International Journal of Advances in Power Systems (IJAPS)
ISSN: 2335-1772
Vol. 1, No. 3, December 2013
Transient Analysis of Grid-Connected
Photovoltaic System Based on Comparative Study
of Maximum Power Point Tracking Techniques
Almoataz Y. Abdelaziz1, Hadi M. El-Helw2, Basem Abdelhamed3
1
Department of Electrical Power & Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt
e-mail: almoatazbdelaziz@hotmail.com
2
Electrical and Control Department, Arab Academy for Science, Technology and Maritime Transport, Cairo,
Egypt
e-mail: elhelw@cairo.aast.edu
3
Department of Electrical Power, El-Shorouk Academy, Cairo, Egypt
e-mail: eng_basemabdelhamed@yahoo.com

Abstract—In this paper the grid disturbances effects on a grid
connected PV array were studied while considering different
maximum power point tracking algorithms. The maximum
power point tracking techniques included in this study are; the
perturb & observe technique (P&O), incremental conductance
technique (ICT), fuzzy logic based technique. The grid
disturbances involved in this paper are the different types of
faults, voltage sag, and voltage swell. A comparative study of the
grid disturbances effect on the three maximum power point
tracking algorithms is obtained. A 100 kW photovoltaic array
connected to the grid via a voltage source inverter through a
boost converter is modeled and simulated under the
MATLAB/SIMULINK in order to accomplish this study. The
simulation results show that the fuzzy logic based technique gives
the best response under steady state and transient conditions.
The output power of PV arrays is mainly influenced by the
irradiance (amount of solar radiation) and temperature.
Moreover for a certain irradiance and temperature, the output
power of the PV array is function of its terminal voltage and
there is only one value for the PV's terminal voltage at which
the PV panel is utilized efficiently. The procedure of searching
for this voltage called maximum power point tracking MPPT.
Recently, several algorithms have been developed to achieve
MPPT technique, such as; Perturb and Observe (P&O) [1],
incremental conductance [2], open circuit voltage, short circuit
current, fuzzy or neural network based algorithms, etc [3, 4].
The PV array generates DC power so power electronics
converters are essential. Actually power electronics converters
are required to converter the generated DC power to AC and to
achieve the MPPT. The MPPT can be accomplished either in
single stage or in a double stage. In single stage, the PV array is
connected to the grid through an AC/DC converter and the
converter is utilized to obtain both the MPPT and the
conversion of the generated voltage to DC. In the double stage,
the PV array is connected to the grid though an AC/DC
converter via a DC/DC converter. In this case, the MPPT is
obtained via the DC/DC converter by controlling its input
voltage. The function of the inverter is to convert the output DC
voltage of the PV into AC and to maintain the output voltage of
the DC/DC converter constant.
Index Terms — Maximum Power Point Tracking; Fuzzy Logic
controller; Photovoltaic System; Transient Analysis
O
I. INTRODUCTION
ver the past few years, the demand for renewable energy
resources has increased significantly due to the fact that
the fossil fuels will run out in the near future and the
harmful environmental
effects of the fossil fuels. Among
various types of renewable energy resources, solar energy has
become one of the most promising and attractive resource.
Nodaway solar energy based photovoltaic is widely used in
many applications as it owns the advantage of being
maintenance and pollution free. Recently, the use of
photovoltaic panel has grown consistently due to the following
factors; the PV efficiency is enhanced, the manufacturing
technology is improved and the PV panel's cost is decreased.
Recently, a large number of PV modules are connected to
utility grid in many countries.
In this paper, maximum power point tracking for a grid
connected PV array is executed and evaluated for three
different MPPT algorithms. The evaluated methods are; (i)
Perturb & Observe (P&O) (ii) Incremental conductance
Technique (ICT) and (iii) Fuzzy logic based (FLC) [3-5].
Furthermore the effects of different grid disturbances on the PV
array and the MPPT algorithms are studied. The considered
disturbances in this study are; the different type of faults,
1
International Journal of Advances in Power Systems (IJAPS)
ISSN: 2335-1772
voltage sag, and voltage swell. In order to accomplish this study
the system shown in Fig. 1 is modeled and simulated using the
MATLAB/SIMULINK.
Vol. 1, No. 3, December 2013
N cs kT
(4)
q
Where Ncs is the number of cells connected in series,q is
electron charge, K is Boltzmann constant and, T is the
temperature of the P-N junction in Kelvin`s
Vt 
B. Model Verification
In order to accomplish this paper, the mathematical model
discribed in the previous sectionis is modeled under the
MATLAB/Simulink.The developed Model is vrefied utilizing
the parameters of a real PV module (Kyocera- KD 200GT)
manufactured by Kyocera (see table I)[7]. Fig. 3 shows the IV and P-V characteristics which developed by the MATLAB
model at different irradiance and constant temperature (25oC).
Fig. 4 shows I-V and P-V characteristics which developed by
the MATLAB model at constant irradiance (1000 W/m2) and
variable temperature. The results shown in Fig. 3 and Fig. 4
are similar to that shown in the PV module datasheet [6].
Fig.1 Block diagram of the grid connected photovoltaic system discussed in
this paper.
II. THE PV MODEL
TABLE I
PRAMETERS OF PV MODULE
A. Mathematical model
A PV model based current source is illustreated in this
section [6]. Fig. 2 shows the PV circuit diagram.
Parameter
I
V
Value
Open circuit voltage (VOC) of a PV module
32.9.0 V
Short circuit current (ISC) of a PV module
8.21 A
Module voltage at maximum power point (Vm)
26.3 V
Module current at maximum power point (Im)
7.61 A
Maximum Power (Pm) of a PV module
200 W
Reference temperature
25º C
Reference solar radiation (1 sun)
1000W/m2
Fig. 2 Equivalent Circuit of photovoltaic cells.
Where Np is the number of parallel modules , Ns is the
number of series modules, Rp is the array parallel resistance,
and Rs is the array series resistance. The module current Im can
be calculated from:
  
I  
  
  1

 
 
 
8
current (A)
 
N
  V  Rs  s
N
 
 p
I m  I PV N p  I o N p exp 
Vt aN s
 
 
 
PV module : Kyocera KC200GT at constant temperature (25°C)
(1)
1000W/m2
800W/m2
6
600W/m2
4
400W/m2
2
200W/m2
0
0
5
10
15
20
25
30
35
Voltage (V)
Ipv can be expressed by:
G
(2)
I pv  I pvn  K i T 
Gn
Where Ipvn is the generated output current at 1000 W/m2 and
25oC as nominal condition, ∆T is the difference between the
real and the nominal temperatures in Kelvins, Ki is the current
temperature coefficient, G is the irradiance and Gn is the
irradiance at nominal conditions. While Io can be given by:
I scn  K i T
(3)
Io 
 Vocn  K v T 
  1
exp 
aVt


Kv is the volatge temperature coefficient, Iscn , Vocn are the
short circuit current and open circuit voltage at nominal
condition respectively,a is the diode ideality constant and Vt is
the thermal voltage of the array and can be calculated from:
1000 W/m2
Power (W)
200
800 W/m2
150
600 W/m2
100
400 W/m2
50
0
0
200 W/m2
5
10
15
20
25
30
Voltage (V)
Fig. 3 I-V and P-V characteristics of the PV module at constant temperature
25°C and various irradiances
2
35
International Journal of Advances in Power Systems (IJAPS)
ISSN: 2335-1772
the MPP and negative on the right.In this algorithm the duty
cycle of the power electronics converter is changed and then
the derivative of the array output power (slope) is caculated.
Accordinding to the slop of the power curve the duty cycle of
the converter is adjusted [2]. The MATLAB / SIMULINK
model of the Incremental Conductance Algorithm (ICT) is
shown in Fig. 6.
PV module : Kyocera KC200GT at 1 kW/m2
current (A)
10
5
50°C
25°C
75°C
0
0
5
10
15
20
25
30
Vol. 1, No. 3, December 2013
35
Voltage (V)
Power (W)
200
25°C
100
50°C
75°C
0
0
5
10
15
20
25
30
35
Voltage (V)
Fig. 4 I-V and P-V characteristics of the PV module under constant
irradiance and different temperature.
III. MPPT ALGORITHMS
As mentioned above the MPPT can be achieved eithier in
single stage or in double stages. In this paper the double stages
scheme is utilized. With the help of the DC/DC converter the
maximum power can be excuted by controlling the duty cycle
of the DC/DC converter in order to control the PV array
terminal voltage. The tracking of the optimam termanl voltage
can be performed by various algorithms.In this section the
MPPTalgorithms[1-5], which are used for the comparative
study in this paper, will be illustrated.
Fig.6 MATLAB / SIMULINK model of ICT algorithm
It is very rare for the ICT to reach exactly to the maximum
power point MPP. Therefore, in this technique the MPP is
considered reached when the operating voltage is within a
certain error limit [2].
C. Proposed Fuzzy Logic Control (FLC) Algorithm
A. Perturb and Observe (P&O)Algorithm.
Maximum power point tracking based Fuzzy logic has the
advantage of being robust and fast in response. In this paper,
the input variables of the proposed fuzzy controller are ΔP(k)
and ΔV(k), where P(k) is PV array output power and V(k) is PV
array output voltage [5]. These variables are expressed in
terms of seven linguistic fuzzy sets; Negative Big (NB),
Negative Medium (NM), Negative Small (NS), Zero (ZO),
Positive Big (PB), Positive Medium (PM) and Positive Small
(PS) using basic fuzzy subset. The MATLAB / SIMULINK
model of the proposed fuzzy logic controller (FLC) is shown
in Fig.7.
In this algorithm, a small perturbation is introduced in the
duty cycle of the power electronics converter and then the
output power of the PV module is observed. If the power
increases due to this perturbation, then the perturbation is
carried on in the same direction. On the other hand, if the PV
output power is decreased then the direction of the
perturbation has to be reversed. The P&O technique is the
simplest MPPT algorithm; however it owns the disadvantage
of oscillation around the final maximum power point (MPP)
[8]. The MATLAB/SIMULINK model of Perturb and
Observe (P&O) Algorithm is shown in Fig. 5.
Fig. 5 MATLAB / SIMULINK model of P&O algorithm
Fig. 7 MATLAB / SIMULINK model of the proposed fuzzy based algorithm
B. Incremental Conductance (ICT) Algorithm
The proposed fuzzy logic controller comprises three
function blocks; fuzzification, Fuzzy rule base, and
defuzzification. An error function (E) and a change of error
(CH_E) are created during fuzzification. In the fuzzy rule
base stage, these variables are then compared to a set of pre-
The ICTalgotithm is built on the principle that the
derivative of the PV array power curve is zero at the
maximum power point(i.e. the slope of the power curve is
zero)[4] . The slope of the power curve is positive on the left of
3
International Journal of Advances in Power Systems (IJAPS)
ISSN: 2335-1772
designed value in order to determine the appropriate
response. In the defuzzification block, the aggregated fuzzy
set is employed to create the simple crisp value of output duty
cycle D. The seven rules which used for tracking the MPP in
the proposed technique are shown in Table II.
via a voltage source inverter through a boost converter. The
function of the boost converter is to control the terminal
voltage of the PV array in order to accomplish the MPPT.
ADC link capacitor is placed after the boost converter and
acts as a temporary power storage device to provide the
voltage source inverter with a steady flow of power. The
capacitor's voltage is regulated using a DC link controller
that balances input and output powers of the capacitor. The
parameter of the system under study is shown in Table III.
TABLE II.
FUZZY RULES
E↓ /CE→
NB
NM
NS
ZE
PS
PM
PB
NB
NM
NS
ZE
PS
PM
PB
ZE
ZE
NS
NM
PM
PM
PB
ZE
ZE
ZE
NS
PS
PM
PB
ZE
ZE
ZE
ZE
PS
PM
PB
NB
NM
NS
ZE
PS
PM
PB
NB
NM
NS
ZE
ZE
ZE
ZE
NB
NM
NS
PS
ZE
ZE
ZE
NB
NM
NS
PM
PS
ZE
ZE
Vol. 1, No. 3, December 2013
TABLE III
PRAMETERS OF THE SYSTEM UNDER STUDY
Quantity
Value
260V
Gridvoltage
The output of FLC is utilized to control the DC-to-DC
converter. The membership functions of the input and output
variables are shown in Fig. 8, Fig. 9 and Fig. 10 respectively.
Fig. 8 Membership function for input variable (E)
Frequency
60 Hz
Switching frequency
5kHz
DC link capacitor C
100µF
DC link voltage
500V
Boost converter inductance
5mH
Boost converter capacitor
1.2mF
Grid voltage
20kV
Inverter voltage
260V
Transformer
260V /20kV
load at bus1
300 + j200 k VA
load at bus 2
200kW
The voltage source converter (VSC) is controlled utilizing
vector control in order to provide a controllable three phase
AC current to the grid. To attain unity power factor
operation, current is injected in phase with the grid voltage.
A phase locked loop (PLL) is utilized in order t o lock on the
grid frequency and provide a reference synchronization signal
for
the
inverter
control
system
[10].
The
MATLAB/SIMULINK model of the VSC is shown in Fig.
11.
Fig. 9 Membership function for input variable (CH_E)
Fig. 10 Membership function for output variable (D)
The proposed fuzzy logic controller utilizes duty cycle with
variable steps for controlling the boost converter and
therefore provides quicker convergence to the maximum
power point [9].
Fig. 11 MATLAB/SIMULINK model of the VSC
V. SIMULATION RESULTS AND DISCUSSION
In this section, the system shown in Fig. 1 is simulated
using the MATLAB/SIMULINK under condition of applying
three maximum power point tracking techniques. The
simulation is run several times in order to study the effect of
different disturbances on the three MPPT algorithms
mentioned above. The MATLAB/SIMULINK model is
shown in Fig. 12.
IV. SYSTEM DISCRIBTION
In this paper a 100 kW PV array is utilized. The 100 kW
PV array is modeled using 63 parallel connected strings with
each string having 8 series connected PV modules (KyoceraKD 200GT). The output of the array is connected to the grid
4
Vol. 1, No. 3, December 2013
Voltage (V)
International Journal of Advances in Power Systems (IJAPS)
ISSN: 2335-1772
PV Array : Kyocera KC200GT of 8 series modules; 63 parallel strings
400
200
0
0
0.5
1
1.5
2
1.5
2
1.5
2
Current (A)
Time (S)
1000
500
0
0
0.5
1
Power (kW)
Time (S)
Fig. 12 The MATLAB/SIMULINK model of the grid connected PV system
200
100
0
A. STEADY STATE ANALYSIS
0.5
Voltage (V)
B. FAULT ANALYSIS
In this section the MATLAB/SIMULINK model shown in
Fig.12 is simulated under different fault conditions. The
simulation is accomplished under nominal condition (G =
2
1000 W/m and T=250 C). As shown in Fig. 12 the fault is
applied on the grid side. The fault duration is 0.1s from 0.2
to 0.3 s. In this section all types of faults will be discussed
under the same condition.
 Line-to-ground fault
The model shown in Fig. 12 is simulated while applying
single line to ground fault (1L-G) on phase A. the fault
location is illustrated in Fig. 12 and the fault duration is 100
ms. The output voltage and current at the point of common
coupling PCC are shown in Fig. 16.
1
1.5
2
1.5
2
1.5
2
Time (S)
1000
500
0
0.5
1
5
Time (S)
200
Voltage (V)
0
Power (kW)
Current (A)
MPPT Based FLC.
PV Array : Kyocera KC200GT of 8 series modules; 63 parallel strings
0
100
0
0
0.5
1
Time (S)
Fig.13 The output power, voltage and current of the PV array
Grid Voltage at PCC With 1L-G
0
0.1
PV Array : Kyocera KC200GT of 8 series modules; 63 parallel strings
0.2
0.3
0.4
0.5
0.4
0.5
Grid Current at PCC With 1L-G
40
200
0
0
0.5
1
1.5
Current (A)
Voltage (V)
4
Time (S)
2
Time (S)
Current (A)
x 10
-5
0
With MPPT Based P&O
400
1
Fig. 15 The output power, voltage and current of the PV array with
200
0
0.5
Time (S)
First the simulation is accomplished while the PV array
operates at nominal conditions (1000W/m2&25°C). The
simulation is run three times; first, the Perturb and Observe
algorithm is applied, second the incremental conductance
algorithm is applied, and finally the fuzzy logic algorithm is
applied. The output voltage, current, and power of the PV
array while applying the three different algorithms P&O, ICT
and FLC are shown in Fig.13, Fig. 14 and Fig. 15
respectively. It can be observed that PV array feeds100kW to
the grid while utilizing the three algorithms but the
proposed FLC gives a faster response when compared with
the others.
400
0
1000
0
-20
500
0
20
0
0.5
1
1.5
0
0.1
0.2
0.3
Time (S)
2
Power (kW)
Time (S)
200
Fig. 16 The output voltage and current at the PCC with single line to ground
fault
100
0
0
0.5
1
1.5
2
The simulation was run three times under condition of
applying a single line to ground fault while utilizing the three
MPPT algorithms discussed in section III. Fig. 17 shows the
output power at the array terminal for the three cases.
Time (S)
Fig. 14 The output power, voltage and current of the PV array
With MPPT Based ICT
5
International Journal of Advances in Power Systems (IJAPS)
ISSN: 2335-1772
different maximum power point tracking algorithms while
applying this type of fault is shown in Fig. 21.
P&O
ICT
FLC
50
0
0
0.5
1
1.5
x 10
5
Voltage (V)
Power (kW)
Output Power of the PV array using the three different algorithms at 1L-G
100
Vol. 1, No. 3, December 2013
2
Time (S)
4
Grid Voltage at PCC With L-L-G
0
-5
0
0.1
0.2
Fig.17 The output power of the PV array using the three different
40
Current (A)
algorithms with 1LG fault
 Line-to-line Fault
In this case the model shown in Fig. 12 is simulated with
applying a line to line fault (L-LF) between phases A and B.
The voltage and the current at the PCC are shown in Fig.18.
x 10
4
0.4
0.5
0
0
0.1
0.2
0.3
Time (S)
Grid Voltage at PCC With L-L
Fig. 20 The output voltage and current at the PCC with L-L-G fault
Output Power of the PV array using the three different algorithms at L-L-G
100
0
0.1
0.2
0.3
0.4
0.5
Time (S)
Grid Current at PCC With L-L
20
Current (A)
0.5
-20
-40
0
-5
P&O
ICT
FLC
50
0
0
0.5
1
1.5
2
Time (S)
Fig. 21 Output power of The PV array using the three different algorithms with
L-L-G fault
0
-20
0
0.1
0.2
0.3
0.4
 Three line to ground fault
A three line to ground (L-L-L-G) fault is applied to the
model shown in Figure 12. Fig. 22 shows the output voltage
and current at the PCC. Fig. 23 shows the output power of
the PV array while applying the three MPPT techniques for
this type of fault.It noteworthy that the proposed FLC
succeeds to sustain the stability of the MPPT during the fault
while the other two conventional techniques fail.
0.5
Time (S)
Fig.18 The output voltage and current at the PCC with L-L fault
In order to compare the performance of the three MPPT
algorithms mention above to this type of fault, the model is
run three times; each time one algorithm is implemented.
The output power of the PV array under the three cases is
shown in Fig. 19.
5
P&O
ICT
FLC
50
0
Voltage (V)
Output Power of the PV array using the three different algorithms at L-L
100
Power (kW)
0.4
20
Power (kW)
Voltage (V)
5
0.3
Time (S)
Grid Current at PCC With L-L-G
0
0.5
1
1.5
0
0.1
Current (A)
0.2
0.3
0.4
0.5
0.4
0.5
Time (S)
Grid Current at PCC With L-L-L-G
0
-20
-40
 Line-to-line-to-ground fault
A line-to-line-to ground (L-L-G) fault is applied to the
model shown in Fig. 12. The voltage and current waveforms
for this case at the point of common coupling are shown in
Fig. 20.
Grid Voltage at PCC With L-L-L-G
20
2
Fig.19 The output power of the PV array using the three different algorithms
with L-L fault
4
0
-5
Time (S)
x 10
0
0.1
0.2
0.3
Time (S)
Fig.22 The output voltage and current at point of common coupling (PCC)
with L-L-L-G fault.
The output power at the array terminal of the three
6
International Journal of Advances in Power Systems (IJAPS)
ISSN: 2335-1772
Vol. 1, No. 3, December 2013
Output Power of the PV array using the three different algorithms at L-L-L-G
50
0
Output Power of the PV array using the three different algorithms at Voltage Dips
P&O
ICT
FLC
0
0.2
0.4
0.6
0.8
P&O
ICT
FLC
100
Power (kW)
Power (kW)
100
50
1
0
0
Time (S)
0.5
1
1.5
2
Time (S)
Fig.23 The output power of the PV array using the three different algorithms
with L-L-L-G fault
Fig.26 Output power of The PV array using the three different algorithms under
voltage sag
C. VOLTAGE SAGS ANALYSIS
D. VOLTAGE SWELLS
The decrease in the RMS value of the voltage or current
between 0.9 to 0.1 p.u. for duration of 0.5 cycle to 1 minute is
defined as voltage sag. Voltage sags are generally caused by
over loading or grid faults. The MATLAB/SIMULINK
model shown in Fig. 24 is utilized to conduct the analysis in
this section. The model shown in Fig. 24 is simulated under
condition of voltage sag at the point of common coupling for
a duration of 0.15 s.
The increase in the RMS voltage or current between 1.1 to
1.8 p.u. for a duration of 0.5 cycle to 1 minute is defined as
voltage swell. Voltage swells are normally initiated by the
disconnection of a very large load, the energization of a large
capacitor bank and voltage swells are usually associated with
the system fault conditions. Fig. 24 shows the grid connected
PV array MATLAB/SIMULINK model which utilizes in this
section. The system is studied under voltage swells of 0.15 s
duration.
In order to studying the effect of voltage swells, the voltage
at the PCC is increased from 20 kV to 26 kV as shown in Fig.
27.
x 10
Voltage (V)
5
Fig. 24 Grid Connected PV system under sag Analysis
Voltage (V)
5
x 10
4
Current (A)
0.2
0.3
0.4
0.5
0.4
0.5
Time (S)
Grid Current at PCC With Voltage Swell
0
0.1
0.2
0.3
Time (S)
Fig.27 The output voltage at the PCC in case of voltage increase by 30%
0
0.1
0.2
0.3
0.4
The PV array output power of the three MPPT algorithms
in case of voltage swell is shown in Fig. 28. It can be
observed that, the FLC has a good response and is not
affected with the disturbances occurred on the grid side.
0.5
Time (S)
Grid Current at PCC With Voltage Dips
0
Output Power of the PV array using the three different algorithms at Voltage Swell
0
0.1
0.2
0.3
0.4
100
0.5
Power (kW)
-20
0.1
0
-20
Grid Voltage at PCC With Voltage Dips
20
Current (A)
0
20
0
-5
Grid Voltage at PCC With Voltage Swell
0
-5
In order to study the effect of voltage sag on the
performance of the three MPPT algorithms under study in this
paper, the voltage at the PCC is reduced from 20kV to 10kV.
The output voltage and current at the PCC is shown in Fig.
25.
4
Time (S)
Fig.25 The output voltage and current at PCC in case of voltage decrease by
50%
50
0
The simulation is run three times and each time one of the
MPPT algorithms is employed while operating the PV array
at nominal condition. Fig. 26 shows the output power of the
PV array in the three cases. It can be observed that FLC has
a faster response and is not affected with the disturbances
occurred on the grid side.
P&O
ICT
FLC
0
0.5
1
Time (S)
1.5
Fig.28 Output power of the PV Array using the three different algorithms
under voltage swell condition
7
2
International Journal of Advances in Power Systems (IJAPS)
ISSN: 2335-1772
VI. CONCLUSION
In this paper, a 100 kW grid connected photovoltaic array
is studied under steady state and transient conditions while
utilizing three different maximum power point tracking
algorithms. The three algorithms employed in this paper are:
the perturb and observe (P&O) algorithm; the incremental
conductance (ICT) algorithm and the fuzzy logic control
(FLC) algorithm. The simulated results under steady state
condition show the effectiveness of the MPPT on increasing
the output power of the PV array for the three techniques.
However the FLC algorithm offers accurate and faster
compared to the conventional techniques. The simulation
results under transient conditions show that the output power
injected to grid from PV array is approximately constant
while utilizing the proposed FLC and the PV system can still
connect to grid and deliver power to grid without any damage
to the inverter switches.
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