Parameters Estimation of Photovoltaic Modules Using Optimization Methods Based on Metaheuristics

This paper deals to evaluate a model already developed for photovoltaic (PV) modules, called global nonlinear model. Based in electrical circuit of a single-diode for PV modules' the main goal is to perform through a comparative study of precision with applying the optimization methods Pattern Search (PS), Particle Swarm Optimization (PSO) and Evolutionary Particle Swarm Optimization (EPSO) in the process of parameters estimating in the PV module model. The global nonlinear model was initially proposed with a process for estimating its parameters using the PS optimization method, therefore, it is necessary to evaluate new optimization methods in the parameter estimation process of this model. Therefore, the precision of the global nonlinear model and optimization methods were evaluated, that is, its ability to predict the behavior of I- V and P- V curves based on comparison with experimental curves, using the Mean Absolute Error in Power (MAEP) as a comparative indicator for the PV module technologies of mono crystalline silicon, polycrys-talline silicon, amorphous silicon, cadmium telluride. The results showed that stochastic metaheuristic optimization methods can lead to good results in estimating the parameters of the evaluated PV modules model.