Parameters identification of photovoltaic solar cells and module using the genetic algorithm with convex combination crossover

Abstract

ABSTRACTTo design a high-performance photovoltaic (PV) system, the parameters extraction of solar cell models is exceedingly crucial. A new variant of the genetic algorithm (GA) called Genetic Algorithm with Convex Combination Crossover (GACCC) is proposed to identify the unknown electrical parameters of different solar cell models, i.e. single diode, double diode, and PV module. GACCC is achieved by integrating a new crossover operation to maintain a good balance between the intensification of the best solutions and the diversification of the search space. To test the proposed GACCC, we have compared it to the basic GA and with other literature techniques. The results indicate a high performance of developed approach GACCC and a high accuracy of estimated parameters. In addition, the efficiency of the results is confirmed by the good agreement between the experimental I-V data and the simulated results in all cases.