Comparison of the MPPT command based on the PSO, P&O, and
IncCond algorithm implemented in Dspace
GHITA BENNIS
LIMAS Laboratory
Faculty of Sciences Dhar El
Mahraz
Sidi Mohammed Ben
Abdellah University
FEZ, MOROCCO
KARIM MOHAMMED
LIMAS Laboratory
Faculty of Sciences Dhar El
Mahraz
Sidi Mohammed Ben
Abdellah University
FEZ, MOROCCO
AHMED LAGRIOUI
Department of Electrical
Engineering and Computer
Engineering
National School of Arts and
Métiers
National School of Arts and
Métiers
Meknes, MOROCCO
Abstract: Several algorithms have been offered to track the maximum power point when we have one maximum
power point. In this paper, we will propose an improved maximum power point tracking method for the photovoltaic
system that utilizes a modified PSO algorithm. The main advantage of the method is the decreasing of the steady-
state oscillation (to practically zero) once the maximum power point is located. moreover, the proposed method has
the ability to track the maximum power point under extreme environmental conditions. To evaluate the effectiveness
of the proposed method, MATLAB simulations are carried out under very challenging circumstances, namely step
changes in irradiance and step changes in load. Finally, its performance is compared with the «perturbation and
observation” and incremental conductance.
The results obtained were validated by a PIL (Processor In the Loop) co-simulation using the DSpace 1104 card.
Keywords: PSO, P&O, MPPT,BOOST, INCREMENTAL CONDUCTANCE, Dspace1104
Received: February 13, 2023. Revised: November 6, 2023. Accepted: December 7, 2023. Published: January 16, 2024.
1. Introduction
In a photovoltaic system, light energy can be directly
converted into electrical energy. [1, 2] And this is
through the use of sensors made of semiconductor
materials sensitive to the wavelengths of the visible,
which are called "photovoltaic" cells "PV". We call a
photovoltaic generator. (GPV) the association of several
PV cells in series and / or parallel, The photovoltaic
generator is essentially distinguished by its static
current-voltage characteristic I (V) which is nonlinear in
nature and which has a maximum power point (PPM) ).
This characteristic has a direct relation with the level of
illumination, the temperature of the cell, and the aging
of the whole. In fact, determining the operating point of
the GPV depends directly on the load to which it is
connected. This operating point is more or less distant
from the PPM which is characterized by the most
optimal current and voltage. For the conversion of
photovoltaic energy in terms of efficiency to be
optimized, a PPM tracking mechanism called
"Maximum Power Point Tracking" (MPPT) is necessary
to ensure the generation of maximum power. In the
literature, there are several methods divided into
conventional methods (perturbation and Observation ...)
and innovative methods (optimization of particle
swarms)[6-8].
2. Principle of Maximum Point
Search (MPPT)
An MPPT (Maximum Power Point Tracker) is a
command which is associated with an adaptation stage
(DC-DC converter) and which allows the photovoltaic
generator to maintain the production, permanently, of
the maximum of its power. The role of the control
technique is to control the static converter that connects
the load, it makes it possible to act on the duty cycle
automatically to bring the generator to its optimal
operating value despite meteorological instabilities or
even sudden fluctuations charges occurring from time to
time[3-5].
2.1 Perturbation & observation (P&O) method
Figure 1 shows the variation of power as a function
of the voltage of a photovoltaic panel. It can be seen that,
if a voltage disturbance occurs, the photovoltaic power
increases and the direction of disturbance is maintained.
Otherwise, it is reversed in order to resume convergence
to a new PPM. The trajectory of the variation of these
points is shown in Figure 1.
International Journal of Electrical Engineering and Computer Science
DOI: 10.37394/232027.2024.6.3
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E-ISSN: 2769-2507
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Fig. 1. Power available depending on the voltage across the PV generator
2.2 MPPT based on the conductance increment
The PPM can be reached by comparing the value of
the conductance (Ipv/Vpv) with that of the increment of
conductance (dIpv/dVpv) at all times. Figure 3 shows
the algorithm of this method, where Vr represents the
reference voltage [9].
Fig. 2. Algorithm of the conductance increment method.
2.3 MPPT based on the PSO
A. one peak
B. Multiple peaks (partial shading)
Fig. 3. PSO particle movements in MPP research
To start the optimization process, the algorithm can
transmit up to three operating cycles di (i = 1,2,3) to the
power converter. In Figure 4, the work cycles d1, d2, and
d3 are mentioned by triangular, circular, and square
points, respectively. These duty cycles play the role of
Pbesti at the level of the first iteration. Of these, d2 is the
Gbest that provides the best fitness value (which is the
power of the array), as shown in Figure 4 (a). At the
second iteration, the resulting speed is only due 'at the
term Gbest. The factor (Pbesti-d (i)) is zero. In addition,
the Gbest speed of the particle (d2) is equal to zero also
since (Gbest-d (2)) is zero. This results in zero speed
and, therefore, the duty cycle remains invariable. Hence,
this particle will not contribute to the exploration
process. To avoid such a problem, a small disturbance of
the duty cycle is introduced, since it is well authorized,
as shown in Figure 4 (b), to ensure the modification of
the value of the physical condition. Fig. 4 (c) mentions
the movement of particles at the level of the third
iteration. As all the work cycles in the previous iteration
lead to a better aptitude value, the direction of the speed
of these particles remains unchanged, and thereafter they
move towards Gbest in the same direction. In the third
iteration, all operating cycles (di, i = 1, 2, 3) reach the
MPP with a low velocity value. In the following
iteration, because of the very low speed, the value of the
duty cycle approaches a constant. Hence, the operating
point will be maintained and the oscillation around the
MPP will be minimized[10-13].
2.4 MPPT based on the PSO multiple pics
When the PV array operates under uniform solar
insolation, the resulting P-V characteristic curve of the
array exhibits a single MPP. However, under partial
shading, the P-V curves are characterized by multiple
peaks, i.e. with several local peaks and one global peak,
as shown in Fig. 3.B. In this example, the i-V curve is
characterized by three peaks, while the p-V curve is
characterized by three peaks. These are labeled P1, P2,
P3. It can be observed that the time derivative of the
power dP/dV is zero for the global peaks and for all local
peaks. In addition, the slope on its right and left sides has
the same signs. Since all conventional MPPT methods
are based on the slope and sign value of dP/dV, the
algorithm could not properly distinguish the local peaks
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Sandipan Pine, Bibhuti Bhusan Choudhury
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(P1, P2, and P 3) and the global peak (P2). It is very
likely that MPPT is forced to trap in the local peak,
leading to a reduction in power output and thus
significantly deteriorating the efficiency of the PV
system [13].
However, since the PSO method works based on the
basis of the research technique, the overall peak can be
tracked without difficulty. Figure 3.B illustrates the
tracking capability of PSO during partial shading.
Similarly to the previous P-V curve, the proposed
method conveys three duty cycles, which serve as Pbest
particles. It can be seen that the voltage and current that
contribute to these initial duty cycles (Pbesti) are far
from the overall peak (P2). But in later stages of
iterations, it has successfully found the global vertex P2.
3. Simulation of Search for the
Maximum Point of Power
Different tracking algorithms have been proven and
used with several types of DC-DC. Among these
algorithms, we studied here the methods "Perturb and
observ" "and" conductance increment "and" PSO ". The
choice of converter is a preliminary step in having a
more efficient MPPT control. The boost-type DC-DC
converter allows the photovoltaic system to follow the
PPM at all times, independently of temperature,
sunshine and load.
The photovoltaic system consists of a photovoltaic
panel, a DC-DC converter of the boost type provided
with its MPPT control, which is based on the P&O
algorithm, and a pulse width modulation generator
(PWM) in order to check the duty cycle of the converter
for a resistive load. The synoptic diagram is mentioned
in figure 5.
Fig. 4. Synoptic diagram of the system studied.
we have made the simulation with Matlab-Simulink
of the curves of input and output voltages as well as
those of input and output currents of the converter for a
constant sunshine of 1000W / m2 and constant
temperature of 25 ° C, and a resistive load. FIG. 5
illustrates the results of the simulation of the input and
output values, and Fig. 6 clearly illustrates the input
(Pin) and output (Po) power,
Fig. 5. Input voltage Vin, input current Iin, output current Io, output
voltage Vo
Fig. 6. Pin input power, Po output power
In figures (6 and 7), and for a constant illumination
of 1000 W / m2 and a temperature of 25 ° C, the typical
results of simulation of the electrical characteristics at
the output of the panel and at the output of a chopper of
controlled elevator type by the MPPT command. It
clearly appears that: The different electrical quantities
(powers, voltages, and currents) are stable and
unchanging. After a transient regime of duration 0.05 s,
the MPPT command oscillates the operating point
around the PPM point.
The power given by the PV generator reaches a stable
value around 1200 W and that supplied to the load
around 1000 W, at the output of the panel, the voltage
and the current stabilize respectively around 100 V and
5 A.
At the level of the load, the voltage and the current
stabilize respectively around 230 V and 4.5 A.
Note that the difference between the power output
from the panel and that supplied to the load does not
exceed 200 watts. These losses are attributed to the
different losses by switching and by conduction in
the Mosfet transistor, in the diode, and in the various
components of the MPPT control.
Influence of lighting and temperature on the
instantaneous evolution of V and P
The results of the simulation that have undergone
variations in the illumination and the temperature are
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mentioned in Figs. (8) to (11), we presented the power
and input voltage of the converter as well as the power
and the voltage of the converter output (across the load).
Temperature Variation Case
Fig. 7. Voltage generated by the PV panel (Vin), voltage across the load
(Vo) for 1000W / m² and variable temperature from 50 ° C to 25 ° C.
Fig. 8. The power generated by the PV panel (Pin) and the output power
consumed by the load (Po) for G = 1000W / m² and variable
temperature from 50 ° C to 25 ° C
Figure (8) shows the evolution of the voltage
produced by the PV panel as well as across the load.
Note that the voltage increases with decrease in
temperature (50 ° C to 25 ° C). Figure (9) shows the
evolution of the power generated by the PV panel and
that consumed by the load.
Case of the variation of the lighting
Fig. 9. Fig. 10. Voltage generated by the PV panel (Vin), voltage across
the load (Vo) for T = 25 ° and variable lighting from G = 1000W / m²
C to 750 W / m²
Fig. 10. The power generated by the PV panel (Pin) and the output power
consumed by the load (Po) for T = 25 ° and variable lineage from G =
1000W / m² C to 750 W / m²
Figure (11) shows the evolution of the power
generated by the PV panel and that consumed by the
load. It is noted that the power increases with increasing
illumination from 750W / m² to 1000W / m². Figure (10)
shows the evolution of the voltage generated by the PV
panel and that across the load. It is noted that the voltage
increases with the increase in the illumination from
750W / m² to 1000W / m².
3.1 MPPT control based on conductance
increment
Figure 12 shows the Matlab / Simulink diagram of
the INC-type MPPT command applied to the PV system.
Fig. 11. Simulation diagram of the MPPT command (INC)
Figures (13) to (14) show the evolution of the voltage
generated by the PV panel and that throughout the load
for an illumination G = 1000W / m² and a temperature T
= 25 ° C.
Figures (15) to (16) show the evolution of the current
generated by the PV panel and that at the terminals of
the load for an illumination G = 1000W / m² and a
temperature T = 25 ° C.
Figures (17) to (18) show the evolution of the power
generated by the PV panel and that consumed by the
load for an illumination G = 1000W / m² and a
temperature T = 25 ° C.
Fig. 12. the voltage generated by the PV panel for G = 1000W / m² and T =
25 ° C.
Fig. 13. the voltage consumed by the load G = 1000W / m² and T = 25 ° C
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Fig. 14. the current generated by the PV panel for G = 1000W / m² and T =
25 ° C
Fig. 15. The current consumed by the load G = 1000W / m² and T = 25 ° C
Fig. 16. the power generated by the PV panel for G = 1000W / m² and T =
25 ° C.
Fig. 17. Puissance consumed by the charge G=1000W/m² et T=25°C
As a general remark concerning the evolution of the
voltage and the power, although we started the
simulation with zero initial conditions, the incremental
MPPT command of conductance allowed us to obtain
the nominal operating point of our load for illumination
and a standard temperature.
The different electrical quantities: powers, voltages, and
currents are stable. After a transient state of 0.05 s, the
MPPT command oscillates the operating point around
the point of the PPM.
The power established by the PV generator reaches a
stable value around 1200 W and that supplied to the load
around 1010 W, at the output of the panel, the voltage
and the current stabilize respectively around 100 V and
4.5A.
At the level of the load, the voltage and the current
stabilize respectively around 230 V and 4.4 A.
It should be noted that the difference between the
power output from the panel and that supplied to the load
does not exceed 190 watts. These losses are attributed to
the switching and conduction losses in the Mosfet
transistor, in the diode, and in the various components of
the MPPT control.
Influence of lighting and temperature on the
instantaneous evolution of V and P
The results of the simulation with variations of the
illumination and the temperature are described by
figures (19) to (26), where we mentioned the power and
the input voltage of the converter as well as the power
and output voltage of the converter (across the load).
Temperature Variation Case
Figures (19) and (27) show the evolution of the
voltage produced by the PV panel and that across the
load. Note that the voltage increases with the decrease in
temperature (50 ° C to 25 ° C). Figures (21) and (22)
show the evolution of the power generated by the
photovoltaic panel and that consumed by the load. We
note that the power increases with decreasing
temperature (50 ° C to 25 ° C).
Fig. 18. Voltage generated by the PV panel with a temperature variation 50
° C to 25 ° C
Fig. 19. Voltage across the load with a temperature variation from 50 ° C to
25 ° C
Fig. 20. Power generated by the PV panel with a temperature variation of
50 ° C to 25 ° C
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Fig. 21. Power at the load terminals with a temperature variation from 50 °
C to 25 ° C
Case of variation of the linghting
Figures (23) and (24) show the evolution of the
power generated by the PV panel and that consumed by
the load. It is noted that the power increases with
increasing illumination from 750W / m² to 1000W / m².
Figures (25) and (26) show the evolution of the voltage
generated by the PV panel and that across the load. It is
noted that the voltage increases with the increase in the
illumination from 750W / m² to 1000W / m².
Fig. 22. Voltage generated by the PV panel for variable lighting 1000 W / m²
to 750w / m²
Fig. 23. Voltage across the load variable lighting 1000 W / m² to 750w / m²
Fig. 24. Power generated by the PV panel for variable lighting from 1000W
/ m² to 750W / m²
Fig. 25. Power across the load variable lighting 1000 W / m² to 750w / m²
3.2 MPPT control based on PSO
In this section we present the techniques for
calculating the parameters of the PSO command, as well
as the results of the MATLAB / Simulink simulation of
the PV system used with the PSO type command.
Fig. 26. Diagram of the complete PSO system
Fig. 27. The current consumed by the load for G = 1000W / m² and T = 25 °
C
Fig. 28. the voltage consumed by the load for G = 1000W / m² and T = 25 °
C.
Fig. 29. the power consumed by the load for G = 1000W / m² and T = 25 °
C.
In the figures (28 to 30), and for a constant
illumination of 1000 W / m2 and a temperature of 25 °
C, the typical results of simulation of the electrical
characteristics at the output of the panel and at the output
of a chopper of controlled elevator type by the MPPT
command clearly appears that: The different electrical
quantities (powers, voltages, and currents) are stable.
After a transient state of 0.03 s, the MPPT command
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oscillates the operating point around the point of the
PPM.
The power supplied by the PV generator reaches a
stable value around 1200 W and that supplied to the load
around 1030 W, at the output of the panel, the voltage
and the current stabilize, respectively, around 100 V and
5 A.
At the level of the load, the voltage and the current
stabilize respectively around 235 V and 4.5 A.
Note that the difference between the power output
from the panel and that supplied to the load does not
exceed 170 Watts. These losses are attributed to the
switching and conduction losses in the Mosfet transistor,
in the diode, and in the various components of the MPPT
control.
3.3 Comparison of MPPT commands
Fig. 30. PSO, P&O and IncCond train MPP monitoring
Figure 31 shows a comparison between the power
extracted from the solar panel of PSO, P & O and
incremental conductances. Based on the results in Figure
31, we can conclude that the PSO MPP gives high
accuracy by comparing it to that of P & O and IncCond.
BOOST converter output
BOOST
converter
input
Algorithm
P&O
Algorithm PSO
One peak multi peaks
Vin= 118W
Iin= 9A
Pin= 1062W
Pout= 1000W
Vout= 230V
Iout= 4,34A
η= 94%
Pout= 1030W Pout= 800W
Vout= 233V Vout= 160V
Iout= 4,4 A Iout= 5A
η= 97%
3.4 PSO Multiple peaks
The role of the PSO block is to direct the system to
MPPG (maximum overall power) with a slight error,
then stabilize the system to the maximum. Figure 3.31
shows the schematic of the complete system.
Fig. 31. Schematic of the complete multipeak PSO system
Fig. 32. shows the characteristic curve of the PV system under the
following insolation: E1=500 W/m², E2=1000 W/m², E3 = 600 W/m².
Fig. 33. BOOST converter output voltage
Fig. 34. BOOST converter output power
Due to non-uniform solar insolation, the resulting P-
V characteristic curve of the SP exhibits multiple peaks,
as shown in Figure 32. Figures 33, 34, respectively,
show the voltage and power of the photovoltaic panel
obtained using the PSO algorithm.
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3.5 PIL simulation DSpace
In previous chapters, we used Simulink to model our system.
With S-function and Stateflow techniques, complicated
systems, and discrete event systems can be modeled and
simulated. We also studied all the numerical simulation
approaches in Simulink. However, interaction with the real
world has not been considered until now. Simulink models
cannot be built due to the complexity of real systems, the
system must be integrated into the simulation loop to obtain
more accurate simulation results; this type of simulation is
usually called processor-in-the-simulation. loop (PIL). The
Workbench provided by MathWorks can translate Simulink
models into C code, and standalone executable files can also
be generated using this tool, so that control can be
performed. Examples of these products are dSPACE, with its
Control Desk and Quanser plus WinCon (which can be used
to implement processor-in-the-loop simulation). MATLAB
and Simulink support many products from well-known
hardware manufacturers such as Motorola, Texas
Instruments, etc., and can directly generate executable code
for them from Simulink models. Network simulators or
programmable DC power supply are expensive instruments
and they are not always affordable. Therefore, PIL testing
can be used as an inexpensive solution to test hardware
implementation of the MPPT algorithm and inverter control
command. As part of this work, we used a DSpace 1104 card
with its control desk to implement the processor-in-the-loop
simulation. In the following, we will present the different
results obtained by the PIL simulation for the MPPT
command.
Fig. 35. PV system using the PIL block.
Figure 35 represents the simulation / cosimulation
diagram of the first part of our system composed of a PV
generator, a boost converter, an MPPT control based on
PSO control and a resistive load, we let's carry out the
co-simulation for E1 = 300, E2=700 and E3=1000
W/m2.
Fig. 36. the power at the output of the boost converter (Pout);
Fig. 37. The current at the output of the boost converter (Iout).
Fig. 38. the voltage at the output of the boost converter (Vout);
We find that there is no difference between the
simulation and co-simulation results.
4. Conclusion
Due to a better transfer of power between the ‘GPV’
photovoltaic generator and the load, we performed a
modeling of the entire conversion chain using Matlab.
We also designed and simulated the Maximum Power
Point Search Algorithm (MPPT). It forces the GPV
generator to operate at its Maximum Power Point
(MPP), thus inducing a total improvement in the
efficiency of the electrical conversion system.
We applied the three MPPT commands chosen on the
PV system by combining the PV panel, chopper, and
charge. We then presented the results of the simulations
for a variation of the temperature and illumination.
These results show very satisfactory operation on the
voltage and on the power produced, as well as on the
load.
We also proposed a method to optimize a
photovoltaic system based on the PSO command. The
results of the simulations carried out prove the
effectiveness of our approach in extracting maximum
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Volume 6, 2024
power from photovoltaic systems compared to other
commands.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed in the present
research, at all stages from the formulation of the
problem to the final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflicts of interest to declare
that are relevant to the content of this article.
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International Journal of Electrical Engineering and Computer Science
DOI: 10.37394/232027.2024.6.3
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