Parameter extraction of solar photovoltaic models using an improved whale optimization algorithm

Abstract

Parameter extraction of solar photovoltaic (PV) models is a typical complex nonlinear multivariable strongly coupled optimization problem. In this paper, an improved whale optimization algorithm (WOA), referred to as IWOA, is proposed to accurately extract the parameters of different PV models. The original WOA has good local exploitation ability, but it is likely to stagnate and suffer from premature convergence when dealing with complex multimodal problems. To conquer this concerning shortcoming, IWOA develops two prey searching strategies to effectively balance the local exploitation and global exploration, and thereby enhance the performance of WOA. Three benchmark test PV models including single diode, double diode and PV module models, and two practical PV power station models with more modules in the Guizhou Power Grid of China are employed to verify the performance of IWOA. The experimental and comparison results comprehensively demonstrate that IWOA is significantly better than the original WOA and three advanced variants of WOA, and is also highly competitive with the reported results of some recently-developed parameter extraction methods.