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International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075, Volume-3, Issue-4, September 2013
108
Abstract—The output power of a photovoltaic generator is
related to many climatic factors like temperature and solar
illumination; it is then necessary to track the maximum power
point in real time to optimize the photovoltaic system efficiency.
This work presents the modeling of a photovoltaic system with a
maximum power point tracking (MPPT).
The operating of the photovoltaic system and the improvement
of its efficiency taking into account rapid variations of
meteorological conditions is presented with a MPPT based on
perturb and observe (P&O) strategy, both implemented using
Matlab. Simulation results showed that operating point oscillates
around maximum power point and these oscillations are
proportional to the variations of the incident illumination.
Index Terms — photovoltaic generator, MPPT, Matlab
I. INTRODUCTION
Electrical energy needs are still increasing overthese last
years but production constraints like pollution [1] and global
warming [2] lead to development of renewable energy
sources, particularly photovoltaic energy. Due to very
limited conversion efficiency [3], it is necessary to optimize
all the conversion chain and specifically DC-DC converters
by use to maximum power point tracking strategies [4]
(figure 1).
Figure 1: Block diagram of typical MPPT system.
II. PHOTOVOLTAIC GENERATOR MODELING
Photovoltaic generatorsconsist usually of several modules
interconnected in series and parallel for a given operating
voltage an output power [5]. Photovoltaic generators
modeling can then be deduced from those of solar cells;
many studies have been already proposed using onediode or
more precise two diodes models. In this paper we use the
conventionalsingle diode model presented on (figure 2).
Manuscript received September, 2013.
Mr. Ahmd Yahfdhou, Physics Department, FST-UCAD, Dakar,
Senegal.
Prof. Abel Kader Mahmoud, PhysicsDepartment, FST-UN,
Nouakchott, Mauritania,
Prof. IssakhaYoum, Physics Department, FST-UCAD, Dakar, Senegal.
Figure 2: Conventional single diode model.
Iph is the photogenerated current related to the illumination
level, Id the diode current, Rsh and Rs are respectively the
shunt and series resistances.
Based on (figure 2), the output voltage and current
dependence can be written in the form [6]:
sh
sV
IRV
ph
R
IRV
eIII t
s
+
−








−−=
+
10 (1)
- Vt is the thermal voltage written as: Vt= ( A*K*T)/q
where A is the ideality factor, K the Boltzmann
constant, T the temperature of the cell and q the
elementary charge.
- I0 is the dark current.
Compared to the measured photocurrent Iph_ref at standard
tests conditions (STC: Gref =1000W/m², Tref =25°C), the
photocurrent at another operating conditions can
beexpressed as:
( )[ ]REFREFPH
REF
ph TTI
G
G
I −+= α, (2)
G is thesolar irradiance, α is the short circuit current
temperature coefficient.
Iph_ref can be taken to be the short current at STC (Icc_ref),
Icc_ref and α are generally given by solar module
manufacturer. In the case where the cell temperature Tambnot
is determined directly by a temperature sensor, it can be
deduced from the following relation:
G
N
TT oct
amb 




 −
+=
800
20
(3)
Tamb is the ambient temperature, Noct is the normal operating
cell temperature given in most cases by the manufacturer.
For the dark current I0 and we can write:












−





=
TTAK
qE
T
T
II
REF
g
A
REF
REF
11
exp
3
,00
(4)
I0,ref is the dark current at STC and Eg is the forbidden band
energy.
In the single diode model, we assumed Rsh to be infinite; the
series resistance can be derived in the form [6]:
Ahmed Yahfdhou, Abel Kader Mahmoud, Issakha Youm
Modeling and Optimization of a Photovoltaic
Generator with Matlab/Simulink
Modeling and Optimization of a Photovoltaic Generator with Matlab/Simulink
109
( )






−−=
AKT
qV
I
q
AKT
dI
dV
R
OCVoc
s
exp0
(5)
Equation (1) can be solved by numerical method likeNewton
Raphsons [5].
)('
)(
1
n
n
nn Xf
Xf
XX −=+
(6)
III.MAXIMUM POWER POINT TRACKING
The maximum power point tracking is a very difficult task
essentially because the photovoltaic generator I-V curve
depends on both incident power and operating temperature.
Many methods have been proposed [6]-[8], but perturb
&observe (P&O)method seems to be most used one [9]-
[11]. The P&O is an iterative techniquethat
perturbsphotovoltage Vpv and analyses the behavior of the
resulting power as presented on figure 3.
Figure 3: Behavior of P&O MPPT algorithm with P-V
curve.
For an increment in Vpv, if the output power ∆Ps greater
than zero (Vpv>0), we are moving to maximum power point
MPP; if ∆P <0 then we are moving away of the MPP. In
each case, the control algorithm is presented on figure 4.
Figure 4: Algorithm diagram of perturb &observe
(P&O)method.
IV.SIMULATION RESULTS AND DISCUSSIONS
The whole simulation is based on experimental data ofsolar
irradiance and temperature for a day at Nouakchott (fig. 5).
Figure 5: Solar irradiance (a) and temperature (b) at
Nouakchott in February.
Figure 6:Shows the I-V and P-V curves of the photovoltaic
generator under different levels of illumination.
Figure 6: Irradiance dependence of I-V and P-
Vcharacteristics of a PV generator.
As it can be seen from this figure, the short circuit current is
directly proportional to the irradiance contrary to the open
circuit voltage variation much smaller (it depends
logarithmically on the irradiance).
Figure 7 illustrates the influence of the operating
temperature on the I-V curve.
Figure 7: Temperature effect on the I-V and P-V curves.
7:00 8:40 10:20 12:00 13:40 15:20 17:00 18:44
0
200
400
600
800
Time (Hours)
Incidentpower(W/m²)
7:00 8:40 10:20 12:00 13:40 15:20 17:00 18:44
10
20
30
40
Time (Hours)
Temperature(°C)
(a)
(b)
0 5 10 15 20
1
2
3
4
5
Photocurrent(A)
Photo voltage (V)
0 5 10 15 20
15
30
45
60
Outputpower(W)
0 5 10 15 20
15
30
45
60
Outputpower(W)
0 5 10 15 20
15
30
45
60
Outputpower(W)
0 5 10 15 20
15
30
45
60
Outputpower(W)
0 5 10 15 20
15
30
45
60
Outputpower(W)
0 5 10 15 20 25
2
4
6
Photocurrent(A)
Photo voltage (V)
0 5 10 15 20 25
20
40
60
80
Outputpower(W)
0 5 10 15 20 25
20
40
60
80
Outputpower(W)
0 5 10 15 20 25
20
40
60
80
Outputpower(W)
0 5 10 15 20 25
20
40
60
80
Outputpower(W)
International Journal of Innovative Technology and Exploring Engineering (IJITEE)
ISSN: 2278-3075, Volume-3, Issue-4, September 2013
110
The most significant is the temperature dependence the open
circuit voltage which decreases with increasing temperature.
The transmission of electric current produced by the PV
generator involves ohmic losses. These can be grouped
together and included as a resistance in the equivalent circuit
(fig. 2). It is seen that the series resistance affects the PV
generator operation mainly by reducing the fill factor
(figure. 8).
Figure 8: effect of the series resistance on the I-V and P-V
curves.
Thisalso explains whenincreasing series resistance, the
voltage across the cell decreases rapidly.
The profile of the P-V curve and the I-V curve is presented
to exhibit the efficiency of the control algorithm (figures 9
and 10) when tracking the MPP.
Figure 9: P-V curve and calculated maximum power point
(MPP).
Figure 10: I-V curve and calculated VMPP and IMPP.
According to these figure, it can be seen that despite
variation of operating conditions, our technique tracks is
very efficiency the maximum power point. This efficiency
can be calculated from equation following [12]:
( )
( )∫
∫
= t
t
MPPT
dttP
dttPact
0
0
max
α
(7)
Pact is the output power of the photovoltaic generator with
P&O algorithm and Pmax is the maximum is the maximum
theoretical power that can be produced by the photovoltaic
generator. Figure 11 exhibits the comparison between Pact
(P&O) and Pmax.
Figure 11: Comparison of the theoretical maximum power
and the maximum power (P&O).
A very good agreement is obtained between the theoretical
maximum output power and the maximum power calculated
by mean of the P&O technique based on Nouakchott
meteorological conditions. This agreement can be seen
directly with the efficiency of the control algorithm on
figure 12.
Figure 12: Efficiency of the maximum power point tacking
(P&O).
The obtained efficiency is near 99, 5% leading to a very
efficiency control technique.
0 5 10 15 20
2
4
6
Photocurrent(A)
Photo voltage (V)
0 5 10 15 20
20
40
60
85
Outputpower(W)
0 5 10 15 20
20
40
60
85
Outputpower(W)
0 5 10 15 20
20
40
60
85
Outputpower(W)
0 5 10 15 20
20
40
60
85
Outputpower(W)
0 5 10 15 20
0
5
10
15
20
25
30
35
40
45
50
55
Photovoltage (V)
Outputpower(W)
750W/m²
600W/m²
450W/m²
300W/m²
150W/m²
0 2 4 6 8 10 12 14 16 18 20 22
0
0.5
1
1.5
2
2.5
3
3.5
4
Photo voltage (V)
Photocurrent(A)
750W/m²
600W/m²
450W/m²
300W/m²
150W/m²
7:00 8:40 10:20 12:00 13:40 15:20 17:00 18:44
0
5
10
15
20
25
30
35
40
45
50
Time (Hours)
Outputpower(W)
P&O
Pmax
8:40 10:20 12:00 13:40 15:20 17:00 18:08
91
92
93
94
95
96
97
98
99
100
Time (Hours)
EfficiencyoftheP&Oalgorithm(%)
Modeling and Optimization of a Photovoltaic Generator with Matlab/Simulink
111
V. CONCLUSION
We presented in this study a mathematical model in order to
simulate the behavior of a photovoltaic generator in a reel
operating conditions.
Based on this model, we exhibited the effects of incident
power, temperature and series resistance on both I-V curve
and P-V curve. We also proved that perturb and observe
algorithm is an efficient technique to optimize the operating
of a photovoltaic generator.
REFERENCES
[1] Askarzadeh, A. Razazadeh, “Extraction of maximum power point in
solar cells using bird mating optimizer-based parameters
identification approach”, Solar Energy 90, pp. 123-133, 2013.
[2] M. R. Alrashidi, M. F. Alhajri, K.M. El-naggar, A. K. Al-othman,
“A new estimation approach for determining the I-V characteristics
of solar cells”, Solar Energy 85, pp. 1543-1550, 2011.
[3] M. Seifi, A. B. Chesoh, N. I. Abdwahab, M.KB. Hasan, “A
comparative study of PV models in Matlab/Simulink”, Word
Academy of Science, Engineering and Technology 74, pp. 108-113,
2013.
[4] M. Yahya, I. Youm, A. Kader, “Behavior and performance of a
photovoltaic generator in real time”, International Journal of the
Physical Science 6(18),pp. 4361-4367, 2011.
[5] D. Bonkoungou, Z. Koalaga, D. Njomo, “Modeling and simulation
of photovoltaic module considering single-diode equivalent circuit
model in Matlab”, International Journal of Emerging Technology
and Advanced Engineering 3(3), pp. 493-502, 2013.
[6] Salas, E. Olias, A. Barrado, A. Lazaro, “Review of the maximum
power point tracking algorithms for stand-alone photovoltaic
systems”, Solar Energy Material & solar cells 90, pp.1555-1578,
2006.
[7] T. Papaioannou, A. Purvins, “Mathematical and graphical approach
for maximum power point modeling”, Applied Energy 91, pp. 59-
66, 2012.
[8] B. Amrouche, A. Guessoum, M. Belhamel, “A simple behavioral
model for solar module electric characteristics based on the first
order system step response for MPPT study and comparison”
Applied Energy 91, pp. 395-404, 2012.
[9] N. Femia, G. petrone, G. Spagnulo, M. Vitelli, “Optimization of
perturb and observe maximum power point tracking method”, IEEE
Transactions on power Electronics 20, pp. 963-973, 2005.
[10] S.Lal, R.Dhtash, S.Sinha, “Analysis different MPPT technique for
photovoltaic system, International Journal of Engineering and
Innovative Technology 06, pp. 1-3, 2012
[11] Yadav, S. Thirumaliah, G. Haritha, “Comparison of MPPT
algorithms for dc-dc converters based PV systems”, International
Journal of Advanced Research in Electrical, Electronics and
Instrumentation Engineering, PP. 18-23, 2012.
[12] S.Brunton, C.Rowley, S.Kulkani , C.Clarkson, ”Maximum power
point tracking for photovoltaic optimization using ripple-based
extremum seeking control”, IEEE transactions on power electronics,
PP. 1-20, 2010.
Mr. Ahmed Yahfdhou [yahevdhouah@yahoo.fr] was born in Elb-
adress, Mauritania, in 1978. He received his Master degree in Solar
Energy, Materials and Systems from College of Sciences and Technics,
Dakar, Senegal, Cheikh Anta DIOP University in the year 2010. He is
working on his doctorate thesis at Cheikh Anta DIOP University Dakar,
Senegal. The interest of his research is about the field of Renewable Energy
and Semiconductor devices characterization.
Prof. Abel Kader Mahmoud [mkader@univ-nkc.mr] was born in
Mauritania. He received his Doctorate degree in 2009 in Solar Energy from
FST, Dakar, Cheikh Anta Diop University. He is working as prof, in the
Physics department of Nouakchott University, Mauritania. He is also the
director of the Applied Center of Renewable Energy in Mauritania. His
research interest in the field of Renewable Energy, Electrical Engineering
and reverse osmosis.
Prof. Issakha Youm [iyoum2@yahoo.fr] was born in Ngaparou, Senegal.
His received his Doctorate degree in 1991 in Solar Energy from FST,
Dakar, Cheikh Anta DIOP University. He is working as Prof. in the Physics
Department of Cheikh Anta DIOP University Dakar, Senegal. He is also the
director of the Center of the Study and Research of the Renewable Energy,
Senegal. His research interest is in the field of Renewable Energy and
Semiconductor devices characterization

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Modeling and Optimization of a Photovoltaic Generator with Matlab

  • 1. International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-3, Issue-4, September 2013 108 Abstract—The output power of a photovoltaic generator is related to many climatic factors like temperature and solar illumination; it is then necessary to track the maximum power point in real time to optimize the photovoltaic system efficiency. This work presents the modeling of a photovoltaic system with a maximum power point tracking (MPPT). The operating of the photovoltaic system and the improvement of its efficiency taking into account rapid variations of meteorological conditions is presented with a MPPT based on perturb and observe (P&O) strategy, both implemented using Matlab. Simulation results showed that operating point oscillates around maximum power point and these oscillations are proportional to the variations of the incident illumination. Index Terms — photovoltaic generator, MPPT, Matlab I. INTRODUCTION Electrical energy needs are still increasing overthese last years but production constraints like pollution [1] and global warming [2] lead to development of renewable energy sources, particularly photovoltaic energy. Due to very limited conversion efficiency [3], it is necessary to optimize all the conversion chain and specifically DC-DC converters by use to maximum power point tracking strategies [4] (figure 1). Figure 1: Block diagram of typical MPPT system. II. PHOTOVOLTAIC GENERATOR MODELING Photovoltaic generatorsconsist usually of several modules interconnected in series and parallel for a given operating voltage an output power [5]. Photovoltaic generators modeling can then be deduced from those of solar cells; many studies have been already proposed using onediode or more precise two diodes models. In this paper we use the conventionalsingle diode model presented on (figure 2). Manuscript received September, 2013. Mr. Ahmd Yahfdhou, Physics Department, FST-UCAD, Dakar, Senegal. Prof. Abel Kader Mahmoud, PhysicsDepartment, FST-UN, Nouakchott, Mauritania, Prof. IssakhaYoum, Physics Department, FST-UCAD, Dakar, Senegal. Figure 2: Conventional single diode model. Iph is the photogenerated current related to the illumination level, Id the diode current, Rsh and Rs are respectively the shunt and series resistances. Based on (figure 2), the output voltage and current dependence can be written in the form [6]: sh sV IRV ph R IRV eIII t s + −         −−= + 10 (1) - Vt is the thermal voltage written as: Vt= ( A*K*T)/q where A is the ideality factor, K the Boltzmann constant, T the temperature of the cell and q the elementary charge. - I0 is the dark current. Compared to the measured photocurrent Iph_ref at standard tests conditions (STC: Gref =1000W/m², Tref =25°C), the photocurrent at another operating conditions can beexpressed as: ( )[ ]REFREFPH REF ph TTI G G I −+= α, (2) G is thesolar irradiance, α is the short circuit current temperature coefficient. Iph_ref can be taken to be the short current at STC (Icc_ref), Icc_ref and α are generally given by solar module manufacturer. In the case where the cell temperature Tambnot is determined directly by a temperature sensor, it can be deduced from the following relation: G N TT oct amb       − += 800 20 (3) Tamb is the ambient temperature, Noct is the normal operating cell temperature given in most cases by the manufacturer. For the dark current I0 and we can write:             −      = TTAK qE T T II REF g A REF REF 11 exp 3 ,00 (4) I0,ref is the dark current at STC and Eg is the forbidden band energy. In the single diode model, we assumed Rsh to be infinite; the series resistance can be derived in the form [6]: Ahmed Yahfdhou, Abel Kader Mahmoud, Issakha Youm Modeling and Optimization of a Photovoltaic Generator with Matlab/Simulink
  • 2. Modeling and Optimization of a Photovoltaic Generator with Matlab/Simulink 109 ( )       −−= AKT qV I q AKT dI dV R OCVoc s exp0 (5) Equation (1) can be solved by numerical method likeNewton Raphsons [5]. )(' )( 1 n n nn Xf Xf XX −=+ (6) III.MAXIMUM POWER POINT TRACKING The maximum power point tracking is a very difficult task essentially because the photovoltaic generator I-V curve depends on both incident power and operating temperature. Many methods have been proposed [6]-[8], but perturb &observe (P&O)method seems to be most used one [9]- [11]. The P&O is an iterative techniquethat perturbsphotovoltage Vpv and analyses the behavior of the resulting power as presented on figure 3. Figure 3: Behavior of P&O MPPT algorithm with P-V curve. For an increment in Vpv, if the output power ∆Ps greater than zero (Vpv>0), we are moving to maximum power point MPP; if ∆P <0 then we are moving away of the MPP. In each case, the control algorithm is presented on figure 4. Figure 4: Algorithm diagram of perturb &observe (P&O)method. IV.SIMULATION RESULTS AND DISCUSSIONS The whole simulation is based on experimental data ofsolar irradiance and temperature for a day at Nouakchott (fig. 5). Figure 5: Solar irradiance (a) and temperature (b) at Nouakchott in February. Figure 6:Shows the I-V and P-V curves of the photovoltaic generator under different levels of illumination. Figure 6: Irradiance dependence of I-V and P- Vcharacteristics of a PV generator. As it can be seen from this figure, the short circuit current is directly proportional to the irradiance contrary to the open circuit voltage variation much smaller (it depends logarithmically on the irradiance). Figure 7 illustrates the influence of the operating temperature on the I-V curve. Figure 7: Temperature effect on the I-V and P-V curves. 7:00 8:40 10:20 12:00 13:40 15:20 17:00 18:44 0 200 400 600 800 Time (Hours) Incidentpower(W/m²) 7:00 8:40 10:20 12:00 13:40 15:20 17:00 18:44 10 20 30 40 Time (Hours) Temperature(°C) (a) (b) 0 5 10 15 20 1 2 3 4 5 Photocurrent(A) Photo voltage (V) 0 5 10 15 20 15 30 45 60 Outputpower(W) 0 5 10 15 20 15 30 45 60 Outputpower(W) 0 5 10 15 20 15 30 45 60 Outputpower(W) 0 5 10 15 20 15 30 45 60 Outputpower(W) 0 5 10 15 20 15 30 45 60 Outputpower(W) 0 5 10 15 20 25 2 4 6 Photocurrent(A) Photo voltage (V) 0 5 10 15 20 25 20 40 60 80 Outputpower(W) 0 5 10 15 20 25 20 40 60 80 Outputpower(W) 0 5 10 15 20 25 20 40 60 80 Outputpower(W) 0 5 10 15 20 25 20 40 60 80 Outputpower(W)
  • 3. International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-3, Issue-4, September 2013 110 The most significant is the temperature dependence the open circuit voltage which decreases with increasing temperature. The transmission of electric current produced by the PV generator involves ohmic losses. These can be grouped together and included as a resistance in the equivalent circuit (fig. 2). It is seen that the series resistance affects the PV generator operation mainly by reducing the fill factor (figure. 8). Figure 8: effect of the series resistance on the I-V and P-V curves. Thisalso explains whenincreasing series resistance, the voltage across the cell decreases rapidly. The profile of the P-V curve and the I-V curve is presented to exhibit the efficiency of the control algorithm (figures 9 and 10) when tracking the MPP. Figure 9: P-V curve and calculated maximum power point (MPP). Figure 10: I-V curve and calculated VMPP and IMPP. According to these figure, it can be seen that despite variation of operating conditions, our technique tracks is very efficiency the maximum power point. This efficiency can be calculated from equation following [12]: ( ) ( )∫ ∫ = t t MPPT dttP dttPact 0 0 max α (7) Pact is the output power of the photovoltaic generator with P&O algorithm and Pmax is the maximum is the maximum theoretical power that can be produced by the photovoltaic generator. Figure 11 exhibits the comparison between Pact (P&O) and Pmax. Figure 11: Comparison of the theoretical maximum power and the maximum power (P&O). A very good agreement is obtained between the theoretical maximum output power and the maximum power calculated by mean of the P&O technique based on Nouakchott meteorological conditions. This agreement can be seen directly with the efficiency of the control algorithm on figure 12. Figure 12: Efficiency of the maximum power point tacking (P&O). The obtained efficiency is near 99, 5% leading to a very efficiency control technique. 0 5 10 15 20 2 4 6 Photocurrent(A) Photo voltage (V) 0 5 10 15 20 20 40 60 85 Outputpower(W) 0 5 10 15 20 20 40 60 85 Outputpower(W) 0 5 10 15 20 20 40 60 85 Outputpower(W) 0 5 10 15 20 20 40 60 85 Outputpower(W) 0 5 10 15 20 0 5 10 15 20 25 30 35 40 45 50 55 Photovoltage (V) Outputpower(W) 750W/m² 600W/m² 450W/m² 300W/m² 150W/m² 0 2 4 6 8 10 12 14 16 18 20 22 0 0.5 1 1.5 2 2.5 3 3.5 4 Photo voltage (V) Photocurrent(A) 750W/m² 600W/m² 450W/m² 300W/m² 150W/m² 7:00 8:40 10:20 12:00 13:40 15:20 17:00 18:44 0 5 10 15 20 25 30 35 40 45 50 Time (Hours) Outputpower(W) P&O Pmax 8:40 10:20 12:00 13:40 15:20 17:00 18:08 91 92 93 94 95 96 97 98 99 100 Time (Hours) EfficiencyoftheP&Oalgorithm(%)
  • 4. Modeling and Optimization of a Photovoltaic Generator with Matlab/Simulink 111 V. CONCLUSION We presented in this study a mathematical model in order to simulate the behavior of a photovoltaic generator in a reel operating conditions. Based on this model, we exhibited the effects of incident power, temperature and series resistance on both I-V curve and P-V curve. We also proved that perturb and observe algorithm is an efficient technique to optimize the operating of a photovoltaic generator. REFERENCES [1] Askarzadeh, A. Razazadeh, “Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach”, Solar Energy 90, pp. 123-133, 2013. [2] M. R. Alrashidi, M. F. Alhajri, K.M. El-naggar, A. K. Al-othman, “A new estimation approach for determining the I-V characteristics of solar cells”, Solar Energy 85, pp. 1543-1550, 2011. [3] M. Seifi, A. B. Chesoh, N. I. Abdwahab, M.KB. Hasan, “A comparative study of PV models in Matlab/Simulink”, Word Academy of Science, Engineering and Technology 74, pp. 108-113, 2013. [4] M. Yahya, I. Youm, A. Kader, “Behavior and performance of a photovoltaic generator in real time”, International Journal of the Physical Science 6(18),pp. 4361-4367, 2011. [5] D. Bonkoungou, Z. Koalaga, D. Njomo, “Modeling and simulation of photovoltaic module considering single-diode equivalent circuit model in Matlab”, International Journal of Emerging Technology and Advanced Engineering 3(3), pp. 493-502, 2013. [6] Salas, E. Olias, A. Barrado, A. Lazaro, “Review of the maximum power point tracking algorithms for stand-alone photovoltaic systems”, Solar Energy Material & solar cells 90, pp.1555-1578, 2006. [7] T. Papaioannou, A. Purvins, “Mathematical and graphical approach for maximum power point modeling”, Applied Energy 91, pp. 59- 66, 2012. [8] B. Amrouche, A. Guessoum, M. Belhamel, “A simple behavioral model for solar module electric characteristics based on the first order system step response for MPPT study and comparison” Applied Energy 91, pp. 395-404, 2012. [9] N. Femia, G. petrone, G. Spagnulo, M. Vitelli, “Optimization of perturb and observe maximum power point tracking method”, IEEE Transactions on power Electronics 20, pp. 963-973, 2005. [10] S.Lal, R.Dhtash, S.Sinha, “Analysis different MPPT technique for photovoltaic system, International Journal of Engineering and Innovative Technology 06, pp. 1-3, 2012 [11] Yadav, S. Thirumaliah, G. Haritha, “Comparison of MPPT algorithms for dc-dc converters based PV systems”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, PP. 18-23, 2012. [12] S.Brunton, C.Rowley, S.Kulkani , C.Clarkson, ”Maximum power point tracking for photovoltaic optimization using ripple-based extremum seeking control”, IEEE transactions on power electronics, PP. 1-20, 2010. Mr. Ahmed Yahfdhou [yahevdhouah@yahoo.fr] was born in Elb- adress, Mauritania, in 1978. He received his Master degree in Solar Energy, Materials and Systems from College of Sciences and Technics, Dakar, Senegal, Cheikh Anta DIOP University in the year 2010. He is working on his doctorate thesis at Cheikh Anta DIOP University Dakar, Senegal. The interest of his research is about the field of Renewable Energy and Semiconductor devices characterization. Prof. Abel Kader Mahmoud [mkader@univ-nkc.mr] was born in Mauritania. He received his Doctorate degree in 2009 in Solar Energy from FST, Dakar, Cheikh Anta Diop University. He is working as prof, in the Physics department of Nouakchott University, Mauritania. He is also the director of the Applied Center of Renewable Energy in Mauritania. His research interest in the field of Renewable Energy, Electrical Engineering and reverse osmosis. Prof. Issakha Youm [iyoum2@yahoo.fr] was born in Ngaparou, Senegal. His received his Doctorate degree in 1991 in Solar Energy from FST, Dakar, Cheikh Anta DIOP University. He is working as Prof. in the Physics Department of Cheikh Anta DIOP University Dakar, Senegal. He is also the director of the Center of the Study and Research of the Renewable Energy, Senegal. His research interest is in the field of Renewable Energy and Semiconductor devices characterization