An Enhanced Chaotic Based Whale Optimization Algorithm For Parameter Extraction of Photovoltaic Models

Parameter estimation of model of Photovoltaic model has substantial influence on systems performance. Effectiveness of algorithms has been used to estimate parameters to obtain the best performance of Photovoltaic systems. Therefore, in this study, to acquire parameters of photovoltaic systems, Chaotic Henon based Whale optimization algorithm (HWOA) has been proposed such that randomness of Henon map and whale optimization algorithms is combined and hybridized. Furthermore, the proposed four different Chaotic Henon-based Whale optimization algorithms have been shown to increase accuracy and reliability compared to the current whale optimization algorithm. Performances of algorithms have been evaluated by considering statistical values. In addition, Wilcoxon and Friedman tests have been used to test the reliability of the comparison results obtained from the algorithms.Consequently, it has been determined that experimental results of proposed algorithms have better performance than the algorithms in literature.