A Novel Optimization Approach Using Chaos Game Optimization Algorithm for Parameters Estimation of Photovoltaic Cells

Abstract

The utilization of solar photovoltaics (PV) in electricity generation is progressively increasing due to its environmental benefits, such as reducing power transmission costs and mitigating global warming. This research aims to enhance the effectiveness of the extracted PV parameters. To estimate the parameters of the PV model, a recent optimization algorithm called the Chaos Game Optimization algorithm (CGO) is employed to precisely choose PV parameters. In this work, PV cells are modeled using two different models, including the single-diode model (SDM) and the double-diode model (DDM). The CGO algorithm outperformed nine well-known optimization algorithms based on the root–mean squares of error (RMSE) with a percentage of up to 97% for the single-diode model (SDM) and up to 92.92% for the double-diode model (DDM).