Download comparison of honey comb and bridge link type configuration of

COMPARISON OF HONEY COMB AND BRIDGE LINK TYPE
CONFIGURATION OF SOLAR PHOTOVOLTAIC ARRAY UNDER PARTIAL
SHADING CONDITIONS
Mohd.Faisal Jalil1
Assistant Professor
Department of Electrical &Electronics Engineering
KIET,Ghaziabad
1
Abstract--- The performance of the photovoltaic (PV)
array depends upon the temperature, solar radiation,
shading and array configuration. The PV array gets
shadowed completely or partially by building, electric
pole, tower, tree and clouds. Partial shading of the PV
array affects the generating power compare to the PV
array with uniform insolation. The losses due to partial
shading of the PV array depend upon the shading
pattern of the PV array. This paper presents a
MATLAB based modeling and simulation of the PV
arrays its analysis under partial shading condition for
honey comb and bridge link array configuration. A
versatile model using MATLAB/SIMULINK is
developed
which
represents
different
array
configuration under partial shading conditions, The
maximum power point is effected by the type of
connection of the PV array for the same shading
pattern of the PV array.
Keywords— Array, circuit, equivalent, model, modeling,
photovoltaic, PV, simulation, MMP.
Santosh Kumar Shakya2, Vishal Kumar3, Popindar
Prajapati4
234
Department of Electrical &Electronics Engineering
KIET,Ghaziabad
simulators [1–3]. In order to study electronic converters for
PV systems, one first needs to know how to model the PV
device that is attached to the converter. PV devices present
a non-linear V-I characteristic with several parameters that
need to be accommodate from experimental data of
practical devices. The mathematical model of the PV
device may be useful in the study of the dynamic analysis
of converters, in the study of Maximum power point
(MPPT) algorithms, and mainly to simulate the PV system
and its components using circuit simulators.
II. LITERATURE REVIEW
A maximum power point tracking algorithm is
conclusively necessary to increase the efficiency of the
solar panel as it has been found that only 30-40% of
energy incident is converted into electrical energy.
I. INTRODUCTION
Among all the MPPT methods, Perturb & Observe and
Incremental Conductance are most commonly used
because of their simple implementation and lesser time to
The first step to study about an appropriate control method
in photovoltaic systems is to know how to model and
simulate a PV system attached to the converter and power
grid. Commonly, PV systems present non-linear PowerVoltage and Current-Voltage characteristics which tightly
depend on the receiving irradiance levels and climate
conditions. The mathematical model of the photovoltaic
system is significantly valuable for studying the maximum
power point algorithms, doing
research about the
dynamic performance of converters, and also for
simulating photovoltaic components by using circuit
track the maximum power point and also other profitable
reasons. Under abruptly changing weather conditions
(irradiation level) as MPP changes progressively, P&O
takes it as a change in MPP due to perturbation rather
than that of irradiation and sometimes ends up in
calculating erroneous MPP[7]. However this problem is
ousted in Incremental Conductance method as the
algorithm takes two samples of voltage and current to
compute MPP. However, instead of more efficiency the
ramification of the algorithm is very high as compared to
the former one and hence the cost of execution increases.
So we have to extenuate with a trade-off between
complexity and efficiency. It has been examined that the
efficiency of the system also relies upon the converter.
Generally, it is maximum for a buck analysis, then for
buck-boost analysis and minimum for a boost analysis.
When more than one solar modules are connected in
parallel, another analog technique which is known as
TEODI is also very efficient which operates on the
principle of equalization of output operating points in
correspondence to force displacement of input operating
Fig1. Single-diode model of the theoretical photovoltaic cell
and equivalent circuit of a practical photovoltaic device including
a series and parallel resistance
points of the identical operating system. It is very
rudimentary to carry out and has high efficiency both
under stationary and time varying climatic conditions [8].
.
III. MODELING OF PHOTOVOLTAIC ARRAY
Fig2. I-V characteristics of photovoltaic cell. The net
cell current
I is composed of the light generated current 𝐼𝑝𝑣
and diode current 𝐼𝑑
A. Ideal photovoltaic cell
The fundamental equation from the theory of
semiconductors [1] that mathematically describes
the I -V characteristic of the ideal photovoltaic
cell is:
𝑞𝑉
𝐼 = 𝐼𝑝𝑣,𝑐𝑒𝑙𝑙 − 𝐼𝑜,𝑐𝑒𝑙𝑙 [𝑒𝑥𝑝 {
− 1}]
(1)
𝑎𝑘𝑇
where
Ipv,cell -- the current developed by the incident light
(it is directly proportional to the Sun irradiation),
Id -- the Shockley diode equation,
I0,cell [A] is the reverse saturation or leakage current
of the diode [A],
q -- the electron charge [1.60217646 · 10−19C],
k -- the Boltzmann constant [1.3806503 ·
10−23J/K],
T [K] -- the temperature of the p-n junction,
and a is the diode ideality constant.
Fig3. Characteristic I -V curve of a practical
photovoltaic device
and the three remarkable points: short circuit (0, Isc),
maximum power point (Vmp, Imp) and open-circuit
(Voc, 0).
B. Modeling the photovoltaic array
The fundamental equation (1) of the rudimentary
photovoltaic cell does not represent the I -V
characteristic of a practical photovoltaic array.
Practical arrays are constituted of several
connected photovoltaic cells and the examination
of the characteristics at the terminals of the
photovoltaic array requires the incorporation of
additional parameters to the basic equation [1]:
𝐼 = 𝐼𝑝𝑣 − 𝐼0 [𝑒𝑥𝑝 (
𝑉+𝑅𝑠 𝐼
𝑉𝑡 𝑎
− 1)] −
𝑉+𝑅𝑠 𝐼
𝑅𝑝
(2)
Where Ipv and Io are the photovoltaic and saturation
𝑁 𝑘𝑇
currents of the array and 𝑉𝑡 = 𝑠 ⁄4 is the thermal
voltage of the array with Ns cells connected in series .Cells
connected in parallel increase the current and cells
connected in series give the voltages. If the array is
constituted of Np parallel connections of cells the
photovoltaic and saturation current may be expressed as
𝐼𝑝𝑣 = 𝐼𝑝𝑣,𝑐𝑒𝑙𝑙 . 𝑁𝑝 , 𝐼0 = 𝐼0,𝑐𝑒𝑙𝑙 𝑁𝑝 .
Eq. (2) characterizes the single-diode model presented in
Fig.1. Some Researchers have distinguished more
sophisticated models that present better accuracy and serve
for different purposes [2]-[6]. For simplicity, this paper
explains the single-diode model. The simplicity of the
single-diode model with the method for adjusting the
parameters and the improvements suggested in this paper
gives better accuracy and give the characteristics similar to
the better model which is two diode models in which two
diodes are represented instead of one for better accuracy.
Manufacturers of photovoltaic arrays, give only a
few experimental data about electrical and thermal
characteristics. All Manufacturers gives only following
information which are the nominal open-circuit voltage
Voc,n, the nominal short-circuit current Isc,n, the voltage
at the maximum power point Vmp, the current at the
maximum power point Imp, the open-circuit
voltage/temperature coefficient Kv, the short-circuit
current/temperature coefficient Ki , and the maximum
experimental peak output power Pmax,e. This information
is always given with reference to the nominal or standard
test conditions (STC) of temperature and solar irradiation.
Some manufacturers give additional information like I-V
characteristics and some other information.
The practical photovoltaic device presents an hybrid
behaviour, which may be of current or voltage source
depend on situation. The practical photovoltaic device has
a series resistance Rs whose impact is stronger when the
device operates in the voltage source region and a parallel
resistance Rp with stronger impact in the current source
region of operation [9]-[15]. The Rs resistance is the sum
of several architectural resistances of the device. The Rp
resistance exists mainly due to the leakage current of the pn junction.
The I-V characteristic of the photovoltaic device
rely upon the internal characteristics of the device (Rs, Rp)
and on external impacts such as irradiation level,
temperature and shading. The output of the PV array is
directly rely upon the sun radiations.. Datasheets only tell
the nominal short-circuit current (Isc,n, maximum current
available at the terminals of the practical device). The
assumption Isc ≈ Ipv is commonly used in photovoltaic
models because in practical devices the series resistance is
low and the parallel resistance is high [8]-]12], [14]-[17],
[18]. The output current of the photovoltaic cell rely upon
linearly on the solar radiation and is also effected by the
temperature according to the following equation:
Ipv = (Ipv,n + K I ∆T)
G
(3)
Gn
Where
Ipv,n [A] -- the light-generated current at the
nominal condition (usually 25 ◦C and 1000W/m2 ),
∆T = T − Tn (being T and Tn the actual and
nominal temperatures [K]),
G [W/m2 ] -- the irradiation on the device
surface, and Gn is the nominal irradiation. The diode
saturation current Io and its dependence on the temperature
may be expressed by (4):
Tn 3 qEg
I0 = I0,n exp ( ) [
T
ak
](
1
Tn
1
− )
T
(4)
where
Eg -- the band gap energy of the semiconductor (Eg
≈ 1.12 eV for the polycrystalline Si at 25 ◦C), and
Io,n -- the nominal saturation current:
Io,n =
Isc,n
Voc,n
)−1
aVt,n
exp(
(5)
Vt,n -- the thermal voltage of Ns series-connected cells at
the nominal temperature Tn. The saturation current Io of
the photovoltaic cells rely upon the saturation current
density of the semiconductor (Jo, generally given in
[A/cm2 ]). The current density Jo relies upon the
characteristics of the photovoltaic cell, which depend on
physical parameters such as the coefficient of diffusion of
electrons in the semiconductor, the intrinsic carrier density,
and others [2]-[5]. the nominal saturation current Io,n is
indirectly retrieved from the data through , which is
obtained by calculating (2) at the nominal open-circuit
condition, with
V = Voc,n,I = 0, and Ipv ≈ Isc,n.
The value of the diode constant a may be assumed usually
1 ≤ a ≤ 1.5 or given by manufacturer. This constant affects
the curvature of the I-V characteristic and varying a can
slightly raises the model accuracy.
C.Model improvement:The photovoltaic model explained in the previous section
can be improved if equation (5) is replaced by:
𝐼0 =
𝐼𝑠𝑐,𝑛+𝐾𝐼 ∆𝑇
𝑒𝑥𝑝(
(6)
𝑉𝑜𝑐,𝑛 +𝐾𝑉 ∆𝑇
)−1
𝑎𝑉𝑡
This adjustment aims to match the open-circuit
voltages of the model with the experimental data for a very
large range of temperatures. Eq. (6) is obtained from (5) by
including in the equation the current and voltage
coefficients Kv and Ki. The validity of the model with this
equation has been tested through computer simulation and
through comparison with experimental data.
The open-circuit voltages of the model are equated with
the open-circuit voltages of the real array in the range Tn <
T < Tmax. By equalling (4) and (6) and solving for Eg at T
= Tmax one gets:
𝐸𝑔 = −𝑙𝑛 [
3
𝐼𝑠𝑐,𝑇𝑚𝑎𝑥
𝑇
)( 𝑛 )
𝑎𝑘𝑇𝑛𝑇𝑚𝑎𝑥
𝐼0𝑛
𝑇𝑚𝑎𝑥
𝑞𝑉 .𝑇
𝑒𝑥𝑝( 𝑜𝑐 𝑚𝑎𝑥 )−1 𝑞(𝑇𝑛 −𝑇𝑚𝑎𝑥 )
𝑎𝑁𝑠 𝑘𝑇𝑚𝑎𝑥
(
]
.
The model established in the preceding sections may be
further improved by taking advantage of the iterative
solution of Rs and Rp. Each iteration updates Rs and Rp
towards the best model solution, so equation (10) may be
concluded in the model.
𝑰𝒑𝒏,𝒏 =
𝑹𝒑 +𝑹𝒔
𝑹𝒑
𝑰𝒔𝒄,𝒏
(10)
Eq. (10) uses the resistances Rs and Rp to examine Ipv ,
Isc.
𝑹𝒑,𝒎𝒊𝒏 =
𝑽𝒎𝒑
𝑰𝒔𝒄,𝒏−𝑰𝒎𝒑
−
𝑽𝒐𝒄,𝒏−𝑽𝒎𝒑
𝑰𝒎𝒑
(11)
Parameters of the adjusted model of the KC200GT solar
array at 25 °C, 1.5AM, 1000 W/m2 :(7)
Where
Imp
7.61A
Vmp
26.3 V
Pmax,e
200.000143 W
D. Model adjustment:
Isc
8.21A
There are two parameters which are yet remain unknown
are Rs and Rp. To adjusting Rs and Rp based on the fact
that there is an only pair {Rs,Rp} that warranties that
Pmax,m = Pmax,e = VmpImp at the (Vmp, Imp) point of
the I-V curve, and solving the resulting equation for Rs, as
(8) and (9) show [6],[8].
Voc
32.9V
Io,n
9.825*𝟏𝟎−𝟖 A
Ipv
8.214 A
A
1.3
Rp
415.405Ὠ
Rs
0.221Ὠ
K1
0.0032 A/K
Kv
-0.1230 V/K
𝐼𝑠𝑐,𝑇𝑚𝑎𝑥 = 𝐼𝑠𝑐,𝑛 + 𝐾𝐼 ∆ 𝑇 𝑎𝑛𝑑 𝑉𝑜𝑐,𝑇𝑚𝑎𝑥
= 𝑉𝑜𝑐,𝑛 + 𝐾𝑉 ∆ 𝑇 , 𝑤𝑖𝑡ℎ ∆ 𝑇 = 𝑇𝑚𝑎𝑥 − 𝑇𝑛 .
𝑷𝒎𝒂𝒙,𝒎 = 𝑽𝒎𝒑 {𝑰𝒑𝒗 − 𝑰𝒐 [𝒆𝒙𝒑 (
𝑽𝒎𝒑 +𝑹𝒔 𝑰𝒎𝒑
𝑹𝒑
𝑹𝒑 = 𝑽𝒎𝒑 (
𝒒
𝒌𝑻
.
𝑽𝒎𝒑 +𝑹𝒔 𝑰𝒎𝒑
} = 𝑷𝒎𝒂𝒙,𝒆
𝒂𝑵𝒔
) − 𝟏] −
(8)
𝑽𝒎𝒑 +𝑰𝒎𝒑 𝑹𝒔
𝑽𝒎𝒑 +𝑰𝒎𝒑 𝑹𝒔 𝒒
{𝑽𝒎𝒑 𝑰𝒑𝒗 −𝑽𝒎𝒑 𝑰𝒐 𝒆𝒙𝒑[
. ]+𝑽𝒎𝒑 𝑰𝟎 −𝑷𝒎𝒂𝒙,𝒆 }
𝑵𝒔 𝒂
𝒌𝑻
)
(9)
Eq. (9) means that for any value of Rs there will be a value
of Rp that forms the mathematical I-V curve cross the
experiment (Vmp,Imp) point.
IV.MATLAB MODELING & SIMULATION
E.Further model improvement:
The I-V curves of the Solarex MSX60 solar panel
simulated with the MATLAB/SIMULINK and PSIM
circuits.
with partial shading condition and without Bypass diode.
In this paper we are showing only two type of connections
which are Bridge Link, Honey Comb with two different
types of shading one is row wise and second is column
wise to show the comparison between the MPP for both
the connections.
Fig.6 BL connection under row wise shading
Fig.4 Basic Simulink model of Photovoltaic array system
Fig.7 HC connection under row wisel shading
Fig.5 Graph between V and Ipv for basic model
The above fig shows output only for one module. Below
figs shows the two types of Photovoltaic array connection
Fig.8 difference among the different connection under row
wise shading
Fig.10 I-V and P-V characteristics under shading with
Bypass diode
Fig.9 difference among the different connection under
REFERENCES
column wise shading
V. CONCLUSION
This paper shows the different types of connections of
photovoltaic array with two different types of shading
which are row-wise shading and column-wise shading.
After analyzing the row-wise shading for all the four types
of connection it is concluded that the MPP is more
efficient in BL connection than HP connection. The
descending order of the MPP for all the connection with
row-wise shading is :HC > BL
But while analyzing the column wise shading the order of
the MPP found is different .The order is in that type of
shading is:BL > HC
From the above two statement it is concluded that the MPP
is depend on the different types of shading and
connections. Obviously if there would be another type of
connection with different type of shading then order of
MPP will be different.
It is also seen that if there is a bypass diode is used
with the photovoltaic modules the power is increased
which can be clearly seen in the given characteristics
[1] G. E. Ahmad, H. M. S. Hussein, and H. H. ElGhetany. Theoretical analysis and experimental
verification of PV modules. Renewable Energy,
28(8):1159–1168, 2003.
[2] Geoff Walker. Evaluating MPPT converter topologies
using a matlab PV model. Journal of Electrical &
Electronics Engineering, Australia, 21(1), 2001.
[3] M. Veerachary. PSIM circuit-oriented simulator
model for the nonlinear photovoltaic sources. IEEE
Transac-tions on Aerospace and Electronic Systems,
42(2):735– 740, April 2006.
[4] Ali Naci Celik and NasIr Acikgoz. Modelling and experimental verification of the operating current of
mono-crystalline photovoltaic modules using fourand five-parameter models. Applied Energy, 84(1):1–
15, January 2007.
[5] Yeong-Chau Kuo, Tsorng-Juu Liang, and Jiann-Fuh
Chen.
Novel
maximum-power-point-tracking
controller for photovoltaic energy conversion system.
IEEE Trans-actions on Industrial Electronics,
48(3):594–601, June 2001.
[6] M. T. Elhagry, A. A. T. Elkousy, M. B. Saleh, T. F.
Elshatter, and E. M. Abou-Elzahab. Fuzzy modeling
of photovoltaic panel equivalent circuit. In Proc. 40th
Midwest Symposium on Circuits and Systems, v. 1, p.
60–63, August 1997.
[7] Shengyi Liu and R. A. Dougal. Dynamic multiphysics
model for solar array. IEEE Transactions on Energy
Conversion, 17(2):285–294, 2002.
[8] Weidong Xiao, W. G. Dunford, and A. Capel. A novel
modeling method for photovoltaic cells. In Proc.
IEEE 35th Annual Power Electronics Specialists
Conference, PESC, v. 3, p. 1950–1956, 2004.
[9] Y. Yusof, S. H. Sayuti, M. Abdul Latif, and M. Z. C.
Wanik. Modeling and simulation of maximum power
point tracker for photovoltaic system. In Proc.
National Power and Energy Conference, PECon, p.
88–93, 2004.
[10] D. Sera, R. Teodorescu, and P. Rodriguez. PV panel
model based on datasheet values. In
Proc.
IEEE Inter-national Symposium on Industrial
Electronics, ISIE, p. 2392–2396, 2007.
[11] M. Chegaar, Z. Ouennoughi , A. Hoffmann, “A new
method for evaluating
illuminated solar cell
parameters” pergamon, solid-state electronics 45
(2001) 293-296.
[12] G. Notton , C. Cristofari , M. Mattei , P. Poggi , “
Modelling of a double-glass photovoltaic module
using finite differences” Elsevier, Applied thermal
Engineering 25 (2005) 2854-2877.
[13] Mohamed M. Algazar, Hamdy AL-monier, Hamdy
Abd EL-halim, Mohamed Ezzat El Kotb Salem,
“Maximum power point tracking using fuzzy logic
control” Elsevier, electrical power and energy systems
39 (2012) 21-28.
[14] Ewdal Irmak ,Naki Guler, “Application of a high
efficient voltage regulation system with MPPT
algorithm” Elsevier, Electrical power and Energy
system 44 (2013) 703-712.
[15] Issam Houssamo, Fabrice Locment, Manuela
Sechilariu, “Experimental analysis of impact of MPPT
methods on energy efficiency for photovoltaic power
systems” Elsevier, Electrical Power and Energy
System 46 (2013) 98- 107.
[16] Ali
Akbar
Ghassami,
Seyed
Mohammad
Sadeghzadeh, Asma Soleimani, “A high performance
maximum power point tracker for PV systems”
Elsevier, Electrical Power and Energy System 53
(2013) 237-243.
[17] K. Ishaque, Z. Salam, and H. Taheri, “Simple, fast and
accurate two-diode model for photovoltaic modules,”
Solar Energy Mater. Solar Cells, vol. 95, pp. 586-594,
2011.
[18] N. Kishor, S. R. Mohanty, M. G. Villalva, E. Ruppert.
“Simulation of PV array output
power for
modified PV cell model.” In:Proc. IEEE International
Conference on Power and Energy (PECon), Page(s):
533 - 538, Kuala Lumpur, Malaysia, 2010.