Extraction of Optimal Solar PV Parameters using Hybrid Optimization Techniques

Abstract

PV parameter estimation is a crucial step for the design of converters for solar panels. The optimal PV parameter estimation through two combinatorial social group whale optimization algorithms (HS-WOA and HS-WOA+) is done for single diode and double diode models. The optimization requires the minimization of the error function, formulated based on the three major points of operation of a PV panel. A comparative analysis involving monocrystalline, polycrystalline and thin-film PV cells is performed. The hybrid algorithms outperformed the parent algorithms in terms of optimality, accuracy and faster convergence.