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

• Published in: Energy conversion and management Vol. 73; pp. 10 - 25
• Main Authors: Ismail, M.S., Moghavvemi, M., Mahlia, T.M.I.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-09-2013; Elsevier
• Subjects: Applied sciences; Computer simulation; Data sheets; Energy; Engineering Sciences; Equipments, installations and applications; Exact sciences and technology; Genetic algorithm; Genetic algorithms; Mathematical models; Modules; Natural energy; Optimization; Partial shading; Photovoltaic cells; Photovoltaic conversion; PV modeling; Renewable energy; Solar cells; Solar energy; Partial shading; Renewable energy; Genetic algorithm; Solar energy; PV modeling; Photovoltaic system; Models; Modeling; Optimization; Photovoltaic cell; coût de l'énergie; Modélisation mathématique; PV-Modul; Énergie solaire; Optimización global; Panneau PV; الوحدة الكهروضوئية; Energiekosten; تكلفة الطاقة; الگوریتم ژنتیک; مدل سازی ریاضی; globale Erwärmung; genetic algorithm; ماژول PV; انرژی های تجدیدپذیر; Énergie renouvelable; النمذجة الرياضية; الطاقة الشمسية; Energía renovable; cost of Energy; بهینه سازی جهانی; globale Optimierung; Solar Energy; Global Warming; گرمایش جهانی; Mathematical modeling; Optimisation globale; Renewable Energy; پنل PV; انرژی خورشیدی; algorithme génétique; Modelado matemático; التحسين العالمي; PV panel; module PV; الخوارزمية الجينية; Energía solar; هزینه انرژی; Panel fotovoltaico; PV module; الاحتباس الحراري; Calentamiento global; coste de la energía; Global Optimization; Solarenergie; mathematische Modellierung; الطاقة المتجددة; الألواح الكهروضوئية; genetischer Algorithmus; erneuerbare Energie; algoritmo genético; Réchauffement climatique; módulo fotovoltaico
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2013.03.033

•Genetic Algorithm optimization ability had been utilized to extract parameters of PV panel model.•Effect of solar radiation and temperature variations was taken into account in fitness function evaluation.•We used Matlab-Simulink to simulate operation of the PV-panel to validate results.•Different cases were analyzed to ascertain which of them gives more accurate results.•Accuracy and applicability of this approach to be used as a valuable tool for PV modeling were clearly validated.
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.