An efficient MPPT based photovoltaic control model considering environmental parameters

International Journal of Power Electronics and Drive Systems (IJPEDS)
Vol. 13, No. 4, December 2022, pp. 2432~2439
ISSN: 2088-8694, DOI: 10.11591/ijpeds.v13.i4.pp2432-2439  2432
Journal homepage: http://ijpeds.iaescore.com
An efficient MPPT based photovoltaic control model
considering environmental parameters
Hossein Zeynal1
, Zuhaina Zakaria2
, Bahareh Pourveis1
1
Department of Electrical and Computer Engineering, Buein Zahra Technical University, Buein Zahra, Iran
2
Power System Planning and Operations Research Group (PoSPO), School of Electrical Engineering, College of Engineering,
Universiti Teknologi MARA, Shah Alam, Malaysia
Article Info ABSTRACT
Article history:
Received Mar 10, 2022
Revised Aug 15, 2022
Accepted Aug 30, 2022
This paper presents an efficient way for maximum power point tracking
(MPPT) in photovoltaic (PV) system. MPPT is one of the crucial issues
when working with PV system as well as the grid. To gain the highest
efficiency for PV system the maximum power has to be generated
continuously. The proposed MPPT method allows PV system to have real-
time maximum power all the time with high accuracy and less fluctuations.
As of the developed PV system control model presented in this work, an
efficient MPP can be realized taking into account changes in irradiation level
and temperature which are the thorny issues for other contender algorithms.
To validate the model, results obtained from the proposed algorithm is
compared with incremental conductance (IC) which is a universally accepted
MPPT method. The simulation results exhibited that the developed model
outperforms IC method in terms of accuracy of MPP and stability of the
output in presence of variable irradiations and temperature. Based on the
simulation results, the proposed algorithm is suitable for practical and real-
time applications with promising results in terms of solution accuracy and
execution. The model is implemented in MATLAB/Simulink.
Keywords:
Incremental conductance
method
MATLAB/Simulink
Maximum power point tracking
Photovoltaic system
Radiation and temperature loop
This is an open access article under the CC BY-SA license.
Corresponding Author:
Zuhaina Zakaria
School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA
40450 Shah Alam, Selangor, Malaysia
Email: zyhainaz@uitm.edu.my
1. INTRODUCTION
One of the ways to utilize the solar energy source is to convert it into a new and usable form. That is
photovoltaic system containing several components such as converters, solar arrays, and batteries [1]. It
mainly works in two modes of grid-connected otherwise off the grid. Designing a photovoltaic system entail
selecting the photovoltaic module, the number of modules required, the way that modules can be arranged to
form the photovoltaic array, sizing the converter capacity, after that addressing the storage system
specifications if required and specifying all other components of the system [2]. Therefore, to begin with the
design of photovoltaic system one has to decide on network-independent and network-connected
photovoltaic systems [3]. Factors such as the practical application of photovoltaic systems, environmental
and climatic conditions, spatial and financial constraints can determine the design criteria.
The characteristics of photovoltaic systems require that in the design stages, the influence of various
factors such as weather conditions, environmental pollution, solar radiation, the characteristics of electrical
energy consumers, the efficiency of photovoltaic system components and their other characteristics.
Therefore, to increase the utilization of these solar energy sources, we must use the maximum power point
tracking under weather conditions [4]. These methods are known as maximum power point tracking or

Int J Pow Elec & Dri Syst ISSN: 2088-8694 
An efficient mppt based photovoltaic control model considering environmental … (Hossein Zeynal)
2433
maximum power point tracking (MPPT). Referring to previous research, we find that the MPPT method has
different functions in two separate categories. In the first category, which is affected by dynamic conditions,
it has an effective performance, and in the other category, it is less compatible under environmental
conditions. Therefore, in this paper, we try to provide valid models of simulation of integrated solar systems
with microgrid, among the best classical method MPPT, which is the method of incremental conductivity
under conditions of significant changes in environmental factors [5].
The MPPT control technique works by calculating power and voltage changes at any given time and
achieving an instantaneous slope value. If the slope is positive, the operating point is found to be on the left-
hand side of the maximum power point [5], [6]. Therefore, increasing the array voltage by changing the pulse
width modulation (PWM) control signal is made to the extent that one can achieve a zero ratio of power and
voltage changes. If the slope is negative, then, the operating point is located on the right-hand side of the
maximum power point and the voltage reduction command must be performed to the point where it reaches
the maximum power point of the MPPT [5]−[7].
Maximum power point tracking (MPPT) of photovoltaic arrays is paramount important issue in
photovoltaic (PV) systems [6], [7]. Different MPPT methods are presented to date where efforts have been
made to address the relevant disadvantages of PV modules and ways to prevail them. The MPPT methods
can be divided into 19 models which are capable of tracking maximum power points in a specific way.
Among them, few methods are more prevailing and found further universal acceptance [8].
The perturbation and observation (P&O) algorithm is one of the favorite method in MPPT by which
increasing or decreasing the voltage or solar array terminal current at regular intervals and then comparison
of current PV output power with pervious sampling output power, the MPPT can be realized [9]−[11]. The
simplicity of this method made it quite suitable for wide application especially in new control systems [5].
However, the large fluctuations around the operating point in the steady state is a challenge when using this
method in practice [12], [13], that is resulting in excessive energy loss [14]. To overcome the limitations of
P&O, a fresh method so-called incremental conductance (IC) emerged. The IC method is performed by
conducting a proportional comparison between the rate of increment between power and voltage (or current)
for each subsequent two samples, so that the MPP can be found. As opposed to P&O method, the IC is more
complex to be implemented. As an advantage, IC offers the ability to specify the proportional “distance” to
reach the maximum power point (MPP). Moreover, this algorithm exhibited a precise MPP tracking
capability in weather conditions with a number of fluctuations [14]. Nevertheless, the IC algorithm suffers
from its instability due to the use of derivation operations in the body of algorithm [15].
The constant voltage (CV) algorithm as a simple alternative introduced to find MPP by considering
a constant reference voltage and disregarding irradiation and temperature as insignificant parameters [5].
However, the proper application of this algorithm requires data gathering of the place the photovoltaic system
is installed as well as voltage referencing which is a hinder. The CV can outperform the P&O and IC as long
as the radiation is small [9], [16], that is not very real-world case.
Other techniques reported in this context including a MPPT approach based on temperature
measurements which later discovered that this algorithm is not as efficient as the P&O and IC methods [9],
[17], besides this method is data-dependent of the underworking PV system. Similarly, for open voltage
method [9], because of interruption during the open voltage measurement, the energy loss becomes
significant and therefore impractical for large cases. The feedback voltage (current) method [18], [19] which
is based on comparison between PV voltage with constant voltage and duty cycle adjustment (D) of converter
allowed the performance of the PV array resting nearby the MPP. This method is less complicated and make
use of a single feedback loop which ends up an economical technique. However, it neglects the radiation
level and temperature changes which is a defect for this method [15].
The fuzzy logic control-based methods is one of the technique used in MPP applications and
recently it found great deal of attention due to the advances in microcontrollers and substantial reduction in
implementation costs [20]. One of the major advantages of this method is on the controller model requiring
no exact mathematical representations, which on the other hand results in minimum fluctuation in vicinity of
MPP point. But there is no warranty on reliable operation when radiation level changes. Nonetheless, the
efficiency of the fuzzy logic control method is related to the designer’s experience and knowledge which
limits a broad application of this method [21].
Furthermore, the neural network (NN) method is among those evolving techniques that smartly
search for MPP in PV arrays [22], [23]. The NN method requires comprehensive training process and all data
relevant to each individual PV array which varies by weather conditions and geographical location [24]. Thus
the training process has to be repeated every time which is unfavorable.

 ISSN: 2088-8694
Int J Pow Elec & Dri Syst, Vol. 13, No. 4, December 2022: 2432-2439
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2. MAXIMUM POWER POINT TRACKING
There are several models for solar cells, the most common of which is the two-diode model. The
output power of PV array is always affected by environmental factors and represents discontinuous values.
By installing MPPT in the PV system, one can always achieve the maximum output power of the system
continuously. Incremental conductance method is used because of its easy and practical simulation and is also
more compatible with environmental factors than other existing methods. The main technique of this method is
based on the inclination of the array diagram in terms of voltage at the maximum power point [25], [26].
3. PROPOSED ALGORITHM
In most researchers reported to date, solar systems both in static and dynamic conditions, take up
solar arrays with constant input of radiation level and the temperature. Since in practice the radiation levels
are fluctuating throughout a day, as a result the input of the solar array is always under different temperature
and radiation conditions. In another words, there is no fixed temperature and radiation for solar system. As a
part of contribution, it is paramount important to study the solar system with dynamic changes in radiation
levels.
It is pertinent to mention that as the radiation increases, the short-circuit current also spikes and the
maximum power point shifts to high voltages. The maximum power amount is also updated. In the radiation
loop, in addition to controlling the maximum power point, damage to the system against the negative
impedance characteristic is somehow prevented.
Many maximum power tracking methods are not capable of adapting their controller following
changes in the input parameters of solar system. Therefore, it is necessary to refine the controller parameters
for the new inlet temperature. Such methods are dependent on the solar array, and methods that can track the
very changes of the solar array input are independent of the solar array.
The temperature loop initiates when the radiation changes are small. Due to the fact that the
characteristic of the solar array performance is a function of temperature variations, the maximum power
point will be also renewed. As the temperature increases, the maximum power point shifts to the voltages
with lower values. As a result, the maximum power value decreases slightly. Therefore, using this
temperature loop allows following this point.
In short, the incremental conductance MPPT method is further rebuilt in this work so as to its
accuracy is improved by adding few items. The two-part incremental conductance algorithm, the radiation
and the temperature loops are incorporated in the solution. The proposed algorithm can then cater the
maximum power point in more realistic fashion via the simulation.
4. SIMULATION RESULTS
To demonstrate a real-world solar cell modeling, and according to the datasheet values, the MSX-60
solar panel model is simulated at this work as shown in Table 1 and Figure 1. To model a solar array and all
the practical associated parameters, as in Table 1, showed thee values of the simulation parameters based on
the available datasheet.
Table 1. MSX-60 array parameters for standard test conditions
Amount
Item
200 W
Maximum Power
21 V
Open circuit Voltage
3.75 A
Short Circuit Current
17.1 V
Voltage in Maximum Power
3.5 A
Current in Maximum Power
0.0032 A/K
Short circuit current temperature coefficient
0.00123
- V/K
Open circuit voltage coefficient
54
The number of cells in each array
125
Number of Parallel Modules (NPPs)
4
Number of series modules (NSS)
0.221 Ω
Series Resistor
414.405 Ω
Parallel Resistor
In Figure 2, simulation model represents solar arrays, converters, controllers and monitoring devices
are displayed. As a part of simulation, the solar array model that encompasses input parameters of radiation
level and temperature value. The boost converter connected to the solar array is used to raise the voltage level

2435
and stabilize it at a reference voltage. This converter boosts the 300 Vdc of a photovoltaic array at a
switching frequency of 5 kHz to a voltage level of 500 Vdc. The MPPT block is located at the bottom right.
After the converter, a buffer capacitor is added which allows increasing the output power to the required
level. Further, one can witness that the inductor similarly entered into the model to represent the effects of
output filters, transformers and source impedance, which, on the other hand, is used to remove the harmonics
produced by the inverter. Finally, as the model shows, the PV system with MPPT control is connected to the
power grid. In Figure 2, simulations model which represents solar arrays, converters, controllers and
monitoring.
Figure 1. Solar cell simulation
Figure 2. Developed model
When the proposed system circuit, as in Figure 3, is made available, the input radiation level can be
set for 21000 W/m whereas the temperature maintained at 25 °C. After that, both the incremental
conductance method of MPPT and the proposed method are simulated and outcomes will be studied in detail.
Following the build-up process of voltage at the array, which takes 0.5 second, Figure 4 shows the output
power of array in two methods of incremental conductance and the proposed method. As can be seen in
Figure 4, the performance of the two model is almost the same, but the proposed method has reached the
maximum power in a shorter time and has reached the value of about 10 kW sooner. The blue color indicates
the incremental conductance and the purple color addresses the proposed MPPT method).
In order to accurately evaluate the performance of the MPPT based proposed method, following
studies can be cast. For rapid changes in environmental conditions, the variable input radiation level of the
array is considered as presented in Figure 5 exhibiting a number of fluctuations while the temperature is
being kept constant. By incorporating radiation pattern shown in Figure 5, one can see the resultant PV
output power of the incremental conductance method as well as the proposed MPPT method for variable
radiation at fixed temperature.

 ISSN: 2088-8694
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Figure 3. Proposed control system
Figure 4. Output power representation of PV system
Figure 5. Radiation level changes over time

2437
The simulation results in Figure 6, can reveal that the proposed method outperforms the incremental
conductance method in presence of a changeable radiation input which ought to challenge the maximum
power output tracking. As Figure 6 shows at the constant temperature and variable radiation level, the
proposed method reaches the first MPP point earlier than the incremental conductance method. Further, to
examine the performance of the proposed method, the radiation level shall be kept fixed at 1000 W/m2 whereas
the temperature of the solar array is no longer constant and it shows changes as displayed in Figure 7.
Figure 6. Output power in constant radiation and variable temperature
Figure 7. Temperature profile
As a result, Figure 8 presents the performance of tracking maximum power point for both methods.
According to Figure 8, the proposed modified MPPT-based method outpaced the contender of incremental
conductance method in terms of less computational time to reach the maximum power outputs of the PV
array. Using numerical results shown in Table 2, under constant temperature and radiation conditions, the
incremental conductance method and the proposed model can be compared. Under these conditions, the
tracking performance by the proposed algorithm presents better than the other contender and it tracks the
maximum power point faster and in an accurate way especially in the moments when there is a temperature
change. Moreover, the incremental conductance method during the weather changes deviates from the
maximum power point tracking and therefore, it is not suitable under this circumstance.
Table 2. Comparison of MPPT algorithms
MPPT Output current Output voltage Output power Accuracy
Incremental conductance 36.09A 250.34V 9.034 kW low
Proposed Model 39.46A 250.37V 9.879 kW high

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Figure 8. Array output power at constant temperature and variable radiation
5. CONCLUSION
At this work a grid-connected solar system using boost converter with MPPT was developed. The
exact performance of the system components is studied and the effect of variable inputs of temperature and
radiation level on the voltage and current of the solar array and their corresponding maximum power point
were analyzed. Further, the array’s voltage and current of the point of common coupling for the PV system to
the grid can be realized. At this work, the focus was on MPPT methods such as incremental conductance and
improve it through the proposed model. Thus, the proposed method caters better performance in tracking the
maximum power point. When using the incremental conductance model, the output power contains losses
and its value is less than the actual value of the system power. In this sense, the incremental conductance
presents devastations in the amount of output power obtained from tracking as compared with the proposed
method. Using the proposed method, the array output power is closer to the actual power value. This
indicates that the algorithm is more accurate in tracking the maximum power point. More, after each
sampling of the open circuit voltage and calculation of the relationship, the output voltage meets the
maximum power point very quickly. The significant advantage of this method, in addition to high speed, is
the absence of oscillation around the point of maximum power, which will prevent energy loss. It is simple to
implement and is stable to changes in environmental conditions due to the nonlinear voltage-current
characteristic. Due to the ease of measuring open circuit voltage in solar systems based on step-down
converter, the developed method can be served properly for them.
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BIOGRAPHIES OF AUTHORS
Hossein Zeynal received his MEng (2007) and Ph.D. (2013) degree from University
Technology of Malaysia (UTM), Skudai, Malaysia in electrical power engineering. Presently He is
an Assistant Professor at Department of Electrical and Computer Engineering, Buein Zahra
Technical University, Qazvin, Iran. He can be contacted at email: hzeynal@gmail.com.
Zuhaina Zakaria received her Ph.D. degree in Power System from University of
Strathclyde in Glasgow, UK in 2005. She is currently a Full Professor in the Faculty of Electrical
Engineering, Universiti Teknologi MARA, Shah Alam, Malaysia. She can be contacted at email:
zuhainaz@uitm.edu.my.
Bahareh Pourveis received her BEng. degree in Electrical Engineering from Buein
Zahra Technical University, Buein Zahra, Qazvin, Iran in 2019. She is currently pursuing her
MEng degree in Electrical Engineering at University of Isfahan, Iran. She can be contacted at
email: b.porvies@gmail.com.

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