matter
of research in Italy and in Emilia-Romagna Region. They are investigated only in some researches or
specific European projects. For this reason, it is not possible to identify innovative methods for
retrofitting purposes applied to the italian case.
Starting with a brief examination of how cities have always been studied we can easily understand
how the socio-economic aspects of cities affect the bio-physical environment.
Nowadays urban planning has begun to introduce environmental sustainability as a conceptual
driving force for all its theories. This implies enormous changes in the planning design and
management of infrastructures and areas to be developed, and energy conservation and water
management become aspects that have to be thoroughly considered in all the phases of planning.
For example there are some General Plans in Italy that includes some requirements on local
microclimate and its improvement.
For example in Bologna Urban and Building Regulation (RUE) is established that the urban projects
must take into account the temperature peaks during the design phase. The designer should make
decisions not only about the building but also about the surrounding areas, and how the vegetal
components can achieve a high quality of the built tissue; moreover the designer should exploit the
phenomenon of evapotranspiration to improve the comfort in the open spaces.
As regards the General Plan there is not any performance index about Urban Heat Island and local
microclimate to comply with, as a result most of the times the designer does not give any plan on the
open space, no indications about vegetal components or the comfort index, as we can find for the
indoor environment, such as PMV (Predicted Mean Vote) or PPD (Predicted Percentage Dissatisfied),
and so on.
Gian Vincenzo Fracastoro, Matteo Serraino, A methodology for assessing the energy performance of large scale
building stocks and possible applications, Energy and Buildings, Volume 43, Issue 4, April 2011, Pages 844–852
162
174
Innovative methods in the General Plans
The City of Bolzano, in order to obtain an overview of the issues and possible mitigation measures
and compensation, that would lead to the formulation of a concrete proposal with regarding to
inserting standards into municipal building, commissioned a study that rsulted in the choice of the
"RIE Index"163 (riduzione dell’impatto edilizio – building impact decrease) system for calculating the
construction.
The Building Code of the City of Bolzano, introduced in 2004, provides for the adoption of the RIE
process for all new construction and interventions on existing buildings as well as for the any kind of
actions having an impact on the external surfaces exposed to rainwater (roofs, terraces, landscape
architecture, courtyards, green areas, paved areas, etc..).
Figure 1 – The Algorithm
RIE = building impact decrease
Svi= i-esima built or not built, green cover
Sj= j-esima built or not built, no green cover
ψ i= i-esimo coefficiente di deflusso
ψ j= j-esimo coefficiente di deflusso
Se = Superfici equivalenti alberature
As it is written above there are only few examples about the Urban Heat Island.
Hereunder an example where the attention for the microclimate is very important during the
architectural process.
163
http://www.comune.bolzano.it/urb_context02.jsp?ID_LINK=512&page=10&area=74&id_context=4663
175
The area of Fiumana, Forlì – Cesena Province164, was a pilot project of sustainable building where the
microclimate was the first issue to to be taken into account. First of all was characterised the
microclimate by MODAMB (pre phase) and then, thanks to ENVI-met software, the area was studied
from a geographical point of view, the position and the material of each buildings were analysed and,
as a result, it was finally decided and designed the vegetal component layout in order to obtain a
certain quality of outdoor comfrot.
Figure 2 – MODAMB and ENVI-met rapresentation
164 Maurizio Garavini, Teodoro Georgiadis e Silvia Rossi, 2009, “Progettare l’abitare”, Bologna, Albisani Editore
176
Figure 3 – Green Layout and Solar Stress
Innovative method from research point of view
There is a very innovative method developed by Politecnico of Milan: COMFA +165.
The model COMFA was developed by Brown and Gillespie, but Valentina Dessì and Adriana Angelotti
improved it. The new method takes into account the person metabolism and the convective heat flux
between air and the person as in the first version, but also the solar radiation absorbed by the person
and direct solar flux and its component intercepted by building.
The urban space from environmental point of view is based on a new layout of the space, new
functions organized during the different day hours, that means that during the day not everywhere
there must be comfort conditions, but only during the activities.
It was tested on Piazza Risorgimento in Milan, where plenty of activities can be unrolled during the
day. Some strategies were adopted after this study to control the summer discomfort as direct solar
radiation and the average temperature. Both, the private and the Public Administration decided to
use shading systems or cool materials for the floor or, vice versa Public Administration decided to
better equip that area that was well shading yet.
165
Valentina Dessì, 2008, “Progettare il comfort urbano”, Sistemi Editoriali Se
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Conclusions
Italian national and regional level regulation does not consider the aspects of open spaces in the
prespective of the U.H.I. mitigation.
As a result in urban planning laws and regulations there is no interpretation of the context, the
morphology and the transformation dynamics of the structure of the urban fabric, translated in
requirement data or into criteria and rules for design on an urban and architectural scale for open
space.
The case studies above described have been developped in the context of University or research
centre activities , because they are at a very experimental stage.
In this case Republic Med has the opportunity to become the first study that elaborates tools,
protocols or methods of investigation aiming at creating legal and operative instruments for
architects, urban planner and local authorities.
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SIMULATION TOOLS (source: UHI CE project)
Scale
Description
Input
Output
Available at
Scale
Description
Input
Output
Available at
ALADIN
Regional climate model
ALADIN is a regional version of the ARPEGE model used for the prediction of
tropical cyclones in the south-west L1elian Ocean (the area of responsibility of
RSMC La Reunion for tropical cyclone warnings). The model configuration is
essentially the same with the following exceptions. Data assimilation is 3D-Var
with a linear beta-plane, non-linear and omega balances for upper-air
observations. In the horizontal, the model has a 10 km horizontal mesh size and
has 60 vertical levels. Bogus synthetic wind observations are produced around
tropical cyclones from the surface to 500 hPa deduced from the Holland analytical
model, plus the mean sea level pressure at the center. The model runs on a 6homly assimilation cycle with 84-hour forecasts produced from data times 0000
UTC and 1200 UTC.
http://www.cnrm.meteo.fr/gmgec/spip.php?article84&lang=fr
ArcGis
Global climate model, regional climate model
Esri's ArcGIS is a geographic information system (GIS) for working with maps and
geographic information. It is used for: creating and using maps; compiling geographic
data; analyzing mapped information; sharing and discovering geographic information;
using maps and geographic information in a range of applications; and managing
geographic information in a database.
The system provides an infrastructure for making maps and geographic
information available throughout an organization, across a community, and
openly on the Web.
ArcGIS includes the following Windows desktop software:
ArcReader, which allows one to view and query maps created with the other
ArcGIS products;
ArcGIS for Desktop is licensed under three functionality levels[1]:
ArcGIS for Desktop Basic (formerly known as ArcView), which allows one to
view spatial data, create layered maps, and perform basic spatial analysis;
ArcGIS for Desktop Standard (formerly known as ArcEditor), which in addition
to the functionality of ArcView, includes more advanced tools for manipulation of
shapefiles and geodatabases; or
ArcGIS for Desktop Advanced (formerly known as ArcInfo), which includes
capabilities for data manipulation, editing, and analysis.
CAD File Support (DXF, DWG), dBASE (DBF), ODBC Connections, Shapefiles,
IDRISI Raster Format (RST), Golden Software Formats (GSAG, GSBG,
GS7GB).
Shapefiles, ArcMap documents
www.esri.com
179
Scale
Description
Input
Output
Available at
Scale
Description
Input
Output
Available at
Scale
Description
88 ECMWF
Regional climate model
European Center for Medium range Weather Forecasting. This model runs to 7
days and provides data at 24 hour intervals for sea level pressure, 850 mb winds
and temperatures and 500 mb heights. These plots are generated once a day at
8:45 PM EST.
The products are provided in GRIB code or in plotted form. Products from the
Deterministic Atmospheric Model: U & V velocity, temperature, cloud cover,
Mean sea level pressure, Sea Ice Cover, Snow depth, Snow density, Soil
temperature, Surface pressure, Total cloud cover, Total column Ozone, Total
column water vapour, Volumetric soil water layer.
http://www.ecmwf.int/
ENVI-met
Urban climate model
ENVI-met is a three-dimensional microclimate model designed to simulate the
surface-plant-air interactions in urban environment with a typical resolution of 0.5
to 10 m in space and 10 sec in time. Typical areas of application are Urban
Climatology, Architecture, Building Design or Environmental Planning, etc.
ENVI-met is a prognostic model based on the fundamental laws of fluid dynamics
and thermo- dynamics. The model includes the simulation of: Flow around and
between buildings, Exchange processes of heat and vapour at the ground surface
and at walls, turbulence exchange at vegetation and vegetation parameters,
bioclimatology particle dispersion.
geometry, surface properties building information, and initial weather data
Binary format which can be extracted by Leonardo or Xtract, graphs and isolines,
or text files. It calculates wind speed, wind direction, air temperature, humidity,
TKE, LAD, short wave radiation, long wave radiation, SVF, wall temperature,
leaf temperature, temperature and vapor flux from vegetation, PMV, PPD, mean
radiant temperature, gas/particle concentration, CO2, surface temperature, heat
flux into the air, heat flux into the soil, water flux, mass deposed, and soil
temperature
http://www.envi-met.com/
IDRISI
Urban climate model
IDRISI is an integrated geographic information system (GIS) and remote
sensing software for the analysis and display of digital geospatial information.
IDRISI is a PC grid-based system that offers tools for researchers and
scientists engaged in analyzing earth system dynamics for effective and
responsible decision making for environmental management, sustainable
resource development and equitable resource allocation.
Key features of IDRISI include:
a complete GIS analysis package for basic and advanced spatial analysis,
including tools for surface and statistical analysis, decision support, land
change and prediction, and image time series analysis;
180
a complete Image Processing system with extensive hard and soft classifiers,
including machine learning classifiers such as neural networks and
classification tree analysis, as well as image segmentation for classification;
Integrated modeling environments including the Earth Trends Modeler for
image time series of environmental trends and Land Change Modeler for land
change analysis and prediction.
Input
Output
Available at
Landsat ETM, SPOT, GEOTIFF, HDFEOS,NETCDF, SDTS, DLG,
RADARSAT
BMPIDRIS, DXFIDRIS, JPGIDRIS
http://clarklabs.org
RayMan
Scale
Description
Input
Output
Available at
Scale
Description
Input
Urban climate model
RayMan is a freely available radiation and human bioclimate model. The
model simulates the short- and long-wave radiation flux densities from the
three-dimensional surroundings in simple and complex environments. It
calculates radiation flux densities, sunshine duration, shadow spaces and
thermo-physiologically relevant assessment indices using a limited number of
meteorological and other input data.
topography, obstacles, horizon limitation, personal data, clothing and activity
data, current weather data, location
Sun paths for each day; shadowing by urban and natural obstacles for each day
of the year and for each specific period of the day; sunshine duration (with and
without horizon limitations); hourly, daily and monthly averages of short-wave
and long-wave radiation fluxes; thermal indices like PMV, PET and SET;
assessment of the thermal bioclimate for different types of landscape or urban
structure.
http://www.urbanclimate.net/rayman/index.htm
RegCM
Regional climate model
RegCM is a 3-dimensional, sigma-coordinate, primitive equation regional
climate model.
Terrain and ICBC, terrestrial variables (elevation, land use, sea surface
temperature) and three-dimensional isobaric meteorological data (temperature,
humidity, geopotential height, zonal and meridional wind, vertical velocity,
surface pressure).
181
Output
Available at
Scale
Description
Scale
Description
Input
Output
Available at
Scale
Description
List of output variables from atmosphere: wind speed, Temperature, Water
vapor Mixing ratio, Cloud water mixing ratio, Surface pressure, Total
precipitation, Lower soil layer temp, Total soil water, Base.
List of output variables from surface model: Anemometer wind, Surface drag
stress, temperature, Anemometer specific humidity, soil moisture, Total
precipitation), Surface runoff, Snow water equivalent), Sensible heat, Net
longwave, Net solar absorbed, Downward longwave, Solar incident, Convective
precipitation, Surface pressure, PBL height.
List of output variables from radiation model: Cloud fraction, Cld liquid H2O
path, Solar heating rate, LW cooling rate, Surface abs solar, LW cooling of
surface, Clear sky col abs sol, Clear sky surf abs sol, Clear sky net up flux, Clear
sky LW surf cool, Instant incid solar, Column abs solar, Net up LW flux at TOA.
List of output variables from tracer model: Tracer mixing ratio, aer mix,
Column burden, Wet deposition large-scale and convective, Surface dry
deposition, chem gas and aqu conv. , Surface emission , TOArad forcing av,
SRFrad forcing av.
http://users.ictp.it/RegCNET/model.html
http://gforge.ictp.it/gf/
REMO
Regional climate model
Remo is coupled atmosphere-hydrology model system for climate modeling
and weather forecast. It was developed based on the Europa model (EM) and
the Global climate model Echam4. The model was successfully validated. The
atmospheric model REMO is coupled to three different hydrology models and
three ocean/sea-ice models. Horizontal resolutions between 1/10° and 1° are
currently used for simulations covering time ranges from days to centuries with
both parameterizations
SkyHelios
Urban climate model
SkyHelios is a new tool for applied climatology, calculating continuous sky
view factor and sunshine duration in high spatial and temporal resolution for
each point in a complex area. Short computing and development time are the
benefits of this model.
Raster files, including: Tab delimited text files (*tab), csv files, text files, cera
text files ond portable network graphics (*png). Vector Files: RayMan
obstacle Files (*obs) and ShapeFiles (*shp).
SVF, Sunpath and sunshine duration.
http://www.urbanclimate.net/skyhelios/
SURFEX
Urban climate model
Surfex is a surface modeling platform developed by Meteo-France. It is
composed of various physical models for natural land surface, urbanized areas,
lakes and oceans. It further takes chemistry and aerosols surface processes into
account. It can be either used stand alone or coupled to atmospheric or
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hydrological models.
Input
Output
Available at
Scale
Description
Input
Output
Available at
Scale
Description
Input
Output
Available at
Physiographical input (topography, surface properties), Meteorological forcing
(solar radiation, rainfall, temperature, wind speed and humidity)
Heat and moisture budgets for different surface types, surface temperatures,
moisture, snow, air temperature, humidity and wind speed at different altitudes
http://www.cnrm.meteo.fr/surfex/
WRF Climate (CLWRF)
Regional climate model, urban climate model
The Weather Research and Forecasting (WRF) Model is a next-generation
mesoscale numerical weather prediction system designed to serve both
operational forecasting and atmospheric research needs. It features multiple
dynamical cores, a 3-dimensional variational (3DVAR) data assimilation
system, and a software architecture allowing for computational parallelism and
system extensibility. WRF is suitable for a broad spectrum of applications
across scales ranging from meters to thousands of kilometers.
Initial and lateral boundary conditions, forecasts, 3dvar
NetCDF, HDF, GriB, binary
http://www.wrf-model.org/index.php
ARPA-SIMC
Global climate model, regional climate model
ARPA-SIMC, conducts observational and forecast operating and research and
development, meteorology, climatology, hydrology, agro-meteorology, radar
meteorology and environmental meteorology. ARPA environmental controls
and monitoring are performed through water control monitoring networks
(surface water and groundwater), sea monitoring service (chemical and
microbiological analysis), meteorological and atmospheric pollution
monitoring networks, specific measurement surveys about environmental
radioactivity and noise pollution.
Wind speed, precipitation, cloud cover, Ultraviolet radiation etc.
http://www.arpa.emr.it/sim/
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