Eur. Phys. J. Plus (2021) 136: 470
https://doi.org/10.1140/epjp/s13360-021-01462-4

Regular Article

Using a novel optimization algorithm for parameter extraction of photovoltaic cells and modules

¹ Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
² Department of Electrical Engineering, Babol Noshirvani University of Technology, Babol, Iran
³ Dynamic Systems and Simulation Laboratory, Technical University of Crete, Chania, Greece
⁴ Department of Systems Engineering and Automatic Control, Universidad de Sevilla, Sevilla, Spain

^a n_pormousa@alumni.ac.ir

Received: 4 April 2021
Accepted: 19 April 2021
Published online: 30 April 2021

Abstract

The critical worldwide revolution towards clean energy has prompted the improvement of studies on the fabrication of high-performance solar cells. In this regard, rendering an accurate model of the solar cell for performance evaluation in the simulation could be essential. So far, several models have been proposed for the solar cell, including single-diode model (SDM), double-diode model (DDM), and three-diode model (TDM). By increasing the number of diodes considered in the equivalent circuit in order to deliver a more accurate model, the number of unknown parameters which must be identified will be increased as well. Therefore, presenting an efficient algorithm to estimate these parameters becomes an interesting issue in recent years. In this study, an improved optimization algorithm, called springy whale optimization algorithm (SWOA), is proposed to estimate the model parameters of solar cells. SWOA is a generalization of the WOA and has the advantages of high convergence speed, global search capability, and high robustness over it. In order to inquire the efficiency of SWOA, this algorithm is posed to estimate the parameters of models of solar cells and photovoltaic (PV) modules as well; the simulation results authenticate the supremacy of the proposed algorithm. Furthermore, the effectiveness of SWOA algorithm in the practical application has been evaluated using commercial modules, including polycrystalline (SW255), multi-crystalline (KC200GT), and monocrystalline (SM55). This assessment is carried out for various operating conditions under different irradiance and temperature conditions, which yield variations in the parameters of the PV model. The results obtained from various experimental setups confirm the high performance and robustness of the proposed algorithm.