Modeling and simulation of solar PV module for comparison of two MPPT algorithms (P&amp;O &amp; INC) in MATLAB/Simulink

Alhussain, Hayder Moayad Abd; Yasin, Naseer M.

doi:10.11591/ijeecs.v18.i2.pp666-677

Cited by 20 publications

(21 citation statements)

References 22 publications

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“…The P&O method of the MPPT algorithm is used [19], [20] since there is no complex computation, and its hardware implementation is also simple. Some papers research the evaluation of the P&O method [21], [22].…”

Section: Mppt Algorithmmentioning

confidence: 99%

Comparison of DC-DC converters for solar power conversion system

Mishra

Senapati

Salkuti

2022

IJEECS

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This paper covers the comparison between four different DC-DC converters for solar power conversion. The four converters are buck converter, buck-boost converter, boost converter, and noninverting buck-boost converter. An MPPT algorithm is designed to calculate battery voltage, current of PV array, the voltage of PV array, power of PV array, output power. It is observed that the non-inverting buck-boost converter is the finest converter for solar power conversion. The final circuit design has the results of 12.2V battery voltage, 0.31A current of PV array, 34V voltage of PV array, 23mW power of PV panel, and 21.8mW of output power. The efficiency of this system is nearly 95%. All four circuits are simulated in MATLAB/Simulink R2020b.

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Section: Mppt Algorithmmentioning

confidence: 99%

Comparison of DC-DC converters for solar power conversion system

Mishra

Senapati

Salkuti

2022

IJEECS

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“…There are two types of operation points (OP) in this graph. For any OP like point 1 on the left side of the MPP, the voltage should be increased, and for any OP like point 2, the voltage should be decreased [28].…”

Section: Mppt Controllermentioning

confidence: 99%

Design and Dynamic Modelling of a Hybrid PV-battery System for a House with an RO Water Desalination Unit in Iran

Mousavi

Iqbal

2021

EJECE

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Energy crisis and power shortage are major concerns in Iran nowadays, where people experience several blackouts during the day. On the other hand, potable water scarcity is another trend in Iran. In this study, the design and dynamic modelling of a stand-alone hybrid PV-Battery-RO system are discussed for a house in Sinak village, Tehran, Iran. Site characteristics are analyzed in the first part to estimate the house load and deferrable RO load. In the second part, the system has been modelled in HOMER pro software to determine the size of the photovoltaic panels and battery. Moreover, complete electrical details of the system such as system autonomy, unmet load and excess energy have been described. In the third part, dynamic modelling of the small-scale RO unit based on a transfer function is described. The introduced transfer function correctly simulates the system's output flow rate in response to input water pressure variations. Electrical dynamic modelling of the PV- battery system has been designed in MATLAB/Simulink. The results prove that introduced model can simulate the system's behavior in four conditions: normal operating conditions, zero irradiance conditions, maximum irradiance conditions, and net-zero energy conditions. The battery supports the system, and PV arrays power the loads with a fixed and stable voltage and frequency in all the conditions.

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“…The advanced SCC device has a feature to optimize electric power harvest, namely the maximum power point tracking (MPPT) technique. This MPPT feature is used to track the maximum power point (MPP), where at this point, the maximum power harvesting process occurs [1]- [3]. The MPP point can be reached if the system operating voltage is set to the MPP voltage [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of evolutionary-based maximum power point tracking for partial shaded photovoltaic

Megantoro

Kusuma

Awalin

et al. 2022

IJECE

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<span lang="EN-US">The characteristics of the photovoltaic module are affected by the level of solar irradiation and the ambient temperature. These characteristics are depicted in a V-P curve. In the V-P curve, a line is drawn that shows the response of changes in output power to the level of solar irradiation and the response to changes in voltage to ambient temperature. Under partial shading conditions, photovoltaic (PV) modules experience non-uniform irradiation. This causes the V-P curve to have more than one maximum power point (MPP). The MPP with the highest value is called the global MPP, while the other MPP is the local MPP. The conventional MPP tracking technique cannot overcome this partial shading condition because it will be trapped in the local MPP. This article discusses the MPP tracking technique using an evolutionary algorithm (EA). The EAs analyzed in this article are genetic algorithm (GA), firefly algorithm (FA), and fruit fly optimization (FFO). The performance of MPP tracking is shown by comparing the value of the output power, accuracy, time, and tracking effectiveness. The performance analysis for the partial shading case was carried out on various populations and generations.</span>

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Modeling and simulation of solar PV module for comparison of two MPPT algorithms (P&O & INC) in MATLAB/Simulink

Cited by 20 publications

References 22 publications

Comparison of DC-DC converters for solar power conversion system

Comparison of DC-DC converters for solar power conversion system

Design and Dynamic Modelling of a Hybrid PV-battery System for a House with an RO Water Desalination Unit in Iran

Comparative analysis of evolutionary-based maximum power point tracking for partial shaded photovoltaic

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