Transcript 6/20/2006 2

Chapter 2
DESIGN OF PV SYSTEM INTERCONNECTED
WITH EU
2-1 INTRODUCTION
Photovoltaic, PV, system is a green power source, which can
convert sunlight to electricity. It requires no fuel, produces no
emissions, and involves no moving parts. There are two modes
of PV system operation. Stand-alone PV system with battery
storage and PV system connected to electric utility, EU with or
without battery storage.
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Chapter 2
PV system connected to
electric utility, EU
without BS
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PV system connected to
electric utility, EU with
BS
2
Chapter 2
This chapter introduces a proposed computer
program for optimum design of a PV system to be
interconnected with EU. The proposed computer
program has been designed to determine an
optimum number of PV modules based on
maximum power point, MPPs, by using neural
network for the system under study. Many PV
module types have been introduced to computer
program to choose the best type of PV module. The
computer program can completely design the PV
system interconnected with EU and determines the
optimum operation hour by hour through the year.
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Chapter 2
Then, it estimates the monthly surplus energy,
monthly deficit energy and yearly purchase or
selling energy to / or from EU . The decision from
the computer program is based on minimum price
of the generated kWh from the PV system and
maximum power extracted from PV system.
Maximum power output from PV system changes
when solar radiation and temperature vary. Control
is needed for the PV system to track the MPPs.
This controller has been designed by neural
network approach.
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Chapter 2
2-2 METHODOLOGY
2-2-1 Estimation of Hourly Radiation on the
Tilted Surfaces
Hourly solar radiation incident upon a horizontal
surface is available for many locations. However
solar radiation data on tilted surfaces are generally
not available [77]. The hourly radiation on surface
tilted by monthly best tilt angle toward equator
estimated using the following method:
(a) Computation of the monthly best tilt angle
[69], [77]:
(b) Calculation of radiation on the tilted surfaces:
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Chapter 2
2-2-2 Calculation of Average Power for One PV
Module
The electrical power generated and terminal voltage of
PV module depends on solar radiation and ambient
temperature. The equivalent electrical circuit describing
the solar cells module used in the analysis is shown in
Fig. 2-1.]78[
Rs
I
Iph
Rsh
Load
+
V
Fig. 2-1 Equivalent Circuit of PV Solar Cells Module.
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Chapter 2
The mathematical equation describing the I-V
characteristics of a PV solar cells module are given by
[9], [26], [79].

I(t )  Iph (t )  Io (t ) *  exp


 q * ( V ( t )  I (t )*R s )   V( t )  I(t ) * R s

  1 
 A* KB * T ( t )  
R

 
sh
(2-1)
Where;
I(t)
: The hourly output current, Amp.
V(t)
: The hourly output voltage, Volt.
A
: The ideality factor for p-n junction.
T(t)
: The hourly temperature, Kelvin.
KB
: The Boltzman's constant in Joules per Kelvin, 1.38*10-23 J/k.
q
: The charge of the electron in Coulombs, 1.6*10-19C.
Io(t)
: The hourly reverse saturation current, Amp. This current varies
with temperature as follows:


Io ( t )  Ior *  T(t) T 

r 

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q * E

go
* exp 
 KB * A (1/T  1/T(t))
r





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Chapter 2
Iph(t) : The hourly generated current of solar cells
module. This current varies with temperature according
to the following equation:
I
ph
(t )  (Isc  K (T(t )  298)) * H (t ) / 100
I
T
Where;
Tr
: The reference temperature, K.
Ego : The band-gap energy of the semiconductor.
KI
: The short circuit current temperature coefficient.
Ior : The saturation current at Tr, Amp.
HT(t) : The average hourly radiation on the tilted
surface
Isc : PV cell short-circuit current at 25o C and 100
W/cm2.
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Chapter 2
The hourly output of the solar cells module can be
calculated by the following equation:

Ppv, out (t )  V(t ) * I ph (t )  I o (t ) *


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
 exp


 q * ( V (t )  I (t ) * R s )   V(t )  I(t )*R s 

  1 

A*KB* T(t )
R sh

 

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Chapter 2
2-2-3 Calculation of Optimum Number of PV
Modules
The energy balance between the load and the output of PV
system must be carried out to compute the optimum number
of PV modules, Npv. The output power from PV system
must satisfy the load power demand. The hourly generated
power, Ppv,out(t), and hourly load power, PLoad(t), are
compared with each other. If Ppv,out(t) is larger than the
load power demand then there is an hourly surplus power,
but if Ppv,out(t) is smaller than the load power demand then
there is an hourly deficit power. At any value of Npv, if the
summation of hourly surplus power equal to the summation
of hourly deficit power then this value of Npv represents the
optimum number of PV modules. The following equations
have been used to get the optimum number of PV modules.
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Chapter 2
t 8760
IF
 [ N pv * Ppv,out (t )  PLoad (t )]  0
t 1
Then, number of PV module must be decreased by one
module and repeating the foregoing process:
IF
t 8760
 [ N pv * Ppv,out (t )  PLoad (t )]  0
t 1
Then, number PV module must be increased by one module and
repeating the foregoing process.
t 8760
IF
 [ N pv * Ppv,out ( t )  PLoad ( t )]  0
t 1
Then, Npv is the optimum number of PV modules satisfies the
energy balance condition. The value of Npv has been taken as the
optimum number of PV modules and can be named ONpv.
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Chapter 2
2-2-4 Estimation the Number of Subsystems
The number of subsystems depends on the inverter
rating and efficiency and also size of PV system. To
determine the number of subsystems required the
following data must be known:
•Rating and efficiency of the inverter unit.
•Solar cell data (module data).
•The optimum number of PV modules that obtained
from energy balance process.
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Chapter 2
2-2-6 Design of Neural Network for MPPs
[87-91]
This item discuses the structure and training of a
neural network, NN, to track the MPPs of PV array.
The MPPs can be obtained by controlling the
switching scheme of the DC/DC boost converter.
This can be done by using NN. The Back
Propagation, BP, learning algorithm is applied to
NN consisting of processing elements with
activation functions.
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Chapter 2
2-2-7 Calculation of Energy Cost Figure, ECF
The major concern in the design of an electric
power system that utilizes renewable energy sources
is the accurate selection of system components that
can economically satisfy the load demand. The
system's components are found subject to:
1- Minimize the cost of electricity
production($/kWh)
2- Ensure that the load is served according to a
certain reliability criteria.
3- Minimize the power purchased from the grid
[66].
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Chapter 2
The energy cost figure, ECF, of PV system is
determined by dividing the summation of the
total yearly expenses of PV system by the
expected yearly energy generated, Ey. The
following equations are used to determine the
ECF [62, 69].
Energy cost figure, ECF, $/kWh
=(TLACPV)/Total expected yearly energy generated.
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Chapter 2
2-3 APPLICATIONS AND
RESULTS
2-3-1 Design of PV System
A new proposed computer program has been
designed
depended
on
the
above
methodology for calculating optimum design
of PV system. The flowchart of this program
is shown in Fig. 2-7.
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Chapter 2
Start
Read Radiation, Temperature, PV module
parameters, and laod demand, Site
Latitude
Modification of radiation on surfaces tilted by monthly best tilt
angle.
Eqn. (2-1) :(2-9)
For PV module=1 : 1 :5
Calculate maximum power for one
module based on MPP Eqn.(2-10): (213)
Energy balance for PV to determine
number of PV modules.
Eqn.(2-14) : (2-16)
calculate the No. of Subsystems.
Eqn. (2-17) : (2-21)
Design of Boost Converter
Eqn. (2-18) : (2-21)
Calculate ECF
Eqn. (2-41) : (2-51)
Take a decision to select optimum type
and number of PV modules for minimum
cost
End
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Chapter 2
The input data of this program is:
1- Hourly radiation, kW/m2.
2- Characteristics of each PV module type.
3-Site latitude, Degrees.
4- Hourly load demand, kW.
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Chapter 2
Fig. 2-8 The Radiation on Horizontal
Surfaces of Zafarâna Site
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Chapter 2
Table (2-2) Characteristics of the Different PV Solar Cells Module
Solar cells type
M55
[40],[92]
BP MSX 80
[93]
BP MSX 64
[93]
BP MSX
120 [93]
ASE-300-DGF/17
[94]
1.29*0.33
1.461*0.50
1.11*0.50
0.99*1.11
1.892*1.28
Area, m2
0.425 m2
0.7309 m2
0.55471
1.104
2.4278
Nominal Peak Power
(Pmax)
55 W
80 W
64 W
120 W
285W
Voltage at Pmax , (Vmp)
17.4 V
16.8 V
17.5 V
33.7 V
17.0 V
Current at Pmax , (Imp)
3.15 A
4.75 A
3.66 A
3.56 A
16.8 A
Open circuit voltage at
Pmax , (Voc)
21.7 V
21.0 V
21.3 V
42.1V
20.0 V
short circuit current at
Pmax , (Isc)
3.45 A
5.17 A
4A
3.87 A
18.4 A
Item
Dimensions, m
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Chapter 2
Fig. 2-9 Daily Load Curve for January, April, July and October.
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Chapter 2
The outputs of this program are:
1- Optimum number of each PV module type.
The first output of the proposed computer program
are the optimum total number of PV modules to
feed the whole load demand, number of modules
per string, and finally number of inverter units.
The inverter has an input voltage 6005% Vdc,
efficiency 95% at unity power factor and rating
500 kW. Table (2-3) revels the construction of the
designed PV system under sizing different selected
types of solar cells module.
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Chapter 2
Table (2-3) The Construction of the Designed PV system
Under Using Different Selected Types of Solar Cells Module
Solar cells
M55
BP MSX 64
BP MSX 120
1893782.0
1784731
1889799
1692094
3202920
1711815
696960
Item
Module Active Area, m2
1611238.0
ASE-300
DGF/17
BP MSX 80
Total Number of
Modules
3787611
Number of series
Modules/string
31
33
31
17
32
Number of parallel string
/subsystem
293
189
252
245
55
Number of Modules
/subsystem
9083
6237
7812
4165
1760
Number of inverter unit
417
414
410
411
396
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Chapter 2
2- Cost of kWh generated, $/kWh.
The second output of the proposed computer program is
Energy Cost Figure, ECF, for each of solar cells module type.
The ECF are displayed in Table (2-5) and Fig. 2-10. From
Table (2-5) and Fig. 2-10 it can be seen that the solar cells
module type of ASE-300 DGF/17 represents the most
economical one for Zafarâna site. The price of kWh ( ECF)
produced form PV system which used ASE-300 DGF/17 PV
module type is 0.08499 $/kWh.
Table (2-5) ECF for each Selected Module Type
Module Type
M55
BP MSX
80
BP MSX
64
BP MSX 120
ASE-300 DGF/17
ECF, (2005) $/kWh
0.08915
0.08841
0.08772
0.08791
0.08499
ECF, (2010) $/kWh
0.04728
0.04689
0.04652
0.046625
0.045074
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Chapter 2
Fig. 2-10 ECF for each Selected Module Type for the year 2005.
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Chapter 2
PV
Load
1600
1400
Energy, MWh
1200
1000
800
600
400
200
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Fig. 2-12 The Total Energy Generated and Energy Demand
for each Month.
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