Evaluation of Weighted Mean of Vectors Algorithm for Identification of Solar Cell Parameters

Processes

Rania M. Ghoniem¹  Amir Y. Hassan²  Abeer Galal Elsayed³  Mokhtar Said³  Alaa A. K. Ismaeel⁴  Sanchari Deb⁵ 

[1] Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia;Department of Power Electronic and Energy Conversion, Electronics Research Institute, Giza 12311, Egypt;Electrical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 43518, Egypt;Faculty of Computer Studies (FCS), Arab Open University (AOU), Madinat Sultan Qaboos P.O. Box 1596, Oman;VTT Technical Research Centre of Finland Ltd., 02044 Espoo, Finland;

关键词: photovoltaic;    parameter identification;    triple-diode model;    single-diode model;    double-diode model;    optimization;   

DOI  :  10.3390/pr10061072

来源: DOAJ

【 摘 要 】

The environmental and technical benefits of renewable energy sources make expanding their use essential in our lives. The main source of renewable energy used in this work is photovoltaic energy. Photovoltaic cells are a clean energy source dependent on solar irradiance to generate electricity from sunlight. The identification of solar cell variables is one of the main items in the simulation and modeling of photovoltaic models. The models used in this work are triple-diode, double-diode, and single-diode solar cells. A novel optimization method called weighted mean of vectors (INFO) is applied for estimating the solar cell variables in the three models. The fitness function of identification is to minimize the root-mean-square error (RMSE) between the measured data of current and the data of simulated current based on the parameters identified from the algorithms. The INFO technique is compared with another seven methods: Harris hawk optimization (HHO), tunicate swarm algorithm (TSA), sine—cosine algorithm (SCA), moth–flame optimizer (MFO), grey wolf optimization (GWO), chimp optimization algorithm (ChOA), and Runge–Kutta optimization (RUN).

【 授权许可】

Unknown