A Hybrid Optimized WOA Parameter Extraction Algorithm of Perovskite Solar Cells' Three-Diode Core Equivalent Circuit Model

Abstract

The three-diode equivalent circuit model accurately describes the electrical characteristics of solar cells, but its obvious nonlinearities and other defects often lead to problems such as low accuracy and susceptibility to local optimization when parameters are extracted using traditional optimization methods. To address this challenge, this article proposes a hybrid whale optimization algorithm (HWOA) that combines the whale optimization algorithm (WOA) and nonlinear least squares (NLSs). The core mechanism consists of a global search via the WOA to determine the approximate parameter ranges, and a local optimization via the NLSs method to improve the final accuracy. This approach achieves a balance between global exploration and local convergence, resulting in the efficient extraction of optimal solutions for the parameters. Experimental validation was performed using a measurement dataset of perovskite solar cells. The proposed algorithm achieves the lowest root mean square error (RMSE) values. The proposed algorithm was further validated using KC200GT solar cells under different light intensity and temperature conditions. The experimental results show a high correlation between the fit values and the measured values, proving the validity and reliability of the algorithm for parameter extraction.