A new approach based on modified social network search algorithm combined with dichotomy method for solar photovoltaic parameter estimation

Abstract

Obtaining the best performance of photovoltaic requires a proper model. This paper uses a new approach based on a modified social network search algorithm combined with the dichotomy method to produce the best parameters of a photovoltaic cell, module, and array. To improve the performance of the parameters to be estimated, a control parameter via a Gaussian and Cauchy distribution is randomly added in the search space to allow the agents to converge to the optimal solution. Then the dichotomy method is inserted into the objective function to compute the best-estimated currents. The application of the proposed model on three different systems, and the subsequent comparison with existing methods show the high accuracy of the proposed method, with the best root mean square error of 6.3554 × 10−4 for the RTC cell, 1.9096 × 10−3 for the Photowatt PWP module and 0.0134 for the 18 PV experimental field.