Estimation of Photovoltaic Cells Parameters Using Chaos Embedded Salp Swarm Algorithm

Abstract

Solar photovoltaic (PV) systems have recently attracted researcher’s attention as a clean source of energy. Thus, the importance to design appropriately the photovoltaic cells highly raises. The main problems faced in the design process are first, the development of a useful model describing the characteristics of the current vs. voltage able to simulate the real solar cells behaviours and then, the precise estimation of photovoltaic cells parameter values. This paper employs an improved version of Salp Swarm Algorithm called Chaotic Salp Swarm Algorithm (CSSA) for the parameters estimation of solar cells in both single and double diode models. CSSA approach benefits from chaotic maps proprieties, and has the advantage of providing good equilibrium between exploration and exploitation mechanisms as well. Performance of the proposed CSSA is compared to fourteen known algorithms. Experimental results demonstrate that the proposed algorithm has the ability to find the optimal solutions with an accurate estimation of parameters for the courant vs voltage characteristics of real solar cell with high performance.