Parameter identification of photovoltaic cell/module using genetic algorithm (GA) and particle swarm optimization (PSO)

Abstract

Parameter identification of a photovoltaic (PV) cell is essential to simulate the behavior and to optimize the different characteristics of the PV generator. Therefore, the prediction of the PV system behavior will be possible; this allows a better energy management and a good operation reliability. There are several models that express the physical behavior of a PV cell to reproduce well the I-V curve in real conditions. In this paper, we focus on metaheuristic methods; two algorithms were used and compared, Genetic Algorithm (GA) and Particle Swarm method (PSO) with experimental results.