Characterizing Parameters in Single-Diode and Double-Diode Photovoltaic Models Using a Novel Bio-Inspired Approach

Abstract

The precise characterization of electrical models relating to the photovoltaic (PV) systems stands as a pivotal task for the advancement of PV energy technology. There are numerous models available in the literature where each comprising multiple undetermined parameters. Precisely determining these parameters pose a considerable challenge. This article introduces a novel metaheuristic algorithm for the determination of PV parameters in the Single-Diode Model (SDM) and the Double-Diode Model (DDM). It is called the Dingo Optimization Algorithm (DOA). The algorithm’s efficacy is evaluated through testing on two distinct PV systems: the RTC France cell and PWP201 module. The findings are compared with established algorithms such as DPDE, and DOA demonstrates outstanding superiority, achieving the smallest error of 7.41937e-04 A for the RTC France cell using DDM. This study underscores the potential of DOA in advancing the accuracy of PV parameter determination, a critical aspect in optimizing PV system efficiency and performance.