A Comprehensive Method for Optimum Sizing of Hybrid Energy Systems using Intelligence Evolutionary Algorithms

Abstract

Exhibition a comprehensive method for optimum sizing of hybrid energy systems using intelligence evolutionary algorithms is performed in this paper. The aim of the method is to find the optimum sizes of the hybrid energy systems among the numerous configurations to reach the expected reliability and the lowest LCE. In this respect, the mathematical model of each component is represented and the components are simulated by means of a comprehensive energy management strategy. Ability to comprise reliability constraints is another outstanding trait of this model. After formulation of the cost function consists of investment and operation cost of proposed hybrid system including reliability constraints, GA and PSO are applied to optimize the cost function. This model can be implemented to such hybrid energy systems with other configurations too. Proficiency of the presented model is shown by means of the results of the simulations implemented via actual weather details from Shiraz weather data.