Chaotic Inertia Weight Particle Swarm Optimization (CIWPSO): An Efficient Technique for Solar Cell Parameter Estimation

Abstract

Solar cell modeling and optimal estimation of their associated parameters is a key point to improve performance of PV solar system. Recently, different numerical, analytical and hybrid approaches have been developed for parameter extraction of PV model. In this paper the Chaotic Inertia Weight Particle Swarm Optimization (CIWPSO) technique is proposed to estimate PV parameters of single and double diode. Furthermore, the Newton Raphson method (NRM) is employed to guide the fitness indicator towards optimal solution. The propose approach solves the premature convergence problem of the conventional PSO. This new approach is implemented on RTC France Silicon Solar cell, under standard test conditions (STC). CIWPSO has ability to find optimal solution with the requirement of relatively less computational time and number of iterations. The validity of results clearly supports the statement that, the proposed approach is highly accurate, efficient and fast for parameter estimation of PV cells.