Comparative Analysis of Parameter Extraction Techniques for Healthy and Degraded PV Modules

Efficient extraction of photovoltaic model parameters is crucial for the simulation, analysis, and monitoring of photovoltaic power plants (PV). Recently, there has been considerable growth in the development of traditional algorithms and metaheuristics designed to estimate the PV model parameters using real data. However, due to the uncertainty surrounding the selection of the optimal algorithm, this investigation undertakes a comprehensive comparative analysis of three metaheuristic techniques for stochastic parameter extraction, including particle swarm optimization (PSO), bacterial foraging optimization (BFO) and war strategy optimization (WSO). MATLAB is used to validate the application and simulation of algorithms on a single-diode model of PV panels in healthy and degraded states. Experimental results validate the effectiveness of the suggested algorithms and unequivocally prove that the WSO technique is a promising and practical approach to parameter estimation in this challenging application.