Electrical characterization of photovoltaic modules using farmland fertility optimizer

Abstract

Photovoltaic (PV) model parameters are essential in recognizing its effectiveness at changed sun irradiances, temperatures and under various loading conditions. Estimating PV model parameters can be considered as a high non-linear optimization problem. The objective function is adapted with the aim of the minimization in regards to the root of the mean squared errors among the corresponding calculated and real current points subjects to set of parameters constraints. In this research, a novel application of newly developed farmland fertility optimization (FFO) algorithm to identify the PV model unknown parameters is addressed. This research work aims at producing an efficient PV models to characterize their performances under changed environmental conditions. Two electrical models such as one- and double-diode equivalent circuits are analyzed carefully. The applicability of the FFO approach is assessed by comparing its simulated results with the empirical results of three typical commercial PV systems. Subsequently, comparisons between the FFO cropped results and other competing recent methods-based results are made to validate the FFO results. It can be declared here that the FFO executes well and owns a good strength to recognize unknown PV model parameters with lesser errors.