Identification of Parameters in Photovoltaic Models through a Runge Kutta Optimizer

Hassan Shaban, Essam H. Houssein, Marco Pérez-Cisneros, Diego Oliva, Amir Y. Hassan, Alaa A. K. Ismaeel, Diaa Salama AbdElminaam, Sanchari Deb and Mokhtar Said
Additional contact information
Hassan Shaban: Faculty of Computers and Information, Minia University, Minia 61519, Egypt
Essam H. Houssein: Faculty of Computers and Information, Minia University, Minia 61519, Egypt
Marco Pérez-Cisneros: Departamento de Electrónica, Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, Av. Revolución 1500, Guadalajara 44430, Mexico
Diego Oliva: Departamento de Electrónica, Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, Av. Revolución 1500, Guadalajara 44430, Mexico
Amir Y. Hassan: Department of Power Electronic and Energy Conversion, Electronics Research Institute, Giza 12311, Egypt
Alaa A. K. Ismaeel: Faculty of Computer Studies (FCS), Arab Open University (AOU), Madinat Sultan Qaboos P.O. Box 1596, Oman
Diaa Salama AbdElminaam: Faculty of Computers and Artificial Intelligence, Benha University, Governorate 13511, Egypt
Sanchari Deb: VTT Technical Research Centre of Finland Ltd., 02044 Espoo, Finland
Mokhtar Said: Electrical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 43518, Egypt

Mathematics, 2021, vol. 9, issue 18, 1-22

Abstract: Recently, the resources of renewable energy have been in intensive use due to their environmental and technical merits. The identification of unknown parameters in photovoltaic (PV) models is one of the main issues in simulation and modeling of renewable energy sources. Due to the random behavior of weather, the change in output current from a PV model is nonlinear. In this regard, a new optimization algorithm called Runge–Kutta optimizer (RUN) is applied for estimating the parameters of three PV models. The RUN algorithm is applied for the R.T.C France solar cell, as a case study. Moreover, the root mean square error (RMSE) between the calculated and measured current is used as the objective function for identifying solar cell parameters. The proposed RUN algorithm is superior compared with the Hunger Games Search (HGS) algorithm, the Chameleon Swarm Algorithm (CSA), the Tunicate Swarm Algorithm (TSA), Harris Hawk’s Optimization (HHO), the Sine–Cosine Algorithm (SCA) and the Grey Wolf Optimization (GWO) algorithm. Three solar cell models—single diode, double diode and triple diode solar cell models (SDSCM, DDSCM and TDSCM)—are applied to check the performance of the RUN algorithm to extract the parameters. the best RMSE from the RUN algorithm is 0.00098624, 0.00098717 and 0.000989133 for SDSCM, DDSCM and TDSCM, respectively.

Keywords: Runge–Kutta optimizer (RUN); photovoltaic (PV); three diode model; double diode model; single diode model; solar energy (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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