International Journal on Electrical Engineering and Informatics - Volume 14, Number 3, September 2022

High Performance MPPT Controller for Solar Photovoltaic System

under Variable Solar Irradiations
Hichem CHOUIAL1, Hocine LABAR1, Mounia Samira KELAIAIA1, Salah NECAIBIA1,
Ammar NECAIBIA2, Okba DJELAILIA1, Faycel MERAD1
1
Department of Electrical Engineering, Faculty of Technology, Badji Mokthar University,
BP 12 Sidi Amar, 23000 Annaba, Algeria
2
Unité de Recherche en Energies Renouvelables en Milieu Saharien, URERMS, Centre de
Développement des Energies Renouvelables CDER 01000, Adrar, Algeria

Abstract: In this paper a comparative study through experimental verification between a novel
low-cost maximum power point tracking (MPPT) and the conventional approach for
photovoltaic (PV) system under variable and real scenario of solar irradiations is presented. The
whole suggested system simulated using ISIS PROTEUS software. In the offered PV scheme, a
novel MPPT technique is added in the command part of the DC-DC converter, this new method
is applied to offer different regions of operation in order to reach the MPP as quickly as possible
with low fluctuations. In each zone, the step-size is changed according to the proximity to the
MPP. With this strategy, some disadvantages of the incremental conductance (IncCond)
technique is prevented. The simulation results show a high tracking precision and a fast
convergence speed of the proposed technique. In fact, the experimental results are very similar
to those obtained through simulation, validating the advantages of the proposed method, such as
its precision and good tracking time.

Keywords: PV system; Boost Converter; MPPT; IncCond algorithm;

1. Introduction
Recently, in the last decades, the demands on the natural resources are rapidly increasing due
to the fact of the fast depleting of both coal and petroleum ones, not to mention the pressure it
adds to the power supply [1][2], which would be resulting into an inevitable threat of a global
energy crisis. For those new forms of highly reliable energy sources must be harnessed and
developed [3][4]. The renewable energy resources such as (solar, wind, rain, biomass, biogas,
ocean, tides, geothermal heat and fuel cells energies) are still suggested to be the alternative
forms of traditional energy that would meet the energy supply in the future [5][6][7].
Amongst the numerous available renewable energy sources, PV solar energy is considered
to be the most promising one, because it has the advantage of not only being clean, abundant,
flexible, emission free, reliable, noiseless, inexhaustible, low maintenance cost, easily converted
into electrical energy, but also an economical source [8][9][10]. As the traditional energy has its
own drawbacks so does the PV energy that cannot be relied upon all the time due to different
variation of weather conditions; not to mention the fabrication expensive cost as well as the low
energy efficiency [11][12].
The different variation of weather conditions (solar irradiation and temperature) is set to be
the key targets of the performance of PV energy supply to the load [10][12]. It is agreed that the
variation of weather conditions cause a variation in the MPP of PV module, so it is highly
recommended to extract the MPP from the PV source as much as possible [9][12].
MPPT algorithm is the most desired, required and needed system, for the fact that it extracts
the MPP to enhance the efficiency of PV modules [13][14], not to mention the several MPPT
developed methods; these last vary in accuracy, complexity, speed and oscillation at the MPP.
Both “Incremental Conductance” and “Perturb and Observe” (P&O) (INC) MPPT algorithms
are the most commonly and widely used due to their simplicity in implementation and control
structures [9][15][16].

Received: January 18th, 2022. Accepted: September 23rd, 2022

DOI: 10.15676/ijeei.2022.14.3.12

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Hichem CHOUIAL, et al.

INC MPPT algorithm based on iteration of fixed step size is simple with good effectiveness.
Moreover, the rapidly changing climate conditions cause a confusion and a failure that come
with drawbacks, which are the oscillation around the MPP, thus it increases the loss of power at
a steady state, simultaneously the time response of MPPT is slower [16][17][18].
In order not only to operate the PV module under a suitable effectiveness and performance,
but also to overcome and acquire the aforementioned drawbacks, an INC_COND MPPT
algorithm is proposed. This work aims to enhance the dynamic response, oscillation at steady
state and efficiency of the conventional MPPT algorithms under various climatic conditions.

2. Overall PV system configuration

The whole PV system shown in Figure 1 consists of the main following elements: the PV
Module, which produces power directly from solar irradiation, the DC/DC converter, which is
used to maximize the power produces from the PV array to an electrical system by controlling
the PV panel output voltage to a reference value at which the PV panel supplies the maximum
energy [5][9][16].

DC/DC
Load
Converter
Control
Signal
PV Module Vpv
MPPT
Ipv Control

Figure 1. Simplified schematic of the overall PV system configuration

A. Solar cell Modelling

PV cells are semiconductor devices which can be fabricated from many different materials
using various methods. The power delivered from a PV cell is achieved by exploiting the PV
effect that converts light energy into electrical energy. A simple equivalent circuit model for a
solar cell consists of a rectifying diode in parallel with an ideal current source. The ideal current
source delivers current in proportion to the solar radiation to which it is exposed. The
corresponding I_V curve is described by the Shockley PV cell equation. The PV module known
as single diode model illustrated in Fig. 2. It consist of Current source Ipv, which depends on
temperature and irradiance, this source connected in parallel to a Diode D and two resistors series
Rs and parallel Rp [18][19][20].
I→pv
Rs
Iph ↓ Id Rp Vpv

Figure 2. The solar cell single diode model

It can extract the current (I) from using current law of Kirchhoff in Fig. (2), by the following
equation (1). Where (I), (Ipv), (Id) and (Ish) are the output current of PV panel, the current of
PV cell depending on temperature and solar irradiation, the diode current and the current pass
through the parallel resistance respectively[21][22].

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High Performance MPPT Controller for Solar Photovoltaic System under Variable

V+Rs I V+Rs I
I = Np �Ipv − I0 �exp � NskT � − 1�� − (1)
γ Rp
q
The IPV current from Practical model given by the equation (2)
G
Ipv = � � �Ipv,STD + K(T − TSTD )� (2)
GSTD
Where G, GSTD, ISTD, TSTD, K, ISTD, T is solar irradiation in (W/m2), solar irradiation
at standard condition in (W/m2), current of PV at GSTD at the standard temperature of p-n
junction, Boltzmann constant (1.38 × 10−23 ) and p-n junction temperature in Kelvin. It can
give the diode current I0 by the following equation (3).
Ipv,STD +Ki (T− TSTD)
I0 = qVoc+ Ki �T− TSTD �
(3)
exp� −1�
γVt
Where V, Voc and Vt is the output, the open circuit and the thermal voltage of PV module.
q, γ, Ki and KV is constant of the electron charge (1.60217646 × 10−19 C),the diode
ideality constant, the short circuit current and the open circuit voltage coefficients. Rs and Rp is
the series resistance due to metal contact joining the PV cells and the parasitic resistance due to
the p-n junction leakage current, Ns and Np is the number of connected cells in series and in
parallel.
The specifications of PV cell are given by the producers as indicated in Tab. 1 according to
the STC (T = 25 °C; G = 1000 W/m2). Nevertheless, the PV output power will change with the
variable weather conditions. Figure 3 demonstrates how the PV output power increases with the
variation of solar irradiation level. Therefore, the output power is proportionally related not only
to the irradiation but also to the temperature [23][24][25][26].

Table 1. Parameters of ISOFOTON IS-75/12 PV panel

Variables Value
Pmpp 75 [𝑊𝑊]
Vmpp 17.3 [𝑉𝑉]
Immp 4.34 [𝐴𝐴]
Vop 21.6 [𝑉𝑉]
Ics 4.67 [𝐴𝐴]

B. Boost analysis
Among, the numerous DC-DC converters used in PV systems, a boost converter Fig.3 is the
most widely used due to the simplicity of structure, construction, competence and higher
effectiveness. It can divide the boost converter to two modes, when the MOSFET switched
ON/OFF. With time of switching, it can control the flow power of PV systems. It can write the
mathematical expressions of the boost converter by the equation (4) [27].
VPV
V0 = 1−D (4)
T
D = Ton (5)
D is duty cycle, 𝑉𝑉0, 𝑉𝑉PV is the boost converter voltage and the output voltage, T is the time
of cycle period, T𝑜𝑜𝑜𝑜 is the time of switching ON. The switching ON/OFF depends on Pulse
Width Modulation (PWM) control[16] [28].

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Hichem CHOUIAL, et al.

Ipv Iout

+ +

Switch
Vpv Vout
Load

- -

Control Signal

Figure 3. DC-DC Boost converter

The implementation of DC-DC boost converter can extract the power generated by PV
modules at the MPP, which supply the load, using the MPPT algorithm to change the duty cycle
D [29][30].

3. Maximum power point tracking algorithm

The maximum solar power delivered depends on the both cell temperature and solar
irradiation as presented in Fig. 4, and thus the optimal operating point of PV panel also changes,
which prevents harvesting the maximum output PV power. Therefore, to use the PV panels more
efficiently, it is necessary to control the PV power harvested by tracking the maximum power
point with a mechanism called MPPT. This mechanism changes the duty-cycle of the Boost
Converter so that the energy delivered by the PV module is maximal. Generally, it is based on
the changing of the duty-cycle until achieve the PPM according to the parameter’s evolutions of
the Boost Converter.
5
(b)
4
PV Current (A)

0
0 5 10 15 20 25
PV Voltage (V)

80
(a)
60
PV Power (W)

40

20

0
0 5 10 15 20 25
PV Voltage (V)
Figure 4. Solar radiation effect.

A. Stand IncCond technique

In this method, the voltage of the solar panel is controlled according to the actual and IncCond
value of the PV panel. Since tracking the control variable is done quickly, it allows avoiding the
disadvantage of IncCond technique, which cannot seek the peak power under rapidly changing
conditions [28].

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High Performance MPPT Controller for Solar Photovoltaic System under Variable

𝑑𝑑𝑑𝑑
𝑑𝑑𝑑𝑑
=0 (6)
𝑑𝑑𝑑𝑑 𝑑𝑑(𝐼𝐼.𝑉𝑉) 𝑉𝑉.𝐼𝐼 𝐼𝐼.𝑑𝑑𝑑𝑑
𝑑𝑑𝑑𝑑
=
𝑑𝑑𝑑𝑑
= +
𝑑𝑑𝑑𝑑 𝑑𝑑𝑑𝑑
(7)
𝑑𝑑𝑑𝑑 𝑑𝑑𝑑𝑑
𝑑𝑑𝑑𝑑
= 𝑉𝑉 + 𝐼𝐼
𝑑𝑑𝑑𝑑
(8)
𝑑𝑑𝑑𝑑 𝐼𝐼
𝑑𝑑𝑑𝑑
+ =0
𝑉𝑉
(9)
Due to its simplicity in its application, the IncCond method Fig.5 is largely applied which has
few difficulties in the regulation of the step-size; this later decides the tracking speed of solar PV
system. If the step-size is large, the system converges very fast toward the optimal power point,
but the perturbations around the peak power it will be large [9][22][28].

Figure 5. Flowchart of the IncCond technique.

𝑑𝑑𝑑𝑑 𝑑𝑑𝑑𝑑 𝐼𝐼
𝑑𝑑𝑑𝑑
= 0 if = − (at MPP)
𝑑𝑑𝑑𝑑 𝑉𝑉
(10)
𝑑𝑑𝑑𝑑 𝑑𝑑𝑑𝑑 𝐼𝐼
𝑑𝑑𝑑𝑑
> 0 if > − (left of MPP)
𝑑𝑑𝑑𝑑 𝑉𝑉
(11)
𝑑𝑑𝑑𝑑 𝑑𝑑𝑑𝑑 𝐼𝐼
𝑑𝑑𝑑𝑑
< 0 if < − (rigth of MPP)
𝑑𝑑𝑑𝑑 𝑉𝑉
(12)

The power and voltage derivative ratio dP/dV of the PV module was introduced as an
adjusting variable to control the step size of the traditional IncCond algorithm [21]. The design
of this algorithm is consequently based on the observation of the dP/dV taking into consideration
the P-V characteristic of the PV module [22].

B. Modified IncCond algorithm

The conventional IncCond method depends in step-size perturbation, therefore, when it is not
rightly adjusted it not able seek the maximum power correctly [22]. A large step-size results in
quick convergence but also in large energy losses. A small step-size could reach the MPP in
steady-state operation but could not follow quick radiation variations. To improve the IncCond
technique, the future approach is considered to rise the pursuing precision by removing steady-

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state berturbations and avoiding the loss of way to the MPP. The flowchart of future IncCond
procedure is exposed in Fig.6. Eq (13) is used to generate two working zones (Fig. 7), Z is a
minor rate 0.001 ( in this implementation). the two working zones A and B, the step-size is
different from Large Step (LS) to Small Step (SS), respectively.
𝑑𝑑𝑃𝑃
𝑎𝑎𝑎𝑎𝑎𝑎 � 𝑝𝑝𝑝𝑝 � ≤ 𝑍𝑍
𝑑𝑑𝑉𝑉
(13)
𝑝𝑝𝑝𝑝
𝑑𝑑𝐼𝐼𝑝𝑝𝑝𝑝 𝐼𝐼𝑝𝑝𝑝𝑝
𝑑𝑑𝑉𝑉𝑝𝑝𝑝𝑝
+
𝑉𝑉𝑝𝑝𝑝𝑝
< 𝑒𝑒 = 0.04 (14)
In zone A, the state of (13) not able obtained, this situation the step-size is settled as LS. In
zone B, state (9) can be satisfied. Therefore, this zone, the step-size is settled as SS. In short, the
procedure uses a large step-size (LS) after the structure functions far from the MPP and sets a
small step-size (SS) after the structure functions near the MPP (area B). Additional important
trial supplementary (14) to notice if there are large differences in either irradiation or load. The
system checks incessantly this condition. If this state is not proved that income, large variations
happen either in load or in irradiance. So, the process sets the step-size as LS. If this state is
content, then no variations happen in both load and irradiance, and the structure remains to
pursuit the MPP with step-sizes defined in function of the areas determined by (13). As (14)
rarely achieves zero, a small tolerance is used, 𝑒𝑒 = 0.04.

Figure 6. Flowchart of the future IncCond technique

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High Performance MPPT Controller for Solar Photovoltaic System under Variable

80

70 MPP
60 A A
PV Power (W) 50
PV characteristic B
40

30

20 abs(dP/dV)
10 Z
0
0 5 10 15 20 25
PV Voltage (V)
Figure 7. PV characteristic with the operating intervals

4. System design and simulation results

The whole PV system implemented in ISIS PROTUES (Fig 8) consists of, the PV panel (the
parameters of this module are mentioned in table (1)) and the Boost DC converter component of
𝑪𝑪𝑰𝑰𝑰𝑰 = 𝑪𝑪𝑶𝑶𝑶𝑶𝑶𝑶 = 2200 µF; 𝑳𝑳 = 284 µH; and the switching frequency 𝒇𝒇𝑺𝑺𝑺𝑺 = 10 khz connected to
resistor load 𝑹𝑹𝑳𝑳 = 20 (𝛺𝛺). The PV module supplies the DC-DC converter, the MPPT control
works and finds the MPP of the PV module for each solar irradiation and transfers it to the load.
If the switch is kept as high (on), then the inductor feeds the energy from the input and stores the
energy in the form of magnetic energy. If the switch is kept as low (off), it discharges the energy
into the load (Figure 9).

Figure 8. The whole PV system under ISIS PROTUES

Table 2. The Boost converter components

Variables Value
Cin 2200 µF
𝐿𝐿 284 µ𝐻𝐻
Cout 2200 µF
fSW 10 khz

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Hichem CHOUIAL, et al.

Figure 9. Boost converter under ISIS PROTUES

Figure 10. Voltage, a) IncCond, b) adapted IncCond

Figure 11. Current, a) IncCond, b) adapted IncCond

Figure 12. Power a) conventional IncCond, b) adapted IncCond

The solar PV system is implemented with Both MPPT algorithms the conventional IncCond
as well as the Adaptive Duty Cycle as demonstrated in fig.8. The conventional IncCond results
are illustrated in Figures (10.a to 12.a), while the variable pitch technique is illustrated in Figures
(10.b to 12.b). These are acquired at standard test conditions, which are a set test point of 25°C
and a fixed irradiation of 1000 W/m2. As can be seen in Tab. 1, the maximum output of PV
panel, is 75 W at standard test conditions (STC). The maximum output obtained in the simulation
using the technology proposed is 74.9 Was indicated in Figure 12.b. The accuracy of the

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High Performance MPPT Controller for Solar Photovoltaic System under Variable

proposed methodology is nearly 99.86%. Examining the outcome in Fig. 10, it becomes apparent
that the response times towards the MPP of the variable step controller is quicker and have a
dynamic response in comparison with the conventional IncCond technique. On the contrary, the
suggested technique has a good tracking time than the traditional IncCond method, as it is shown
in Fig 11. Fig 12 can affirm once more the superiority of the proposed method in stability and
fast convergence to the MPP. Following these details, the future MPPT algorithm answers
adequately, instantly and successfully.

Figure 13. Different types of irradiance change

Figure 14. Voltage a) IncCond (b) adapted IncCond.

As shown in Figs. 14 and 15, the standard IncCond approach is slow to reach a stationary
state and becomes stable around MPP with large perturbation amplitude due to its constant step;
these oscillations worsen when solar irradiation changes abruptly. As a result of its instabilities
in the steady state, this approach loses energy, reducing its efficiency and precision in tracking
the MPP. Figure 16 shows the power harvested by the two MPPT controllers under various
irradiation conditions. The results clearly show that the proposed strategy outperforms the
standard method (faster settling time and fewer steady-state oscillations), resulting in an
improvement in PV panel energy production. The suggested MPPT controller responds more
quickly to changes in insolation.

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Figure 15. Current a) IncCond b) adapted IncCond.

Figure 16. Power a) IncCond b) adapted IncCond.

The simulations given below were run using data from a meteorological database at Adrar
(Algeria) Figure 17. The progression of the irradiation data every 15 minutes from 6:00 am to
6:00 pm of the chosen day is shown in Figure 18.

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High Performance MPPT Controller for Solar Photovoltaic System under Variable

Figure 17. The weather forecasting of the Renewable Energy Research Unit in Middle East
Saharan Region

Figure 18. Irradiation data registered and recorded in Adrar region (Algeria)

Figure 19. PV delivered Power and Boost Output Power:(a) conventional IncCond
algorithm (b) modified IncCond algorithm.

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The traditional IncCond technique in case of low solar irradiation level it cannot reach the
optimal function point adequately (Fig 19a). Whereas the suggested adaptive duty cycle MPPT
technique was able to ensure the load requirements even during the hours of the low solar
irradiation levels (Fig 19b). The use of the adaptive MPPT technique shows a higher convergence
of rate to achieve the desired MPP, with fewer errors on the output power delivered from the PV
panel. In addition, the proposed technique requires fewer sensors and less microcontroller
memories.

5. Experimental verification
The whole system consists of the solar PV source, the DC boost shopper, the PIC16F877A
microcontroller, the gate drive and the load. The boost transistor (MOSFET) is controlled by
varying the duty cycle. Thus, the PV module function point proceeds around the MPP. Both the
old Inc_Cond technique and the proposed Inc_Cond technique are implemented in the
PIC16F877A microcontroller; in order to generate the PWM signal to control the boost
MOSFET. The current ACS712 sensor and the voltage divider are used respectively to sense the
boost converter input and output current, and to sense the boost converter input and output
voltages.

Data
Load MOSFET Acquisition
Driver
Displaying

PV Output
Boost
PIC Circuit
converter
control

Figure 20. The whole PV System experimental test.

a Boost b Boost

PV PV

Figure 21. Voltage, a) IncCond, b) adapted IncCond

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High Performance MPPT Controller for Solar Photovoltaic System under Variable

a PV
b PV

Boost Boost

Figure 22. Current, a) conventional IncCond, b) adapted IncCond

From Figure 21 and 22, traditional MPPT technique produces sharp fluctuations at steady-
state due to the size of the perturbation step and irradiation profile, which causes power losses in
the PV production. The proposed variable step-size MPPT technique limits the amplitude
perturbation around the MPP to a very low value. The traditional MPPT technique has the
problem of low MPP tracking speed and poor dynamic response. Proposed MPPT technique is
able to track the MPP with high tracking velocity and has good dynamic response.

6. Conclusion
In this work a MPPT control system using IncCond technique was used. In this technique a
new strategy was suggested which differs greatly from existing methods. The difference between
the traditional algorithm and the proposed algorithm is the calculation of incremental steps. The
tracking time of the suggested procedure to MPP is very fast compared to the classical one, and
also the fluctuations of the proposed algorithm around MPP are strongly reduced. This article is
addressed on the adaptation of incremental steps to get a very fast system and reduce the
fluctuations around MPP.

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Hichem Chouial was born in Guelema Algeria. He received Master Degree in

Electrical Engineering from University of Badji Mokhtar-Annaba, Algeria, in
2015. He is attending his PhD from the department of Electrical Engineering,
University of Badji Mokhtar-Annaba, Algeria Since 2018. His research interests
are in renewable energy system, energy management, micro grid, and power
electronics.

Hocine LABAR was born in El Kala Algeria. He received Dipl.-Ing. Degree

in Electrical Engineering in 1991, and the PhD. degree in electrical engineering
from University of Badji Mokhtar-Annaba, Algeria, in 2004. He is Scientific
Committee Chairman of the Department 2005 up to 2010.Director of
Laboratoire d’Electrotechnique d’Annaba up to now. Currently, he is a full
professor at electrical engineering department of University of Badji Mokhtar-
Annaba, Algeria since 2011. His research interests are in the power quality,
renewable energy, and multilevel inverters

Mounia Samira KELAIAIA was born in Annaba Algeria. She received Dipl.-
Ing. Degree in Electrical Engineering in 1993, and the PhD. degree in electrical
engineering from University of Badji Mokhtar-Annaba, Algeria, in 2007.
Currently, she is an associate professor at electrical engineering department of
University of Badji Mokhtar-Annaba, Algeria since 2014. Her research interests
are in the power quality, renewable energy, and multilevel inverters

Salah NECAIBIA was born in Annaba Algeria. He received Master Degree in

Electrical Engineering from University of Badji Mokhtar-Annaba, Algeria, in
2015, and the PhD degree in electrical engineering from University of Badji
Mokhtar-Annaba, Algeria, in 2018. His research interests are in renewable
energy system, and power electronics.

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Hichem CHOUIAL, et al.

Ammar NECAIBIA was born in Guelma Algeria. He received the State

Engineer degree in Automatics from University of Badji Mokhtar-Annaba,
Algeria in 2007 and the Magister degree in Electrical Engineering from Annaba
University, Algeria in 2009 and the PhD degree in electrical engineering from
university of "20 August 1955" Skikda, Algeria, in 2016. He is Researcher, in
Research Unit on Renewable Energy in Middle-Saharan Adrar, Algeria. His
research interests are in the Fractional order Control, Adaptive Control, Robust
Control, Renewable Energy and Photovoltaic Conversion.

Okba DJELAILIA was born in Tebessa Algeria. He received Master Degree in

Electrical Engineering from University of Badji Mokhtar-Annaba, Algeria, in
2016. He is attending his PhD from the department of Electrical Engineering,
University of Badji Mokhtar-Annaba, Algeria Since 2016. His research interests
are in renewable energy system, energy management, micro grid, and power
electronics.

Faycel MERAD was born in Annaba Algeria. He received Master Degree in

Electrical Engineering from University of Badji Mokhtar-Annaba, Algeria, in
2016. He is attending his PhD from the department of Electrical Engineering,
University of Badji Mokhtar-Annaba, Algeria Since 2016. His research interests
are in concentrator solar power system, power electronics, renewable energy
system, and energy management.

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