Optimum sizing of hybrid PV/wind/battery system using Fuzzy-Adaptive Genetic Algorithm

This paper proposes the optimum sizing methodology to optimize the configuration of hybrid energy system. For this, we use an approach for automatic fuzzy rule base generation and optimization by means of Fuzzy-Adaptive Genetic Algorithm, wich changes dynamically the crossover and mutation rates ensuring population diversity and avoiding premature convergence. This Algorithm allows us to obtain the optimal number of photovoltaic panels, wind turbines and storages units ensuring the minimal global high efficiency system total cost and guaranteeing the permanent availability of energy to cover the load energy requirements. Historical hourly wind speed, solar irradiance and load data are used to stochastically model the wind turbines, photovolaic generation and load. The total cost is the objective function and the technical size is a contraint.