Title :
Optimal sizing of a hybrid renewable system
Author :
Sánchez, Víctor ; Ramirez, Juan M. ; Arriaga, Gerardo
Author_Institution :
CINVESTAV, Unidad Guadalajara, Zapopan, Mexico
Abstract :
Sizing of an electric power generation system requires an analysis of the investment, maintenance, and operation costs. In the case of a generation system that uses renewable sources the sizing it is more complex with regard to a conventional system, due to the randomness of the renewable resources, and to the even high costs of wind generators and photovoltaic modules. This paper presents the optimal sizing of a generation system wind-photovoltaic-fuel cell such that demand of an isolated residential load is met. The function objective is constituted by the costs of the system, and the solution method employed is based on evolutionary computation technique called Particle Swarm Optimizer (PSO). The aim of this work is to minimize the total cost of the system such that demand is met. In order to compare the performance of PSO with other method, the sizing of the renewable generation system is made it also by the heuristic method called Differential Evolution.
Keywords :
maintenance engineering; particle swarm optimisation; photovoltaic power systems; renewable energy sources; wind power plants; differential evolution; electric power generation system; evolutionary computation technique; hybrid renewable system; investment analysis; maintenance analysis; operation costs; optimal sizing; particle swarm optimizer; photovoltaic modules; renewable sources; wind generators; wind-photovoltaic-fuel cell; Cost function; Energy storage; Fossil fuels; Fuel cells; Hybrid power systems; Hydrogen; Photovoltaic systems; Power generation; Solar power generation; Wind energy generation; Alternative energy; Optimization; PSO;
Conference_Titel :
Industrial Technology (ICIT), 2010 IEEE International Conference on
Conference_Location :
Vi a del Mar
Print_ISBN :
978-1-4244-5695-6
Electronic_ISBN :
978-1-4244-5696-3
DOI :
10.1109/ICIT.2010.5472544