Optimum sizing of hybrid PV/wind/battery using Fuzzy-Adaptive Genetic Algorithm in real and average battery service life

This paper proposes the optimum sizing methodology to optimize the configuration of hybrid energy system in two cases: when the life of a battery is determined with the number charge/discharge and when only the average life is taken. For this, we use an approach for automatic fuzzy rule base generation and optimization by means of Fuzzy-Adaptive Genetic Algorithm, which 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.