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Supporting the Eindhoven University of
Technology to reach Thermal Energy Balance
at the Campus 2020
Student: J.G. Spruijt
ID: 0788803
Graduation date: 24 February 2015
Graduation Supervision Committee:
Prof.dr.ir. J.L.M. Hensen
dr. M.H. Hassan Mohamed
Mr. J.I. Torrens Galdiz
Unit Building Physics and Services,
Department of the Built Environment
University of Technology Eindhoven
Supporting the Eindhoven University of
Technology to Reach Thermal Energy Balance
at the Campus 2020
J.G. (Tjeerd) Spruijt
Supervised by: J.I. Torrens, J.L.M. Hensen
Unit BPS
Eindhoven University of Technology
Eindhoven, the Netherlands
[email protected]
NOMENCLATURE
1.
AER
ATES
BTES
CTES
MBE
MJA
RE
RMSE
TES
TU/e
UNFCCC
Every building requires a certain amount of energy, to keep
the indoor climate at a comfortable level. This amount of
energy depends on the outdoor climate and the buildings
properties. This amount of energy (cooling or heating
demand) is different for every building. When a building
requires cooling in summer and heating in winter, a mismatch
in time exists [4]. If said in another way, this might sound
even more obvious:
When in summer thermal energy (heat) has to be removed
from a building, and in winter thermal energy has to be
supplied to that same building, a mismatch in time exists.
UTES
Annual Energy Report
Aquifer Thermal Energy Storage
Borehole Thermal Energy Storage
Cavern Thermal Energy Storage
Mean Biased Error
Multiple Years Agreement
Real Estate department of the TU/e
Root Mean Square Error
Thermal Energy Storage
Eindhoven University of Technology
United Nations Framework Convention on
Climate Change
Underground Thermal Energy Storage
INTRODUCTION
1.1. Thermal Energy Storage
To overcome this mismatch, the thermal energy can be
stored and made available for recovery when the energy is
required. This is possible with a Thermal Energy Storage
(TES). Storing thermal energy for a larger time then a few
hours would require a large amount of insulation material to
prevent the thermal energy from escaping the storage. Instead
of using insulation material, an environment with a constant
temperature like the ground can also be used to keep the
energy from escaping, a system like this is called an
Underground Thermal Energy Storage (UTES) [5] [6]. There
are different types of UTES’s possible; ATES (Aquifer),
BTES (Borehole) and CTES (Cavern) [7] [8]. The type of
storage to use in the Netherlands is not difficult to choose, as
aquifers (water-containing layers between two impermeable
layers) are commonly available in the whole country. This is
the reason why the ATES systems are becoming more and
more popular in the Netherlands. It is even expected that in
the year 2020 around 20.000 of these systems will be
operative [2].
The ATES system can be carried out in two ways, a
closed system or an open system. The closed system is a Ushaped tube inserted in the ground. A liquid of a certain
temperature is send through the tube. Depending on the
ground water temperature in the aquifer and the temperature
in the tube, the system will extract/provide thermal energy
from/to the aquifer. The open system extracts groundwater of
a certain temperature, with the countercurrent principle
thermal energy is extracted/provided to the groundwater and
the water is then reinjected in another well with another
temperature.
ABSTRACT
Every building requires a certain amount of heating or
cooling, whenever a building requires cooling (heat removal)
in summer and heating (heat supply) in winter, a mismatch in
time exists. A solution to this problem could be to store the
thermal energy on a seasonal period. In the Netherlands water
containing ground layers (Aquifers) are often used to store
the energy because of their common availability [1]. It is
expected that in 2020 a quantity of 20.000 ATES systems be
applied in the Netherlands, while there were around 2.000
applications in the year 2011 [2]. One of the largest ATES
systems in the Netherlands is located on the campus of the
Eindhoven University of Technology (TU/e). This system has
been providing the TU/e with warm and cold water for the
last 13 years. During this time two cooling towers have been
emitting heat into the air to overcome the difference between
the heat and cold extraction. The last few years the TU/e has
made plans to renovate the campus and its real estate [3]. This
renovation might be the opportunity to create a better
balanced ATES system. To do this, computational
simulations were used to research the current and future
balance in the heating and cooling demand of the TU/e
buildings real estate. The result of the research shows that the
TU/e real estate in 2020 will have a larger cooling than
heating load. Some solutions are mentioned which could help
decrease the mismatch
Keywords—Aquifer, ATES, Dymola, Low Grade Energy,
Modelica, TES, Thermal Energy Storage.
1
On top of this, the provincial water plan of Noord-Brabant
[16] states that both heat and cold are used, only in
exceptional cases discharge to the air or surface water is
allowed to create a balanced situation underground.
The most common reason to choose for the application of
a TES system is to reduce the energy use of the building.
Since a TES system stores the energy, it can be reused later
with only a small amount of extra energy. The storage uses
multiple wells, and is thus able to store both heat and cold, so
in winter less gas is necessary to heat the building and in
summer less electricity is needed to cool the building.
When the United Nations signed the United Nations
Framework Convention on Climate Change (UNFCCC) [9]
in 1992, a promise was made to prevent the increase of
greenhouse gas emissions. Even stricter promises were made
in the Kyoto-protocol [10], this protocol set the goal to
reduce the production of greenhouse gasses instead of
reducing the growth of the emissions. In response to these
worldwide goals, the Eindhoven University of Technology
(TU/e) made its own plan. The TU/e aimed to improve the
energy efficiency by 20% between 1996 and 2006, to reach
this goal, a large scale ATES was applied in 2002 to provide
in the cooling and heating demand for the TU/e buildings
located on the campus [11].
1.3. TU/e Campus
The TU/e is one of the three technical universities located in
the Netherlands and provides education for around 8.000
students and 1.200 PhD students. The university buildings are
located on a campus of 121 hectares near the center of the city
Eindhoven.
The ATES system located on the TU/e campus is a large
open circuit system created out of 32 wells (16 cold and 16
warm) divided over 6 clusters (3 cold and 3 warm) [Figure 1]
[11]. The clusters are connected to each other making use of
two ring tubes (cold and warm), the rings are kept at around
6°C and 18°C under a pressure of 2.5 bar. With this ring
system buildings can extract or supply heat and cold at the
same time. The most common heat and cold delivery system
at the TU/e is direct cooling and heating via a heat pump, in
most cases a peak load system with boilers is installed to deal
with outdoor temperatures below -5°C. Figure 3 is a
schematic representation of this type of system.
1.2. Regulations on ATES
Since an ATES system makes use of a common source (the
freshwater), it is bound to some regulations. These
regulations are there to prevent someone from making a
common source unavailable to others [12]. A number of
regulations are applied to the use of an ATES system in the
Netherlands. These regulations are contained in the Water act
[13] , the Milieu act [14] and the official gazette of the
Netherlands [15] which states that:
“An open ground energy storage system reaches a moment
where there is no excess heat within 5 year after first use and
repeats this within 5 year after the last time this situation
occurred.”
Excess heat as used in this law occurs when the total
amount of thermal energy which is infiltrated into the ground
is larger than the total amount of thermal energy that is
extracted.
Figure 1: The six clusters of the TU/e ATES system [IF
Technology]
Energy [MWh/year]
TU/e ATES Extraction
8.000
6.000
4.000
2.000
0
-2.000
-4.000
-6.000
-8.000
-10.000
-12.000
30%
49%
21%
2003
Cold use
-8.384
Heat use
332
Heat extraction CT
0
Cum. Imb. according to AER
0
2004
-8.407
2.393
5.323
-691
2005
2006
2007
-8.882 -10.505 -9.400
3.384 4.316 3.200
4.326 4.858 3.900
-1.863 -3.194 -5.494
2008
-8.360
4.460
4.800
-4.594
Time [Year]
Figure 2: Energy extraction from the ATES
2
2009
-9.180
3.600
5.110
-5.064
2010
-8.124
4.350
5.690
-3.148
2011
-8.922
3.634
5.080
-3.356
When the TU/e ATES system was created in 2002, twelve
buildings were connected to the system. Ten of these
buildings are combined users, one is only using heat and one
is only using cold. The buildings have different functions,
sports, education, research and related business.
Since the European Union has set new goals [17], the TU/e
is required to make some changes in its real estate collection.
A plan “Campus 2020” was made to renovate the campus
before the year 2020. The plan includes a number of measures
like a reduction of 60.000m2 in floor area and renovation of
existing buildings to come to an energy neutral campus.
Another step to make is the increase in efficiency of the
ATES system, which is possible because the twelve buildings
that are connected are together not in a thermal energy
balance. This problem is currently overcome using two
cooling towers. Figure 2 shows the energy extraction from the
ATES over the years 2003-2011.
currently renovating, this might be the moment to research if
and how a thermal balance can be found in the TU/e real
estate/ATES. To do this, the heating and cooling energy
demand of the buildings has to be known. Real measurement
data will be used as well as simulation based performance
analysis of the different TU/e buildings to check what the
heating and cooling demand of the buildings is or will be after
renovation.
2.
METHODS
The TU/e campus covers 121 hectares and tens of buildings
are located on this campus. Some of these have been
connected to the ATES since the ATES was created. To get
an overview of the last 13 year that the ATES system was in
production, the available data of all buildings will be
analyzed, mainly focusing on the total ATES balance. The
amount of heat or cold extracted for use and the heat extracted
for the cooling towers will be analyzed to see what the actual
imbalance is.
2.1. Classification of buildings
To create some overview in the wide range of buildings
located on the TU/e campus four partitions were made, of
which one can directly be excluded as it contains the
buildings that are not and will not be connected to the ATES
system.
The division is based on data from the Annual Energy
Reports (AER) of 2003-2010 [19]–[26] and the Management
review Multiple Year Agreement Energy Efficiency TU/e
[27]. These documents contain the annual energy
consumption per building in gas, water, ATES cold and
ATES heat. For determination of the future ATES users, the
pamphlet “TU/e science park” is used [28].
According to these documents, twelve buildings were
connected to the ATES one year after it was built in 2002. Of
these twelve buildings, only seven will remain the same
between 2010 and 2020, the other five will be changed,
renovated or demolished. Nine buildings will be newly
connected to the ATES system before 2020. The division of
the buildings over the groups is given in -3.
2.1.1. Group 1
The first group contains seven buildings that are still
connected, and will not be getting a renovation before 2020.
For this group; a lot of measurement data is available, as well
as architectural drawings and installation schemes. Since a lot
of real data is known for these buildings, they are simulated
with a computational model. After simulation they are
calibrated using the simulation results and the measured data.
The calibrated model is used as a guide for the other
buildings.
Figure 3: Schematic representation of the Heating and cooling
installation of Vertigo [18]
1.4. Research
As a response to the new European goals, the TU/e created
its own plan to come to an energy neutral campus. Part of this
plan is the “Campus 2020” which is a plan to increase the
energy efficiency and decrease the carbon emissions. This
large renovation of the TU/e campus is happening as we
speak. The renovation of the campus includes multiple
buildings that are currently energy inefficient, as well as the
optimalisation of installations like the ATES system. This
system is currently unbalanced and two cooling towers are
used to balance out the ATES. This is a waste of thermal
energy, as well as electricity and money. Since the TU/e is
Figure 4: Group 1, 2 and 3 on campus
3
Table 1: TU/e buildings divided into groups
1
Sportcentrum
Auditorium
Vertigo
Groups
2A
2B
Ceres
Hoofdgebouw
Metaforum
Potentiaal
GeminiSpectrum
Noord
Matrix
Laplace
Helix
Cyclotron
Kennispoort
Catalyst
demand. The other three buildings are new connections to the
ATES since 2011, this means that two or three years of
measurement data of these buildings is available. For the first
two buildings some calculations will be done to tell what the
amount of cooling or heating energy will be, for the other
three the measured data will be used as the energy demand
for those buildings.
Group B of the second group is made out of buildings that
will be fully renovated. Two of these buildings were already
connected to the ATES (Gemini Noord and Gemini Zuid), so
measurement data is available for those. The other two will
be new connections to the ATES, gas and electricity data is
available of these buildings, so this can be used. These four
buildings will be simulated using the same model as group
one, the real measured data of the un-renovated buildings will
be used to make a comparison with the simulation results.
This comparison will give an estimation of the trend in the
building heating and cooling demand.
2.1.3. Group 3
Third is a group with buildings that are being built at the
moment, are just finished or will be built in the near future.
Some estimations may be made of these buildings, however
no data is available of these four buildings.
3
Flux
Differ
Vestide
toren
Studenten
dorp
Gemini-Zuid
2.1.2. Group 2
Group 2 contains existing buildings as well, of these
buildings some will receive just minor changes or have been
connected to the ATES recently, others will receive a
complete renovation before 2020. The group is thus split into
two parts, A and B.
Group A contains five buildings of which two already have
a connection to the ATES system, however some changes
will be made in the buildings resulting in a changed energy
Table 2: Basic information Group 1 [29]
GROUP 1
Name
Sportcentrum
Auditorium
Vertigo
Matrix
Helix
Cyclotron
1966
1995
1965
2002
1960
N/A
1996
N/A
1967
2001
Academic
Academic
Academic
Academic
Academic
5864
16098
3660
16124
5026
Kennispoort
Image
Year
Renovation
Function
Functional
Floor Area
1967
2001
Retail and
leisure
7169
2002
N/A
Related
Business
6708
Table 3: Basic information Group 2A and 2B
GROUP 2A
Ceres
1959
2012
Related
Business
49
Metaforum
Spectrum
Laplace
Catalyst
1959
2013
2002
N/A
1972
N/A
Academic
Academic
Academic
2012
N/A
Related
Business
10531
4431
5534
4
Hoofdgebouw
GROUP 2B
Gemini
Potentiaal
Zuid
Gemini
Noord
1963
2015
1963
N/A
1974
N/A
1974
1999
Academic
Academic
Academic
Academic
24014
10995
11764
8825
The third group (2B) is simulated using the same calibrated
model of group 1, the current un-renovated building is the main
input for this model. Then the insulation values of the most
recent Dutch Building Code [Table 4] will be applied to the
model, and the function change is kept in mind.
2.1.4. Group 4
The fourth group exists out of buildings that are not and will
not be connected to the ATES, as this group has no influence
on the balance of the TU/e ATES the group will not further be
mentioned. Further information about each building is available
in appendix 2
2.2. Data analysis
The creation of the ATES system started in 2002, in this time
a number of buildings were directly connected to the ATES,
creating a load on the system. At the same time two cooling
towers were used to counter the calculated imbalance. Data
about the ATES can be found in the Annual Energy reports
[19]–[26] and the Multiple Year Agreement Energy Efficiency
TU/e [27]. The data measured of the ATES contains heat and
cold extraction per building, heat extraction for the cooling
towers, electricity and water.
Since group 1 and 2 [Table 1, Table 2, Table 3] contain only
existing buildings, real measurement data is available for each
one of these buildings. This data has been extracted from the
real estate servers as well as MYA [27] documents and AER
[19]–[26]. Only measurement data since 2002 are needed since
that is when the ATES was applied. The year 2011 will be used
as the simulation year because this is the last year that only the
first connected buildings were applied to the ATES, after this
year new buildings have been connected, and other buildings
have been demolished which influences the ATES.
The measured data contains hourly measurements of the
ATES as well as gas, electricity and water use. Most buildings
are supplied with sensors for the HOK, HLK and
HRK which are the main electricity sensors for fluctuating,
lighting and constant power. The fluctuating power net supplies
energy to elevators and installations, the lighting power is for
the light net, and the constant power is used for measurement
equipment. For some buildings extra sensors are applied for
specific parts, like a heat pump electricity sensor in the Vertigo
building. If this is the case, the coefficient of performance
(COP) can be used to calculate the production of the heat pump.
The gas use can be multiplied with the caloric energy of the gas
and a boiler efficiency.
Figure 5: ISO-13790 model (5R1C) [30]
Table 4: Dutch building code requirements
Residential
Commercial
U-value
Wall
[W/m2K]
U-value
Roof
[W/m2K]
U-value
Floor
[W/m2K]
0.4
0.22
0.4
0.167
0.4
0.286
The simulated energy demand from all groups is combined
to analyze what the balance without new buildings will be. This
will give an indication if the new buildings will need to use
more heat or cold energy from the ATES. The new buildings
will be discussed and finally some possible measures will be
named.
3.
RESULTS
The data analysis of the ATES, shows that there is a small
imbalance in the yearly heat and cold extraction [
Figure 2]. In this data the heat extraction by the cooling towers
is not seen as an imbalance but as extraction, and with it the
annual imbalance is around 1 to 2GWh. If the cooling towers
are seen as imbalance (it is available heat), the imbalance would
be around 5 to 6GWh.
When the average annual ATES energy demand per building
is calculated [Figure 6], it shows that three buildings stand out
due to their large influence on the ATES system, these buildings
are; Helix, Cyclotron and Spectrum. These are three laboratory
facilities located on the TU/e campus.
2.3. Model
De collected data will be used for the computational
simulations using Dymola, which is a simulation environment
in the open Modelica modelling language. The model used is
based on the ISO 13790- which is a five resistances 1
capacitance (5R1C) model [Figure 5] [30]. Extra additions to
this model are a user schedule, ventilation with heat recovery
and weather influences, the computational code of the model
can be found in appendix 1 [31].
A base load is calculated using computation simulation
models of the first group, this group is calibrated with the real
measured data. This base load represents the load that has
always been and will be present, from this point the balance is
checked. The second step is to add group 2A, this is possible by
adding the measured data, which is available for 3 of the 5
buildings since they are already in use.
The other two buildings will receive minor changes in their
system, resulting in a different energy demand towards the
ATES system.
5
3.2. Simulation results
The first building simulated is the Vertigo building, this
building was chosen due to the large amount of sensors and
measurement data available. A description and schematic
representation of the installation system were retrieved from the
FAGO report [18] [Figure 3]. The base load for heating is
provided by the ATES via a heat pump, if this is insufficient
(exterior temperature -5°C) then the two gas-fired boilers can
step by. The cooling is done directly, the ATES provides
cooling to the ventilation system. As an extra cooling option the
heat pump can be used in reverse mode. This system is not in
detail implemented in the model although it would be possible
it would increase the simulation time.
Av. perc. of annual energy use
per building (2003-2013)
Cold usage [MWh/year]
3.000
2.500
11%
2.000
1.500
1.000
12%
17%
06%
3.2.1. Data modification
As an example the Vertigo building is used in this article. The
real measured data of the Vertigo building contains gas, ATES
warm, ATES cold and electricity for the heat pump. The total
amount of heat is calculated with the following steps:
- Gas use multiplied by 9. This value is the result of the
caloric value of gas which is approximately 32MJ/m3
[32] multiplied by the efficiency. 1kWh is equal to
3.6MJ so, 1m3 of gas can provide 8.88kWh with an
optimal combustion efficiency of 100% the
conversion value was estimated at 9.
- The heat energy provide by the ATES is already in
kWh_thermal and can be added after a check if the
measured values of the real estate department are the
same as the values provided in the AER.
- The electricity use of the heat pump is a more difficult
story this is split between the heating and cooling, if
cooling exists without heating, then the electricity for
the heat pump is multiplied by 5 (EER) and otherwise
it is multiplied by 4 (COP). [33]
07%
04%05%
50003%
01%
02% 04%
01% 03%
0 00%
0
0
500 1.000 1.500 2.000 2.500 3.000
Heat usage [MWh/year]
Sportcentrum
Auditorium
Ceres
W-hal / Metaforum
Vertigo
Matrix
Helix
Catalyst
Cyclotron
N-Laag / Flux
Spectrum
W Hoog / Gemini zuid
W Laag / Gemini noord
Laplace
Kennispoort
Figure 6: Percentage of total use per building
3.1. Schedules
To be able to create a user schedule in the simulation model,
a plot is made of the weekly and daily energy demands. The
third week of January was chosen as this is a normal week.
These plots for each of the buildings of group 1 are added to
appendix 2. For the Auditorium building a measurement error
was found [Figure 7] in the data. This is the ATES which
collected data when 1.000kWh was provided instead of the
hourly value. Another week of the same year shows correct data
[Figure 8].
6
Energy demand
[kWh/hour]
Auditorium Week
1500
1000
500
Total cold
0
15 Jan 2011 16 Jan 2011 17 Jan 2011 18 Jan 2011 19 Jan 2011 20 Jan 2011 21 Jan 2011
0:00
0:00
0:00
0:00
0:00
0:00
0:00
Total heat
Time [day]
Figure 7: Auditorium weekly schedule data error
Energy demand
[kWh/hour]
Auditorium Week
600
400
200
Total cold
0
19 Nov 2011 20 Nov 2011 21 Nov 2011 22 Nov 2011 23 Nov 2011 24 Nov 2011 25 Nov 2011
0:00
0:00
0:00
0:00
0:00
0:00
0:00
Total heat
Time [day]
Figure 8: Auditorium weekly schedule correct data
To calibrate the model (get a better RMSE/MBE) the
calibration signature [Equation 3] and characteristic signature
[Equation 4] can be used [Figure 10 and Figure 11], these are
ways to see what effect a changed parameter has on the
simulation results. Since a low resolution model is used, the
data is fluctuating a lot, and instead of the expected line, a
cloud was found as the calibration signature. To see which
parameters had to be adjusted, a trend line was plotted into the
graphs. Calibration signatures can be found for every
simulated building in appendix 3.
3.3. Calibration of the model
The errors in the comparison between the measured and
simulated data [ Figure 9] can be due to the input values,
which were assumed to be correct. This doesn’t have to be the
case, and thus the model has to be calibrated.
For calibration of the model, first the Root Mean Square
Error (RMSE) is used [Equation 1], an important note here may
be that since a low-resolution model is used, the RMSE will
never get as low as 20. After solving the errors in the model, the
first simulation delivered a RMSE value of 45 for cooling and
56 for heating. The unit of the RMSE is kWh, and since it is
calculated using the daily average, the value is in kWh/day.
Since the ATES should be balanced once every 5 year [15],
the focus is not on the hourly or daily error, the yearly error is
detailed enough. Thus the MBE [Equation 2] might be useful as
well. The MBE uses the daily error as well, the difference with
this and the RMSE is that the negative and positive errors
eliminate each other in the MBE, while the RMSE uses both as
a positive error. The residual in these equations is the result of
the simulated minus the measured hourly data.
=
Equation 1: RMSE-value [34]
=
∑
=
!
−
! !
Equation 3: Calibration signature [34]
ℎ
'
'
=
ℎ
"'
!(
! !
"'
!(
Equation 4: Characteristic signature [34]
/2
∑
Equation 2: MBE-value [34]
7
"
100%
100%
Daily average energy demand
[kWh/day]
Vertigo Uncalibrated
Cold
600
500
400
300
Measured_cold
200
Simulated_cold
100
0
0
20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360
Time [day]
Daily average energy demand
[kWh/day]
Vertigo Uncalibrated
Heat
600
500
400
300
Measured_heat
200
Simulated_heat
100
0
0
20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360
Time [day]
Figure 9: Un-calibrated annual energy demand Vertigo
These calibration signatures show that the cooling has to
increase when outdoor temperature is high and the heating has
to increase when the outdoor temperature is low.
Different parameters are then changed to see what would be
of correct influence on the results. The calibration signature is
calculated with the first simulation as a baseline.
The final result is a calibrated model with a certain RMSE/MBE
value as close to zero as possible. Table 5 shows the RMSE and
MBE values for the buildings of group 1.
The calibrated model is found when a combination of
different measures is made. This building was eventually
calibrated with a RMSE of under 50 for both heat and cold, and
an MBE around -3. The annual cooling demand [Figure 12] and
the annual heating demand [Figure 13] show a great similarity
with the measured data.
All buildings of group one were calibrated in this way, the
results of these calibrations can be found in Table 5.
Vertigo Cal_Sig_cold
Cold water [%]
100
-20
50
0
-10
0
-50
10
20
30
40
50
Temperature [°C]
Figure 10: Cooling calibration signature for Vertigo
Vertigo Cal_Sig_heat
Hot water [%]
60
-20
40
20
0
-10
-20
0
10
20
30
40
50
Temperature [°C]
Figure 11: Heating calibration signature for Vertigo
8
Daily average energy demand
[kWh/day]
Vertigo Calibrated (Cold)
600
500
400
300
Measured_cold
200
Simulated_cold
100
0
0
20
40
60
80 100 120 140 160 180 200 220 240 260 280 300 320 340 360
Time [day]
Figure 12: Annual cooling demand calibrated model
Daily average energy demand
[kWh/day]
Vertigo Calibrated (Heat)
600
500
400
300
Measured_heat
200
Simulated_heat
100
0
0
20
40
60
80 100 120 140 160 180 200 220 240 260 280 300 320 340 360
Time [day]
Figure 13: Annual heating demand calibrated model
Table 5: Calibration data group 1
RMSE
Cold
RMSE
Heat
MBE
Cold
MBE
Heat
[kWh/day]
[kWh/day]
[kWh/day]
[kWh/day]
Sportcentrum1
0
31
0.00
Auditorium
22
45
-1.23
Vertigo
45
45
-2.42
Matrix2
118
49
-80.00
Helix2
45
236
-1.09
Cyclotron1
26
33
0.33
Kennispoort2
N/A
N/A
N/A
1
A base load was removed during the simulation
2
These buildings have not been calibrated
Table 6: Total demands versus ATES demands
-0.55
-3.36
-3.32
-17.00
-18.20
-0.32
N/A
Sportcentrum
Auditorium
Vertigo
Matrix
Helix
Cyclotron
Kennispoort
TOTAL
3.3.1. First group
The measured/simulated data exists out of 2 parts, the
gas/electricity and the ATES. Out of the measured data, the
percentage of energy that was delivered by the ATES can be
calculated. Vertigo is the only building where the electricity
towards the heat pump is measured, so this would be the most
precise measured data. Out of this data a percentage of around
90% is coming from the ATES for cold, and around 50% for
heat. For large users like Helix and Cyclotron the heat part is
around 65% and for small users like Auditorium and Matrix a
percentage of 16 is reached.
Sportcentrum
Auditorium
Vertigo
Matrix
Helix
Cyclotron
Kennispoort
TOTAL
9
Total
Cold
ATES
Cold
COLD
[MWh/year]
[MWh/year]
[%]
0
200
597
831
1018
1451*
397
4494
0
200
530
831
1018
1432
397
4408
N/A
100
89
100
100
100
100
98
Total
Heat
ATES
Heat
Heat
[MWh/year]
[MWh/year]
[%]
950*
910
856
1682
5773
1524
683
12378
216
147
461
263
2701
1298
0
5086
18.5
16.15
54
15.6
46.8
85
N/A
40
3.4. Second group
3.4.1. Part A
The second group exists out of two groups, group A is a group
where not a lot will change, and/or buildings which are already
renovated. Group B is the group with buildings that will be
renovated before 2020.
Group A contains the Metaforum (former W-hal), Ceres and
Catalyst, these buildings are already built/renovated and have
been measured over the last 3 year. The measurement data of
2013 of these buildings will be used to estimate the balance of
the ATES system, this year was chosen as it has the least startup
errors. The result when group 2A is added is given in Part B
Group A contains the Spectrum building and Laplace, both
of these buildings will undergo some changes which will
influence the energy demand of the buildings. The Spectrum
building is currently cooled using cooling machines, these
machines are working fine, but a more efficient option with the
chillers working as heat pumps is possible. A new building
named Flux (former N-laag) will be using a lot more cold than
heat, as a compensation project for this new building, the
cooling machines of Spectrum will be changed for heat pumps,
making it possible to reduce the gas use by 70%. This leaves the
question where the compensation project for the Spectrum
building itself is, as it has a larger cooling demand than heating
as well. The heat normally provided to the building through the
boilers, will now be provided by the heat pumps. A simple
calculation can be done to calculate the extra heat that will be
extracted from the ATES.
Spectrum used 258.000m3 of gas in 2011, this is comparable
to 258000 * 9 = 2.322.000 kWh_thermal. 70% of this is
1.625.400kWh_thermal energy that will be extracted extra from
the ATES in the future.
The total energy demand of the existing buildings is shown in
Table 7.
3.4.2. Part B
Group 2B are four buildings that will be renovated between
now and the year 2020, these buildings are: Potentiaal,
Hoofdgebouw, Gemini South and Gemini North. Of these
buildings the façade area’s and floor surfaces are calculated
using the buildings architectural drawings [appendix 2]. And
the insulation parameters of the Dutch Building Code are used
(Table 4).
Potentiaal will have a function change, this building will
house students and expats, so the function will be residential.
In a decree of 2007 from the RE department [35], a few
decisions for new and to be renovated buildings were made. The
buildings concept should use the following steps in this order:
- Reduction of glass percentage max 20-40%
- Reduction of solar transmittance using a sunscreen or
G-value <0.4
- Make use of the heat accumulating properties of the
building.
- Use summer night ventilation
- Reduction of internal heat gains
- Heat producing machines are placed in separate
rooms
The window to wall ratio for the simulation of Potentiaal has
been set at 30%, and the glazing has a G-value of 0.35. The full
floor height is calculated as part of the zone, which would make
use of the heat accumulating properties of the building. A user
schedule has been programmed as nigh/daytime schedule: 7
days per week the day schedule from 8:00 till 23:00, the
ventilation is doubled, as the students will be active, during
night time the ACH is 1, which is exactly the minimum amount
ventilation according to the Dutch Building Code. The internal
gains have been set on 30W/m2, as the TU/e buildings of group
1 have an internal heat gain of around 30W/m2.
For the other 3 buildings the same values are used, the
schedule is changed into the academic schedule. The results of
these simulations have been modified using the percentage of
cold from the vertigo building (90%) and the average
percentage of heat (40%). After this modification, they have
been added to Table 8.
Table 7: ATES energy demand groups 1 and 2A
Sportcentrum
Auditorium
Vertigo
Matrix
Helix
Cyclotron
Kennispoort
Subtotal
CERES
Metaforum
Spectrum
Laplace
Catalyst
Subtotal
TOTAL
Group
1
Group
2A
COLD
HEAT
[MWh/year]
[MWh/year]
0
200
530
831
1.018
1.432
397
4.408
28
321
2.780
191
116
3.436
7.844
216
147
461
263
2.701
1.298
0
5.086
48
379
1.625
13
553
2.618
7.704
Table 8: Group 2B simulated according to Dutch Building Code and
with heat recovery
Subtotal
Hoofdgebouw
Gemini Zuid
Gemini Noord
Potentiaal
Subtotal
TOTAL
Laplace is built as the server building, when a computer
needed a whole building for itself. Nowadays only a small
amount of servers is left in this building, RE confirmed that the
servers will be removed and placed at the High Tech Campus
(HTC) this will decrease the cooling demand of this building.
10
Group 1
+2A
Group
2B
COLD
HEAT
[MWh/year]
[MWh/year]
7.844
7.704
1.547
471
351
248
2.617
10.461
64
11
12
63
150
7.854
3.5. Third group
The third group contains the Vestide tower (Residential),
the student village (Residential), Flux (Academic) and Differ
(Related business). As Table 8 shows, the trend is to require
more cooling than heating.
The Vestide tower will provide space for 300 residential
units, which is the same as the future residential building
Potentiaal. The building is almost the same height as the
Potentiaal building, and will have the same shape. Thus it is
assumed that the Vestide tower will have the same energy
demand as the Potentiaal building after its renovation.
Flux is built at the moment, it will be an academic building
housing the electrical engineering and the applied physics
departments. Since the Flux is imbalanced, the Spectrum
building will be adjusted as a compensation project. The amount
of thermal energy that Spectrum is compensating for is
1.265.400kWh, so the cooling demand for flux will be at least
this amount higher than its heating demand.
Differ is a new research facility for the research into cleaner
energy for the future. The building is not TU/e property, and
thuse not the same designing principles have been applied. The
amount of glazing is definitely more than 30%, and although the
triple glazing should be placed in a direction to avoid direct
sunlight entering the building it looks like the evening sun will
be entering anyway.
The residential student village will contain multiple low two
story buildings. As cooling is not a requirement for Dutch
residential buildings, these buildings will probably not be
cooled using the ATES. These assumptions are taken into
account in Table 9.
4.2. Simulation
Figure 7 shows an error in the measured data of the ATES for
the Auditorium building, this was in 2011 the case for the
month’s January, February and December. It was tried to use
the data of 2012 instead, however during that year the gas sensor
was not working, and no gas data was available. The 2011 data
was used and as the average of the daily consumption was used
it is expected that no large errors occur as a result of this
measurement error.
Table 5 shows the calibration results of group 1, as visible
not all buildings have been calibrated. This is due to some data
issues.
4.2.1. Combined heating system
The Helix and Matrix buildings show large errors in the
calibration results. These errors may be due to the measured
data for the heating system. The buildings share the same
heating system (boilers), the thermal energy is then transported
from one building to the other. The data provided the total
amount of gas for both buildings together, and the annual gas
load for each building. Out of the annual gas load, the
percentage of gas for each building was calculated and used to
transform one set of hourly gas data into hourly data for each
building. The error here might be that one building might need
a lot of gas during a certain period, where the other might need
it in another period, this would result in an error as the
“measured” and the simulated data will not line up. It should be
noted that although Helix shows large errors, it is also a large
consumer, so the error might only be a small amount of the total.
4.2.2. Simplified model
Another thing is that the Sportcentrum only uses the ATES
to heat up the swimming pool, as the swimming pool is not
simulated in the simplified model, it was chosen to remove the
energy provided by the ATES from the measured data, and add
it later to the simulated data.
4.2.3. Single zone
The cyclotron building uses a lot of heat and cold, this cannot
be simulated using the single zone model as it would need to
simulate heat and cold at the same time. To overcome this the
average hourly cooling demand of the first week was used, and
removed from the measured data for each week of the whole
year. This amount of cold energy was later added back to the
measured data as well as the simulated data.
4.2.4. Group 2A
Two buildings of the second group will undergo some
changes during the renovation of the campus, these are
Spectrum and Laplace. The heating for spectrum has been
estimated using a change in the heating provided by the ATES.
The change in the Laplace building will be the removal of the
servers which are located in this building. This will reduce the
cooling load of the building, this has not been taken into
account.
4.2.5. Group 2B
The second part of group 2 contains buildings that have been
simulated to estimate what the heating and cooling load will be.
The current buildings properties like floor area have been taken
as the starting point, and some values have been changed to
fulfil the current building standards. If something would change
in the design of these buildings, like the total floor area, the
heating and cooling demands will change.
Table 9: Cold and Heat demand from the ATES group 3
COLD
HEAT
[MWh/year]
[MWh/year]
Vestide toren1
248
63
Student village1 Group
0
Flux1
3
1.625
Differ1
TOTAL
1.773
63
1
Not enough data available for more detailed estimations
4.
DISCUSSION
4.1. Balance
Currently the ATES is imbalanced and according to the
regulations all heat and cold should be used and cannot be
emitted into the air. As a result of this there is currently an
imbalance of around 6MWh/year when the cooling towers are
not taken into account.
The imbalance for the buildings of group 1 (base load) is a
lot better (46% cold 54% heat) than the original balance of 70%
cold versus 30% heat. When the renovated and new buildings
of group 2 are added, the imbalance increases again. This might
be due to the trend to increase the insulation (reducing glazing
is increasing insulation as well) of the buildings, resulting in a
lower heating demand and a higher cooling demand.
11
4.2.6. Group 3
Not enough data was available to be able to simulate group
3, thus estimations have been used to check what the imbalance
would be.
over the last 10 years, not all data is specific enough. To be able
to calculate the exact amount of heat or cold provided to a
building, electricity provided to the installation has to be
known. The total electricity can be found under the name HOK
(Main Operation Power) but this is a sum of all installations like
elevators, ventilation and heat pumps. Better would be to have
separate sensors for the heat pump, which is the case for the
Vertigo building but not for the other buildings. Since the
electricity could not be split, the heat pumps were not really
taken into account in the calculation of the total measured heat
and or cold.
Other issues with the data would be the missing data for
energy inserted into the ATES, and data about insulation values,
ventilation amounts and heat recovery, these have been
estimated during this research and adjusted during the
calibration process. It is recommended to increase the amount
of sensors to measure the energy supplied to the ATES as well
as the energy demand of the heat pump installations separately.
4.3. Solutions
4.3.1. Building level
Optimally the balance could be created by using more heat or
less cold energy from the ATES. This however would result in
an increase in electricity for cooling of the buildings, or a
reduction in the insulation of the buildings. Other options might
be to reduce the heat recovery in the buildings when a building
is heated, this is still inefficient use of the energy as heat is
brought into the air, but it will also decrease the amount of
cooling needed [Table 10]. Free cooling would also help, this
however could not be entered in the simulation model and is
thuse not simulated.
4.3.2. Campus level
On campus level it would be possible to increase the comfort
of the students and residents in the winter by deicing of the
foot/cycle paths. To keep the snow detached from the path
surface, 0.12kWh/m2 is required, for melting the snow
0.3kW/m2 would be needed [TAUW]. With an imbalance of
around 4GWh/y, around 33km2 could be ice-free for an hour,
divided by 2400 (100 days of cold in the Netherlands), makes
this around 14.000m2 This type of system would already have
been used in the Metaforum hall, but was canceled due to cost
savings.
With the compact campus the buildings are all reachable by
making use of the skyways. These could be heated in winter as
well, while in summer the skyways can be cooled using free
cooling.
Another solution would be to improve the TU/e community
garden, which is a 200m2 area used as a kitchen garden
(agriculture) [TU/e]. With the future residents on the TU/e
campus, there might be an increase in the demand for kitchen
gardens and with the large group of people of mixed descent it
might be interesting to create a large horticulture at the TU/e
campus. This could be heated using the ATES system and at the
same time function as a research facility for reduction in energy
demand for horticulture in the Netherlands.
4.5. Recommendations
4.5.1. Model resolution
During this research a low-resolution simulation program
was used, it showed that the buildings on the TU/e are too
complex to be simulated as a one zone model. It is thuse
recommended to make a high-resolution model of all buildings
to provide better insight in the energy flows in the buildings.
4.5.2. ATES measurement
Currently only the energy extraction from the ATES is
measured, and the balance has to be found in the extracted
data. Measuring the supplied energy to the ATES as well
might give a proper view into the underground balance. This
might help to control the extraction from the ATES and with
that the balance could be created.
5.
Table 10: Group 2B simulated according to the Dutch Building Code
without Heat Recovery
Subtotal
Hoofdgebouw
Gemini Zuid
Gemini
Noord
Potentiaal
Total
Group 1
+ 2A
Group 2B
COLD
HEAT
[MWh/year]
[MWh/year]
7844
7.704
530
146
224
83
161
104
118
8.899
197
8.312
CONCLUSION
Although some possible options have been given to come to
a balanced ATES, the goal, to provide a solution for the
imbalanced TU/e real estate for the year 2020, has not been met.
This research shows that more data is needed to make correct
estimations on the future balance.
The future campus 2020 will probably have a larger cooling
than heating demand according to the research results in this
article. This is mostly due to the fact that there is a trend in
increasing the insulation value of the buildings shell. A possible
solution has been provided in the shape of removing the Heat
Recovery of buildings that will be renovated [Table 10]. It
should however be mentioned that an increase in heating
demand would also mean an increase in electricity use. This
does not work in the same way for cooling, as cooling is used
directly instead of via a heat pump.
The estimation on the thermal energy balance of the TU/e real
estate does provide a guideline on how the energy demand will
develop.
Possible solutions will have to be further researched.
4.4. Data
Enough data is a key point in a research with real buildings,
although measurement data is available for all TU/e buildings
12
ACKNOWLEDGEMENTS
[33]
I would like to thank Thijs Meulen of the Real Estate
department and for his help with gathering data and information
about the future campus. Also I would like to thank all the
members of the TU/e CBPS department for their feedback and
guidance.
[34]
[35]
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Appendix 1
Modelica Dymola computational model code
Appendix 2
Modelica inputdata per building acquired from:
Building envelope: Architectural drawings
Indoor climate settings: Estimations
Schedules: Measured data
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Sportcentrum
0700
1967-2001
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
0.5/2 [m3/m2]
15 [W/m2]
(15/24)*100 [%]
6 [h]
19.5/21 [°C]
50 (no cooling) [°C]
9272 [m2]
4
8530 [m2]
7 [m]
1400/870/1400/870 [m2]
0.07/0.18/0.21/0.21
0.7
0.4 [W/m2*K]
1.53 [W/m2*K]
0.25 [W/m2*K]
0.4 [W/m2*K]
75 % fresh air
Energy demand [kWh_thermal]
Sportcentrum Week
600
500
400
300
Gas_heat
200
100
0
15 Jan 2011 0:00 16 Jan 2011 0:00 17 Jan 2011 0:00 18 Jan 2011 0:00 19 Jan 2011 0:00 20 Jan 2011 0:00 21 Jan 2011 0:00
Time [day]
Energy demand [kWh_thermal]
Sportcentrum Day (19-Jan-2011)
500
450
400
350
300
250
200
150
100
50
0
Gas_heat
1
2
3
4
5
6
7
8
9
10
11
12
13
Time [hour]
14
15
16
17
18
19
20
21
22
23
24
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Number of floors: 7
Auditorium
Roof area: 4406 [m2]
1300
1966
Floor height: 5.2 [m]
1995
Facade area N/E/S/W: 1479/853/1479/853 [m2]
3
2
Wtw ratio N/E/S/W: 0.35/0.54/0.35/0.54
3/5 [m /m ]
2
G-factor glazing: 0.7
32 [W/m ]
U-value walls: 0.4 [W/m2*K]
(13/24)*100 [%]
7 [h]
U-value windows: 1.53 [W/m2*K]
19.5/21 [°C]
U-value roof: 0.4 [W/m2*K]
U-value floor: 0.4 [W/m2*K]
22.5 (no cooling) [°C]
Heat Recovery 55% fresh air
5859 [m2]
Energy demand [kWh_thermal]
Auditorium Week
450
400
350
300
250
200
Total cold
150
Total heat
100
50
0
19 Nov 2011 0:0020 Nov 2011 0:0021 Nov 2011 0:0022 Nov 2011 0:0023 Nov 2011 0:0024 Nov 2011 0:0025 Nov 2011 0:00
Time [day]
Energy demand [kWh_thermal]
Auditorium Day (19-Jan-2011)
1400
1200
1000
800
600
Total heat
400
Total cold
200
0
1
2
3
4
5
6
7
8
9
10
11
12
13
Time [hour]
14
15
16
17
18
19
20
21
22
23
24
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Vertigo
5100
1965
2002
0.5/2.5 [m3/m2]
30 [W/m2]
(13/24)*100 [%]
6 [h]
19.5/21 [°C]
22.5 [°C]
16.098 [m2]
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
11
1454 [m2]
5.2 [m]
1790/3085/1830/3150 [m2]
0.73/0.59/0.71/0.61
0.35
0.4 [W/m2*K]
1.53 [W/m2*K]
0.25 [W/m2*K]
0.4 [W/m2*K]
70% fresh air
Vertigo Week
Energy demand [kWh_thermal]
800
700
600
500
400
Total_Heat
300
Total_Cold
200
100
0
15 Jan 2011 0:0016 Jan 2011 0:0017 Jan 2011 0:0018 Jan 2011 0:0019 Jan 2011 0:0020 Jan 2011 0:0021 Jan 2011 0:00
Time [days]
Vertigo Day (19 januari 2011)
Energy demand [kWh_thermal]
700
600
500
400
300
Total_Heat
200
Total_Cold
100
0
1
2
3
4
5
6
7
8
9
10
11
12
13
Time [hour]
14
15
16
17
18
19
20
21
22
23
24
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Matrix
5300
1960
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
2/8[m3/m2]
10[W/m2]
(14/24)*100 [%]
4[h]
19/21[°C]
23[°C]
7000[m2]
4
3059[m2]
2.05[m]
805/147/805/147[m2]
0.8/0.3/0.3/0.3
0.7
0.4[W/m2*K]
1.53[W/m2*K]
0.4[W/m2*K]
0.4[W/m2*K]
50% fresh air
Matrix Week
Energy demand [kWh_thermal]
1000
900
800
700
600
500
Total cold
400
Total heat
300
200
100
0
19 Nov 2011 0:00 20 Nov 2011 0:00 21 Nov 2011 0:00 22 Nov 2011 0:00 23 Nov 2011 0:00 24 Nov 2011 0:00 25 Nov 2011 0:00
Time [day]
Matrix Day (19-Jan-2011)
Energy demand [kWh_thermal]
700
600
500
400
300
Total cold
200
Total heat
100
0
1
2
3
4
5
6
7
8
9
10
11
12
13
Time [hour]
14
15
16
17
18
19
20
21
22
23
24
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Helix
5800
1996
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
11/16 [m3/m2]
50 [W/m2]
(24/24)*100 [%]
6 [h]
19.5/22 [°C]
23 [°C]
16.124 [m2]
6
2690 [m2]
3.60 [m]
1475/4643/1475-4643 [m2]
0.9/0.96/0.6/0.96
0.35
0.5 [W/m2*K]
1.1 [W/m2*K]
0.5 [W/m2*K]
1.7 [W/m2*K]
50% fresh air
Helix Week
Energy demand [kWh_thermal]
3000
2500
2000
1500
Total_Cold
1000
Total_Heat
500
0
15 Jan 2011 0:00 16 Jan 2011 0:00 17 Jan 2011 0:00 18 Jan 2011 0:00 19 Jan 2011 0:00 20 Jan 2011 0:00 21 Jan 2011 0:00
Time [day]
Energy demand [kWh_thermal]
Helix Day (19-Jan-2011)
2000
1800
1600
1400
1200
1000
800
600
400
200
0
Total_Cold
Total_Heat
1
2
3
4
5
6
7
8
9
10
11
12
13
Time [hour]
14
15
16
17
18
19
20
21
22
23
24
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Cyclotron
7100
1968
2001
10/12 [m3/m2]
50 [W/m2]
(14/24)*100 [%]
6 [h]
19/21 [°C]
23 [°C]
5.026[m2]
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
4
5006 [m2]
2.88 [m]
1187/528/1187/405 [m2]
0.3/0.15/0.33/0.22
0.35
0.4 [W/m2*K]
1.53 [W/m2*K]
0.25 [W/m2*K]
0.4 [W/m2*K]
0.75% fresh air
Energy demand [kWh_thermal]
Cyclotron Week
600
500
400
300
total cold
200
total heat
100
0
15 Jan 2011 0:00 16 Jan 2011 0:00 17 Jan 2011 0:00 18 Jan 2011 0:00 19 Jan 2011 0:00 20 Jan 2011 0:00 21 Jan 2011 0:00
Time [day]
Energy demand [kWh_thermal]
Cyclotron Day (19-Jan-2011)
400
350
300
250
200
total heat
150
total cold
100
50
0
1
2
3
4
5
6
7
8
9
10
11
12
13
Time [hour]
14
15
16
17
18
19
20
21
22
23
24
Name: Kennispoort
Number: 8800
Year of construction: 2002
Year of renovation:
ACH min/max: [m3/m2]
Internal gains: [W/m2]
Day length: (13/24)*100 [%]
Day start: 6 [h]
Heating setpoint min/max: [°C]
Cooling setpoint: [°C]
Useful floor area: [m2]
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
6.708 [m2]
9
[m]
[m2]
[W/m2*K]
[W/m2*K]
[W/m2*K]
[W/m2*K]
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Potentiaal
3100
1963
20?? [m3/m2]
1/2 [W/m2]
30
(13/24)*100 [%]
8 [h]
16/21 [°C]
25 [°C]
1460 [m2]
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
10.995 [m2]
16
3.20 [m]
1125/3060/1125/3060 [m2]
0.3/0.3/0.3/0.3
0.35
0.4 [W/m2*K]
1.1 [W/m2*K]
0.4 [W/m2*K]
0.4 [W/m2*K]
50% fresh air
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Hoofdgebouw
1100
1963
2015
0.5/2.5 [m3/m2]
30 [W/m2]
(14/24)*100 [%]
6 [h]
16/21 [°C]
25 [°C]
24.014 [m2]
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
15
3100 [m2]
9 [m]
766/6867/766/6867 [m2]
0.3/0.3/0.3/0.3
0.35
0.22 [W/m2*K]
1.1 [W/m2*K]
0.1667 [W/m2*K]
0.2 [W/m2*K]
50% fresh air
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Gemini Zuid
8100
1974
N/A
0.5/2.5 [m3/m2]
30 [W/m2]
(14/24)*100 [%]
6 [h]
16/21 [°C]
25 [°C]
1680 [m2]
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
7
4200 [m2]
2.93 [m]
2050/435/2050/435 [m2]
0.3/0.3/0.3/0.3
0.35
0.22 [W/m2*K]
1.1 [W/m2*K]
0.1667 [W/m2*K]
0.286 [W/m2*K]
50% fresh air
Name:
Number:
Year of construction:
Year of renovation:
ACH min/max:
Internal gains:
Day length:
Day start:
Heating setpoint min/max:
Cooling setpoint:
Useful floor area:
Gemini Noord
8200
1974
1999
0.5/3 [m3/m2]
35 [W/m2]
(14/24)*100 [%]
6 [h]
16/21 [°C]
25 [°C]
8.826 [m2]
Number of floors:
Roof area:
Floor height:
Facade area N/E/S/W:
Wtw ratio N/E/S/W:
G-factor glazing:
U-value walls:
U-value windows:
U-value roof:
U-value floor:
Heat Recovery
4
5575 [m2]
3.5 [m]
760/360/760/360 [m2]
0.3/0.3/0.3/0.3
0.35
0.22 [W/m2*K]
1.1 [W/m2*K]
0.1667 [W/m2*K]
0.2 [W/m2*K]
50% fresh air
APPENDIX 3
Calibration and Characteristic signatures per building
Building: Sportcentrum
RMSE_cold:
RMSE_heat:
MBE_cold:
MBE_heat:
0
31
0
-0.55
Sportcentrum Uncalibrated
Heat
600
Energy demand [kWh_thermal]
500
400
300
Measured_heat
Simulated_heat
200
100
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Sportcentrum
Sportcentrum
Char_Sig_heat
RH 0,75? (1)
Cali_Sig_heat
Un-calibrated
20
0
-20
-10
0
10
20
30
40
50
30
40
50
10
-5
0
-20
-10
0
10
20
30
40
50
-10
Error [%]
Error [%]
-10
-20
-15
-20
-30
-25
-40
-50
-30
Temperature [°C]
Temperature [°C]
Sportcentrum
Char_Sig_heat
Int 15? (25)
Sportcentrum
Cal_Sig_heat
Calibrated
70
20
60
10
50
0
40
-20
-10
20
10
-10
10
20
-20
0
-20
0
-10
Error [%]
Error [%}
30
-30
0
10
20
30
40
50
-10
-40
-20
-30
-50
Temperature [°C]
Temperature [°C]
Sportcentrum Calibrated (Heat)
450
Energy demand [kWh_thermal]
400
350
300
250
Measured_heat
200
Simulated_heat
150
100
50
0
0
20
40
60
80
100
120
140
160
180
Time [day]
200
220
240
260
280
300
320
340
360
Building: Auditorium
RMSE_cold:
RMSE_heat:
MBE_cold:
MBE_heat:
22
45
-1.23
-3.36
Auditorium Uncalibrated
Cold
300
Energy demand [kWh_thermal]
250
200
150
Measured_cold
Simulated_cold
100
50
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Auditorium Uncalibrated
Heat
500
Energy demand [kWh_thermal]
450
400
350
300
250
Measured_heat
200
Simulated_heat
150
100
50
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Auditorium
Cali_Sig_cold
Un-calibrated
Auditorium
Cali_Sig_heat
Un-calibrated
60
60
50
50
40
40
30
Error [%]
20
Error [%]
-20
30
10
0
-10
0
10
20
30
40
20
10
50
-10
0
-20
-10
0
10
-20
-30
-20
-40
-30
Temperature [°C]
40
20
10
20
50
40
50
0
-20
-10
0
10
-10
0
-20
0
10
20
-10
-20
30
40
50
Error [%]
Error [%]
40
Auditorium
Char_Sig_heat
HR 0,6? (1)
30
-10
30
Temperature [°C]
Auditorium
Char_Sig_cold
HR 0,6? (1)
-20
20
-10
20
-30
-40
-30
-50
-40
-60
-50
-70
-60
-80
Temperature [°C]
10
Temperature [°C]
30
Auditorium
Char_Sig_cold
Int 35? (25)
Auditorium
Char_Sig_heat
Int 35? (25)
30
60
20
40
10
0
20
0
-20
-10
0
10
20
30
40
-10
0
Error [%]
Error [%]
-20
50
10
20
30
40
50
30
40
50
-10
-20
-30
-20
-40
-40
-50
-60
-60
Temperature [°C]
Temperature [°C]
Auditorium
Char_Sig_cold
Vent x2? (0,5/2)
Auditorium
Char_Sig_heat
Vent x2? (0,5/2)
40
40
30
30
20
20
10
10
-10
0
10
20
30
40
Error [%]
Error [%]
0
-20
50
0
-20
-10
-20
-10
0
10
20
-10
-20
-30
-30
-40
-40
-50
-60
-50
Temperature [°C]
Temperature [°C]
Auditorium Calibrated
Cold
300
Energy demand [kWh_thermal]
250
200
150
Measured_cold
Simulated_cold
100
50
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Auditorium Calibrated
Heat
500
Energy demand [kWh_thermal]
450
400
350
300
250
200
150
100
50
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Measured_heat
Simulated_heat
Auditorium
Char_Sig_cold
Result
Auditorium
Char_Sig_heat
Result
60
60
50
40
40
30
-20
0
-10
0
10
20
30
40
50
-20
-20
20
Error [%]
Error [%]
20
10
0
-10
0
10
20
-10
-20
-40
-30
-60
Temperature [°C]
-40
Temperature [°C]
30
40
50
Building: Vertigo
RMSE_cold:
RMSE_heat:
MBE_cold:
MBE_heat:
45
45
-2.42
-3.32
Vertigo Uncalibrated
Cold
600
Energy demand [kWh_thermal]
500
400
300
Measured_cold
Simulated_cold
200
100
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Vertigo Uncalibrated
Heat
600
Energy demand [kWh_thermal]
500
400
300
Measured_heat
Simulated_heat
200
100
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Vertigo
Cal_Sig_cold
Un-calibrated
Vertigo
Cal_Sig_heat
Un-calibrated
60
50
50
40
40
30
30
-20
10
0
-10
20
Error [%]
Error [%]
20
0
10
20
30
40
10
50
-10
0
-20
-20
-10
0
10
20
30
40
50
30
40
50
-10
-30
-40
-20
Temperature [°C]
Temperature [°C]
Vertigo
Char_Sig_Cold
HR 0,7? (0,5)
Vertigo
Char_Sig_Heat
HR 0,7? (0,5)
40
10
35
30
5
-20
20
0
-10
0
10
20
-5
30
40
50
Error [%]
Error [%]
25
15
10
5
0
-20
-10
-10
-5
0
10
20
-10
-15
Temperature [°C]
-15
Temperature [°C]
Vertigo
Char_Sig_Heat
Int 30? (20)
Vertigo
Char_Sig_Cold
Int 30? (20)
80
30
60
20
10
40
0
-20
0
-20
-10
0
10
20
30
40
-10
0
50
-20
10
20
30
40
50
30
40
50
-10
Error [%]
Error [%]
20
-20
-30
-40
-40
-60
-50
-80
-60
-100
-70
Temperature [°C]
Temperature [°C]
Vertigo
Char_Sig_Cold
Vent_max 3? (2)
Vertigo
Char_Sig_Heat
Vent_max 3? (2)
60
60
40
40
20
20
0
Error [%]
-10
0
10
20
30
40
50
Error [%]
-20
-20
0
-20
-10
0
10
20
-40
-20
-60
-40
-80
-100
-60
Temperature [°C]
Temperature [°C]
Vertigo Calibrated (Cold)
600
Energy demand [kWh_thermal]
500
400
300
Measured_cold
Simulated_cold
200
100
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Vertigo Calibrated (Heat)
600
Energy demand [kWh_thermal]
500
400
300
Measured_heat
Simulated_heat
200
100
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
-20
Vertigo
Cal_Sig_Heat
Result
60
30
40
20
20
10
0
-10
0
10
20
30
40
50
Error [%]
Error [%]
Vertigo
Cal_Sig_cold
Result
-20
0
-10
0
-20
-10
-40
-20
-60
Temperature [°C]
-30
10
20
Temperature [°C]
30
40
50
Building: Helix
RMSE_cold:
RMSE_heat:
MBE_cold:
MBE_heat:
45
236
-1.09
-18.20
Helix Un-calibrated
Cold
1400
Energy demand [kWh_thermal]
1200
1000
800
Measured_cold
600
Simulated_cold
400
200
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Helix Un-calibrated
Heat
Energy demand [kWh_thermal]
2500
2000
1500
Measured_heat
1000
Simulated_heat
500
0
0
5
20
0
13
18
20
27
16
20
25
16
22
16
14
18
16
14
13
Temperature [°C]
Helix
Cal_Sig_heat
Un-calibrated
Helix
Cal_Sig_cold
Un-calibrated
100
80
80
70
60
60
50
-20
0
-10
40
Error [%]
Error [%]
40
20
0
10
20
30
40
30
20
50
-20
10
-40
0
-20
-60
-10
0
-80
-20
Temperature [°C]
20
40
50
30
40
50
10
0
-20
0
0
10
20
30
40
-10
0
10
20
-10
50
-10
Error [%]
-20
Error [%]
30
Helic
Char_Sig_heat
HR 0,4? (1)
10
-10
20
Temperature [°C]
Helix
Char_Sig_cold
HR 0,4? (1)
-20
10
-10
-20
-30
-30
-40
-40
-50
-50
-60
-60
-70
-70
Temperature [°C]
Temperature [°C]
Helix
Char_Sig_cold
Int 35? (150)
Helic
Char_Sig_heat
Int 35? (150)
20
40
10
20
0
-20
-10
0
-10
10
20
30
40
50
0
-20
-10
-30
-40
0
10
20
30
40
50
30
40
50
-20
Error [%]
Error [%]
-20
-40
-50
-60
-60
-70
-80
-80
-90
-100
Temperature [°C]
Temperature [°C]
Helix
Char_Sig_cold
Vent 6/12? (6/8)
Helix
Char_Sig_heat
Vent 6/12? (6/8)
200
40
30
150
20
10
Error [%]
Error [%]
100
0
-20
50
-10
0
0
-20
10
20
-10
-20
-10
0
10
20
30
40
50
-30
-50
-40
-100
-50
Temperature [°C]
Temperature [°C]
Helix Calibrated
Cold
1400
Energy demand [kWh_thermal]
1200
1000
800
Measured_cold
600
Simulated_cold
400
200
0
0
5
20
0
13
18
20
27
16
20
25
16
22
16
14
18
16
14
13
Time [day]
Helix Calibrated
Heat
Energy demand [kWh_thermal]
2500
2000
1500
Measured_heat
1000
Simulated_heat
500
0
0
5
20
0
13
18
20
27
16
20
25
16
22
16
14
18
16
14
13
Time [day]
-20
Helix
Cali_Sig_heat
Result
20
40
15
30
10
20
5
10
0
-10
0
10
20
-5
-10
-15
30
40
50
Error [%]
Error [%]
Helix
Cali_Sig_cold
Result
-20
0
-10
0
20
-20
-30
-20
-40
-25
-50
-30
10
-10
Temperature [°C]
-60
Temperature [°C]
30
40
50
Building: Matrix
RMSE_cold:
RMSE_heat:
MBE_cold:
MBE_heat:
118
49
80
-17
Matrix Un-calibrated
Cold
500
Energy demand [kWh_thermal]
450
400
350
300
250
Measured_cold
200
Simulated_cold
150
100
50
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Matrix Un-calibrated
Heat
800
Energy demand [kWh_thermal]
700
600
500
400
Measured_heat
Simulated_heat
300
200
100
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Matrix
Cal_Sig_heat
Matrix
Cal_Sig_cold
90
80
80
60
70
60
50
Error [%]
Error [%]
40
20
40
30
20
0
-20
-10
0
10
20
30
40
50
10
0
-20
-20
-10
0
10
20
30
40
50
-10
-40
-20
Temperature [°C]
Temperature [°C]
Matrix
Char_Sig_heat
HR 0,5? (1)
Matrix
Char_Sig_cold
HR 0,5? (1)
20
40
0
20
-20
0
10
20
30
40
-20
20
-40
-40
-60
-60
-80
-80
10
50
Error [%]
Error [%]
-10
0
-20
0
-20
-10
Temperature [°C]
-100
Temperature [°C]
30
40
50
Matrix
Char_Sig_cold
Vent 4? (0,5)
Matrix
Char_Sig_heat
Vent 4? (0,5)
30
20
20
10
10
0
0
-20
-10
Error [%]
-10
0
10
20
30
40
-20
50
-10
0
10
20
30
40
50
30
40
50
-10
Error [%]
-20
-30
-20
-30
-40
-40
-50
-50
-60
-70
-60
-80
-70
Temperature [°C]
Temperature [°C]
Matrix
Char_Sig_heat
ZTA 0,35? (0,7)
Matrix
Char_Sig_cold
ZTA 0,35? (0,7)
20
40
10
20
0
-20
-10
0
-20
-10
10
20
30
40
0
10
20
-20
50
Error [%]
Error [%]
0
-10
-20
-30
-40
-50
-40
-60
-70
-60
-80
-80
-90
Temperature [°C]
Temperature [°C]
Matrix Calibrated
Cold
500
Energy demand [kWh_thermal]
450
400
350
300
250
Measured_cold
200
Simulated_cold
150
100
50
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Matrix Calibrated
Heat
800
Energy demand [kWh_thermal]
700
600
500
400
Measured_heat
Simulated_heat
300
200
100
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Matrix
Char_Sig_heat
Result
Matrix
Char_Sig_cold
Result
-10
25
20
10
15
0
10
-10
0
10
20
30
40
50
5
Error [%]
Error [%]
-20
30
20
-20
-20
-30
0
-10
-5
-50
-15
-60
-20
10
20
-25
-70
-80
0
-10
-40
Temperature [°C]
-30
Temperature [°C]
30
40
50
Building: Cyclotron
RMSE_cold:
RMSE_heat:
MBE_cold:
MBE_heat:
26
33
0.33
-0.32
Cyclotron Uncalibrated
Cold
700
Energy demand [kWh_thermal]
600
500
400
Measured_cold
300
Simulated_cold
200
100
0
0
20
40
60
80
100
120
140
160
-100
180
200
220
240
260
280
300
320
340
360
Time [day]
Cyclotron Uncalibrated
Heat
800
Energy demand [kWh_thermal]
700
600
500
400
Measured_heat
Simulated_heat
300
200
100
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Cyclotron
Cali_Sig_heat
Cyclotron
Cali_Sig_cold
25
60
40
20
20
0
-20
-10
0
10
20
30
40
15
50
Error [%]
Error [%]
-20
-40
10
-60
5
-80
-100
0
-20
-120
-140
-10
0
Temperature [°C]
120
40
100
20
-20
Error [%]
Error [%]
60
40
-10
40
50
40
50
Temperature [°C]
0
-60
-80
10
20
Temperature [°C]
30
40
20
-40
0
0
10
-20
20
-20
30
0
80
-10
20
Cyclotron
Char_Sig_heat
HR 0,5? (1)
Cyclotron
Char_Sig_cold
HR 0,5? (1)
-20
10
-5
50
-100
Temperature [°C]
30
Cyclotron
Char_Sig_heat
Int 50? (150)
40
50
30
40
20
30
10
20
Error [%]
Error [%]
Cyclotron
Char_Sig_cold
Int 50? (150)
0
-20
-10
0
10
20
30
40
10
50
0
-10
-20
-10
0
10
-30
-20
Temperature [°C]
40
50
30
40
50
Cyclotron
Char_Sig_heat
Vent 16? (12)
140
30
120
25
20
100
15
80
10
Error [%]
60
Error [%]
30
Temperature [°C]
Cyclotron
Char_Sig_cold
Vent 16? (12)
40
5
0
-20
20
-10
-5
0
-20
20
-10
-20
-10
0
10
20
30
40
-20
-15
-40
-20
-60
0
10
20
-10
50
-25
Temperature [°C]
Temperature [°C]
Cyclotron Calibrated
Cold
350
Energy demand [kWh_thermal]
300
250
200
Measured_cold
150
Simulated_cold
100
50
0
0
20
40
60
80
100
120
140
160
180
-50
200
220
240
260
280
300
320
340
360
Time [day]
Cyclotron Calibrated
Heat
800
Energy demand [kWh_thermal]
700
600
500
400
Measured_heat
Simulated_heat
300
200
100
0
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
Time [day]
Cyclotron
Cali_Sig_heat
Result
Cyclotron
Cali_Sig_cold
Result
30
20
20
15
10
10
0
-10
0
10
20
-10
-20
40
50
-20
5
0
-10
0
10
20
-5
-30
-10
-40
-50
30
Error [%]
Error [%]
-20
Temperature [°C]
-15
Temperature [°C]
30
40
50