Photovoltaic cells parameters extraction using variables reduction and improved shark optimization technique

Abstract

This article aimed to present a new approach which consists of three-points, and concerns each diode pattern separately. Distinct from traditional curve fitting processes, this approach is based on the simplistic view which flourishes the potential abilities in order to provide the efficient solutions with the least repetitions. The basic reason of this study is to substitute the three – point approach with the previous used approach and set it as core point. By using mentioned points, it reinforces the usage of improved shark smell optimization algorithm and regulates the left parts efficiently. Consequently, it decreases the elaborateness of algorithms. According to the conducted parts comparisons on the three case studies, proved that the presented method has more exactness than the traditional methods. As well as, the investigated the proposed method has high efficiency and presents the optimized solution in various cells type. Also the achieved solutions are stable and is compared with over 17 various algorithms which in whole of the standard deviation of root mean square error for three type of cells is lower than the determined scales in other studies. By having these values, the suggested approach had been predicted to work efficiently in all circumstances like offline analysis and online controlling and it requires an exact, steady approach exploitation tool.