Estimation of Parameters of One-diode and Two-diode Photovoltaic Models: A Chaotic Gravitational Search Algorithm based Approach

Abstract

ABSTRACT Photovoltaic (PV) module is one of the major sources of clean energy to substantially reduce the global carbon footprint. Researchers are keen on developing an equivalent PV mathematical model to acquire insights regarding its monitoring and operations. This is a stimulating task as these modules are sensitive to operational conditions. In this work, a chaotic gravitational search algorithm (CGSA) based method is proposed for estimating the PV parameters of the one-diode and the two-diode PV models. The proposed method includes an update to confine the decision variables within the appropriate ranges. It is tested on the RTC France cell and the Photowatt-PWP-201 PV module. The suitability is highlighted considering the mean absolute error (MAE) and the root mean square error (RMSE) between the experimental and the estimated currents. For example, the errors are in the orders of and (one-diode model) and and (two-diode model), respectively, for the Photowatt-PWP-201 PV module. A comparative analysis of the proposed method with several popular algorithms (e.g. equilibrium optimizer (EO), whale optimization algorithm (WOA), Harris hawks optimization (HHO), variants of particle swarm optimization (PSO) etc.) is presented. Results and the comparative analysis confirm the effectiveness of the suggested approach.