Accurate Parameter Determination for Photovoltaic Systems Using Meta-Heuristic Methods: A Comparative Study with Particle Swarm Optimization and Multiple Objective Functions

Abstract

The effective implementation of photovoltaic (PV) systems heavily relies on accurate electrical modeling, where The Single Diode Model (SDM) stands out for its ability to accurately capture the complex behavior of photovoltaic (PV) modules. The SDM involves five unknown parameters, presenting a challenge for precise determination. This study investigates and compares of meta-heuristic methods in addressing this parameter determination challenge. Specifically, Particle Swarm Optimization (PSO) is employed using two distinct objective functions: and Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). The validation of these methods is conducted on a PV module provided by RTC FRANCE under standard test conditions (STC). The outcomes of PSO indicate a realistic and accurate determination of the unknown parameters and precise prediction of the I-V curve for the PV module. This research contributes valuable insights into the application of meta-heuristic methods for enhancing the precision and reliability of electrical modeling in PV systems.