PV parameters extraction using metaheuristics

Abstract

Interest in photovoltaics has been increasing hugely over the past years.Among the many interests developed, theoretical understanding of PVs has taken much attention in research.To help in design and assess the performance of PV panels, a developed model is used. The model is none other than an equivalent electrical circuit with basic components (a source, resistors, and one diode or more). Single-diode and double-diode models are the most popular in the literature. Equivalent circuit parameters must be obtained, from either a set of experimental data or a manufacturer’s datasheet, in order to construct a model. The aim is to obtain values that yield an accurate model. The problem is tackled as an optimization one, where the Root mean square error (RMSE), between the experimental and the calculated data, is the function to be optimized. Optimization is achieved using five different meta- heuristic algorithms: Particle swarm optimization (PSO), Wind driven optimization (WDO), Exchange market algorithm (EMA),Differential evolution (DE), and Marine predators algorithm(MPA). The aforementioned algorithms are adapted to PV parameters extraction using MATLAB. Algorithms are then compared based on the accuracy of the obtained results.