A novel optimal parameters identification of triple-junction solar cell based on a recently meta-heuristic water cycle algorithm

Abstract

A novel methodology for extracting the optimal parameters of PV module with high efficiency InGaP/InGaAs/Ge triple-junction solar cells (TJSCc) is developed. Such methodology is based on recent meta-heuristic approach of Water Cycle Algorithm (WCA). The TJSC model is represented by single diode model and then a constrained objective function has been derived to be used in the optimization process of optimal parameter estimation. The analysis has been carried out based on high efficiency InGaP/InGaAs/Ge TJSC. The performance of WCA is evaluated and tested for TJSC based PV module operated with various irradiances and temperatures. Finally, a comparison between the proposed methodology and experimental data is carried out. Furthermore; other algorithms are programmed and applied to solve the problem under study like grey wolf optimizer (GWO), antlion optimizer (ALO), mine blast algorithm (MBA), harmony search algorithm (HSA) and the obtained results via these approaches are compared with those obtained by the proposed WCA. The results reveal the validity and superiority of WCA in extracting the optimal parameters of the TJSC based PV module.