Characterization of PV panel and global optimization of its model parameters using genetic algorithm

This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. The accurate modeling of any PV module is incumbent upon the values of these param...

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Main Authors: Ismail M.S., Moghavvemi M., Mahlia T.M.I.
Other Authors: 9633224700
Format: Article
Published: Elsevier Ltd 2023
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spelling my.uniten.dspace-301772023-12-29T15:45:15Z Characterization of PV panel and global optimization of its model parameters using genetic algorithm Ismail M.S. Moghavvemi M. Mahlia T.M.I. 9633224700 7003701545 56997615100 Genetic algorithm Partial shading PV modeling Renewable energy Solar energy Global optimization Hybrid systems Iterative methods Optimization Photovoltaic cells Solar energy Sun Average absolute error Manufacturer's datum Numerical iterative methods Optimization ability Parameter optimization Partial shading Renewable energies Voltage-current relations Genetic algorithms This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. The accurate modeling of any PV module is incumbent upon the values of these parameters, as it is imperative in the context of any further studies concerning different PV applications. Simulation, optimization and the design of the hybrid systems that include PV are examples of these applications. The global optimization of the parameters and the applicability for the entire range of the solar radiation and a wide range of temperatures are achievable via this approach. The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. The results of single-diode and two-diode models are evaluated in order to ascertain which of them are more accurate. Other cases are also analyzed in this paper for the purpose of comparison. The Matlab-Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. The results of the simulation are compared with the Data Sheet information, which is obtained via experimentation in order to validate the reliability of the approach. Three types of PV modules, using different technologies, are tested for the purpose of this validation, and the results confirm the accuracy and reliability of the approach developed in this study. The effectiveness of the model developed by this approach to predict the performance of the PV system under partial shading conditions was also validated. � 2013 Elsevier Ltd. All rights reserved. Final 2023-12-29T07:45:15Z 2023-12-29T07:45:15Z 2013 Article 10.1016/j.enconman.2013.03.033 2-s2.0-84877764031 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84877764031&doi=10.1016%2fj.enconman.2013.03.033&partnerID=40&md5=a7ea385fd75db639cc6b359efd59d1fc https://irepository.uniten.edu.my/handle/123456789/30177 73 10 25 Elsevier Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Genetic algorithm
Partial shading
PV modeling
Renewable energy
Solar energy
Global optimization
Hybrid systems
Iterative methods
Optimization
Photovoltaic cells
Solar energy
Sun
Average absolute error
Manufacturer's datum
Numerical iterative methods
Optimization ability
Parameter optimization
Partial shading
Renewable energies
Voltage-current relations
Genetic algorithms
spellingShingle Genetic algorithm
Partial shading
PV modeling
Renewable energy
Solar energy
Global optimization
Hybrid systems
Iterative methods
Optimization
Photovoltaic cells
Solar energy
Sun
Average absolute error
Manufacturer's datum
Numerical iterative methods
Optimization ability
Parameter optimization
Partial shading
Renewable energies
Voltage-current relations
Genetic algorithms
Ismail M.S.
Moghavvemi M.
Mahlia T.M.I.
Characterization of PV panel and global optimization of its model parameters using genetic algorithm
description This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. The accurate modeling of any PV module is incumbent upon the values of these parameters, as it is imperative in the context of any further studies concerning different PV applications. Simulation, optimization and the design of the hybrid systems that include PV are examples of these applications. The global optimization of the parameters and the applicability for the entire range of the solar radiation and a wide range of temperatures are achievable via this approach. The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. The results of single-diode and two-diode models are evaluated in order to ascertain which of them are more accurate. Other cases are also analyzed in this paper for the purpose of comparison. The Matlab-Simulink environment is used to simulate the operation of the PV module, depending on the extracted parameters. The results of the simulation are compared with the Data Sheet information, which is obtained via experimentation in order to validate the reliability of the approach. Three types of PV modules, using different technologies, are tested for the purpose of this validation, and the results confirm the accuracy and reliability of the approach developed in this study. The effectiveness of the model developed by this approach to predict the performance of the PV system under partial shading conditions was also validated. � 2013 Elsevier Ltd. All rights reserved.
author2 9633224700
author_facet 9633224700
Ismail M.S.
Moghavvemi M.
Mahlia T.M.I.
format Article
author Ismail M.S.
Moghavvemi M.
Mahlia T.M.I.
author_sort Ismail M.S.
title Characterization of PV panel and global optimization of its model parameters using genetic algorithm
title_short Characterization of PV panel and global optimization of its model parameters using genetic algorithm
title_full Characterization of PV panel and global optimization of its model parameters using genetic algorithm
title_fullStr Characterization of PV panel and global optimization of its model parameters using genetic algorithm
title_full_unstemmed Characterization of PV panel and global optimization of its model parameters using genetic algorithm
title_sort characterization of pv panel and global optimization of its model parameters using genetic algorithm
publisher Elsevier Ltd
publishDate 2023
_version_ 1806426307834150912
score 13.188404