Comparison of PV panels MPPT techniques applied to solar water pumping system

International Journal of Power Electronics and Drive Systems (IJPEDS)
Vol. 12, No. 3, September 2021, pp. 1813~1822
ISSN: 2088-8694, DOI: 10.11591/ijpeds.v12.i3.pp1813-1822  1813
Journal homepage: http://ijpeds.iaescore.com
Comparison of PV panels MPPT techniques applied to solar
water pumping system
Islam K. Abdul-Razzaq1
, Mohamed M. Fahim Sakr2
, Yasir G. Rashid3
1,2
Department of Electrical Power Engineering, College of Engineering, Cairo University, Giza, Egypt
3
Department of Electronic Engineering, College of Engineering, Diyala University, Diyala, Iraq
Article Info ABSTRACT
Article history:
Received Apr 13, 2021
Revised Jul 1, 2021
Accepted Jul 12, 2021
This paper deals with an advanced design for a pump powered by solar
energyto supply agricultural lands with water and also the maximum power
point is used to extract the maximum value of the energy available inside the
solar panels and comparing between techniques MPPT such as Incremental
conductance, perturb & observe, fractional short current circuit, and
fractional open voltage circuit to find the best technique among these. The
solar system is designed with main parts: photovoltaic (PV) panel, direct
current/direct current (DC/DC) converter, inverter, filter, and in addition, the
battery is used to save energy in the event that there is an increased demand
for energy and not to provide solar radiation, as well as saving energy in the
case of generation more than demand. This work was done using the matrix
laboratory (MATLAB) simulink program.
Keywords:
Fractional open voltage circuit
Fractional short current circuit
Incremental conductance
Perturb and observe
Solar water pumping system
Maximum power point trackers
This is an open access article under the CC BY-SA license.
Corresponding Author:
Yasir G. Rashid
Department of Electronic Engineering
College of Engineering, University of Diyala
Baqubah, 32001 Diyala, Iraq
Email: yasserghazee_enge@uodiyala.edu.iq
1. INTRODUCTION
Solar energy is one of the available renewable energy resources that can provide us with steady,
reliable power [1]. However, because sunlight does not need any kind of fuel, solar energy can be used
directly to create electricity. No gases or poisons are emitted into the air. Solar power systems need minimal
maintenance. Solar modules have a service life of 25 years without lubrication or maintenance. Using solar
energy does have one drawback, however: It is expensive. As long as the sun doesn't shine for 24 hours a
day, the solution involves the combination of a photovoltaic system and a battery. It is useful in nearly any
place, particularly if there is sunlight and access to clean water. When a user of a solar water application
opens a faucet, water is applied to the tank from above [2]-[4]. Figure 1 depicts the daily supply of solar
water.
PV systems frameworks are being used more to increase their energy-efficiency by using PV
systems. But due to the low module efficiency, there is still a device capacity problem in photovoltaic
systems [4]. As a result, matching the maximum electrical output to a photovoltaic device requires careful
evaluation of its constituents. Placing only requires choosing the best PV modules and implementing an
efficien maximum power point tracking (MPPT) algorithm.
In literature, a multitude of MPPT schemes for solar PV systems have been presented in books and
journal articles. Many techniques vary in difficulty, hardware, popularity, and availability, among other
variables. An approach which has found broad acceptance in PV tracking is based on this technique, but not
limited to, perturbation & observation (P&O) (which is the most known), the incremental conductance (INC),

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Int J Pow Elec & Dri Syst, Vol. 12, No. 3, September 2021 : 1813 – 1822
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fractional short current circuit and fractional open voltage circuit [5]-[7]. In this work, the emphasis will be
on design and simulation of solar water pumping systems and comparison study between widely applied
MPPT techniques, while considering weather conditions will be on assessing which method is the most
capable of shifting resource patterns in short order.
Figure 1. Solar water daily supply
2. PHOTOVOLTAIC SYSTEM MODELLING
Figure 2 shows the main block diagram of the proposed stand-alone system. The first block is
represented by photovoltaic solar panels. The voltage and current that gets sent to the output of the MPPT
controller will be measured by a sensing circuit. A boost converter DC/DC power electronic switch uses
pulse width modulation (PWM) to vary its duty cycle. The battery is still charged, which means the rest of
the blocks are represented by PWM. The inverter output voltage will be sensed by sensing circuit that to be
used for modulation index control to stabilize the inverter alternating current (AC) voltage level [8], [9].
Figures 2. The stand-alone PV system block diagram
2.1. Photovoltaic generator model
When there is low electricity production from PV cells. As a result, the cells should be laid out in a
parallel-serial fashion, where the energy is created in several modules. A photovoltaic panel is composed of
series and parallel modules. The PV panel design begins with selecting CS6P-250P solar cell type
Monocrystalline Maxeon Gen II PV modules. Table 1 also includes a summary of the spectifications of the
PV panel parameters. PV panels will be used in this project, which will include 80 panels (total capacity is
20 Kw). These panels are organized into eight parallel lines, each of which contains ten serially linked panels

Int J Pow Elec & Dri Syst ISSN: 2088-8694 
Comparison of PV panels MPPT techniques applied to solar water pumping system (Islam K. Abdul-Razzaq)
1815
[10]. Figure 3 shows solar cellsequivalent circuit in -series and -parallel is shown in and the formula
for their and [11], [12]:
[ ( ) ] ( ) (1)
where , is light-generated current; cell reverse saturation current; A is ideality factor
(=1); T is cell temperature (in Celsius); K is Boltzmann’s constant (= 1.3805 × 10−23
N m/K); q is electronic
charge (=1.6×10−19
C); and is the series and parallel resistance respectively, is the solar short-
circuit current. To learn more about the differences in the impact of different irradiation levels on the P-V
and I-V characteristics, see Figure 4 and Figure 5.
Table 1. Spicefications of CS6P-250 MPV model [13]
Property Value
Maximum Power (Pmax) (W) 250 W
Voltage at Pmax (V) 30.4 V
Current at Pmax (A) 8.22 A
Open-circuit voltage (Voc) (V) 37.5 V
Short-circuit current (Isc) (A) 8.74 A
Temperature coefficient of Power
(%/K)
-0.45
Temperature coefficient of Voc
(%/K)
-0.35
Temperature coefficient of iSC
(%/K)
-0.06
Cell type (e) Monocrystalline
Module efficiency 15.54%
Dimensions (mm) 1638 (h) x 982 (w) 40 (d)
Weight 20 kg
Figure 3. Solar panel electrically equivalent
circuit [12]
Figure 4. At T=25 °C, the P-V characteristics for
various solar irradiance (G) values are shown
Figure 5. At T=25 °C, the I-V characteristics for
various solar irradiance (G) values are shown
2.2. Boost converter model
By interposing a power converter (DC-DC converter) between the photovoltaic generator and the load
(battery), the MPPT can be achieved. By acting on the converter duty cycle (D), the operation point can be guaranteed
to be the MPPT. It uses step-up methodology. The voltage the sensor produces is larger than the voltage that is fed
into it. The circuit shown in Figure 6 has an inductor, a capacitor, a switch, and a diode [14]. When the switch is
closed, the diode tends to be reverse biased and the current increases through the inductor. When the switch is
switched off, the diode tends to be forward biased, the inductive voltage stored in the capacitor is discharged, and the
current is allowed to flow through the inductance. Once the voltage has been increased, it is routed to the load. The
duty cycle is calculated using the values of the input and output voltages specified in the (2).

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(2)
Figure 6. The boost converter circuit
2.3. MPPT techniques
The MPPT control is a key component of the PV system. It is critical to optimal system operation.
This control approach is derived from the principle of optimal variation of the cyclic ratio D, and we will
present and explain later the most popular control techniques. There are a number of common and practical
models for estimating how much a PV power will increase with altitude, including perturb & observe,
incremental conductance, and fractional short current circuit and fractional open voltage circuit [15], [16].
2.3.1. Perturb and observe (P&O) technique
This technique is widely used for tracking the maximum power due to its simple design. This method
adjusts the PV module voltage and compares the new power output with that of the previous perturbation cycle in
order to see if it has returned to normal. On the same principle as shown in Figure 7, the PV module voltage shifts
the control system in this direction if the PV output voltage rises, and the power is limited if it doesn't [17], [18].
Figure 7. The flowchart of the P&O technique
2.3.2. Incremental conductance (IC) MPPT technique
Incremental conductance technique employs an array terminal voltage that is based on the MPPT
voltage. Here is the diagram for this technique in Figure 8. The general form of this technique is this [19], [20].
at MPPT (3)

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at the left of MPPT (4)
at the right of MPPT (5)
= (6)
Figure 8. The flowchart of the INC technique
The dP/dV is defined as the identifier factor for the MPPT. The INC technique is proposed to effectively
track the MPPT of a photovoltaic panel by utilizing this factor. The definitions are taken into account when
tracking the MPPT.
at MPPT (8)
at the left of MPPT (9)
at the right of MPPT (10)
2.3.3. Technique fractional open circuit voltage (FVOC) technique
This technique is based on the nearly linear relationship between the open circuit voltage VOC and
the photovoltaic panel's optimal voltage VMPP [21]-[23]. The relationship between VOC and VMPP is given by
the (11).
(11)
where Kv the coefficient of between between 0.71 and 0.8 varies. The flowchart in Figure 9 illustrates the
FVOC technique.

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Figure 9. Flowchart of FVOC technique
2.3.4. Fractional short circuit current (FSCC) technique
This technique is linear in response and there is almost a direct correlation between the optimum
IMPP and the short circuit current ISC change of the PV in different atmospheric conditions [24], [25]. The
relation between IMPP and Isc is given by the (12):
(12)
where is the coefficient of between 0.78 and 0.92 varies. The flowchart in Figure 10 illustrates the FSCC
technique.
Figure 10. Flowchart of FSCC technique
3. RESULTS AND DISCUSSION
As illustrated in Figure 11, the considered photovoltaic system generates 20 kW and is designed,
simulated, and implemented. This system is divided into six stages. The first stage is a photovoltaic array
with 80 panels, the second stage is a boost converter DC/DC, and the inverter (3-level single-phase bridge, H

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voltage source). The fourth stage includes a passive LCL (LPF) filter connected to the main off-grid fifth
dynamic load circuit, and the final stage is a battery.
Figure 11. The simulation of PV system
Table 2 show MPPT controller at fixed temperatures (T) with range of irradiance (G), while Table 3
show MPPT controller at different temperatures (T) with fixed irradiance (G). Figures 12 (a)-(d) and Figure
13 (a)-(d)illustrate the step response of power for various MPPT techniques at different temperatures (T)
25°𝐶, irradiance (G) 1000 W/𝑚2
and temperature (T) 15°𝐶, irradiance (G) 600 W/𝑚2
, respectively. Table 4
and Table 5 show comparison between the four MPPT techniques after take 10 (sec) of time operation
temperature (T) 25°𝐶, irradiance (G) 1000 W/𝑚2
and temperature (T) 15°𝐶, Irradiance (G) 600 W/𝑚2
,
respectively, mention overshoot, undershoot, rise time and setting time.
Table 2. MPPT controller fixed (T=25), range of (G=200, 600, 1000)
G V-PV P&O INC FVOC FSCC
V Error V Error V Error V Error
200 360.798 360.6 0.198 359.8 0.998 352.5 8.298 351.082 9.716
600 360.806 360.6 0.209 359.8 1.009 352.6 8.209 351.2 9.609
1000 360.826 360.6 0.226 359.8 1.026 352.6 8.226 351.21 9.616
Table 3. MPPT controller range of (T=10, 30, 50), fixed (G=1000)
G V-PV P&O INC FVOC FSCC
V Error V Error V Error V Error
10 360.826 360.6 0.226 360.17 0.656 353.16 7.666 351.93 8.896
30 360.826 360.6 0.226 359.8 1.026 352.6 8.226 351.21 9.616
50 360.267 351.02 0.247 349.68 1.587 347.87 3.397 349.67 5.597

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(a) (b)
(d) (d)
Figure 12. The result of power from different techniques in temperature (T) 25°𝐶, (a) irradiance (G) 1000 W/𝑚2
;
(b) INC curve; (c) FOVC curve; (d) FSCC curve
(a) (b)
(c) (d)
Figure 13. The result of power from different techniques in temperature (T) 15°𝐶, (a) irradiance (G) 600 W/𝑚2
;
(b) INC curve; (c) FOVC curve; and (d) FSCC curve

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Table 4. Performance comparison of MPPT techniques for PV at T= 25°𝐶, G = 1000 W/𝑚2
MPPT Techiques Undershoot (%) Overshoot (%) Settling time (sec) Rise time (sec)
P&O 5.83 0.89 20.437 6.843
INC 1.89 10.75 18.425 6.954
FVOC 6.92 5.87 9.835 5.217
FSSC 7.38 5.42 9.672 5.372
Table 5. Performance comparison of MPPT techniques for PV at T= 15°𝐶, G = 600 W/𝑚2
MPPT Techiques Undershoot (%) Overshoot (%) Settling time (sec) Rise time (sec)
P&O 4.21 2.57 21.846 8.492
INC 19.57 4.28 11.487 8.921
FVOC 14.83 3.37 16.475 7.647
FSSC 16.48 3.82 22.749 7.384
4. CONCLUSION
This study also includes the design and simulation of a 20-kW photovoltaic-powered pump that uses
simple methods, such as PVP. In summary, the results can be stated is being as: The best oscillation in P&O
MPPT technique; the best rise time, settling time in Fractional voltage current circuit (open, short) MPPT; At
T=15°𝐶, G=600 W/𝑚2
the Incremental conductance MPPT best performance in settling time.
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