DocumentCode :
560881
Title :
Application of GA, PSO and ABC in optimal design of a stand-alone hybrid system for north-west of Iran
Author :
Javadi, Mohammad Reza ; Mazlumi, Kazem ; Jalilvand, Abolfazl
Author_Institution :
Electr. Eng. Dept., Zanjan Univ., Zanjan, Iran
fYear :
2011
fDate :
1-4 Dec. 2011
Abstract :
In this paper, a novel intelligent method is applied to the problem of optimal design hybrid power system for supplying the isolated load demand. The purpose of this design is to optimize the costs during the 20-year operation system. This system includes photovoltaic, wind and a lead-acid battery bank. Using optimization methods of Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) the optimal capacity of these sources is determined. The objective function is minimized and the efficiency of this system in different operation situations. The input data of this paper is real and north western remote areas of Iran is studied. Covering the load demand under various weather conditions is the main constraint in this study.
Keywords :
genetic algorithms; hybrid power systems; lead acid batteries; particle swarm optimisation; photovoltaic power systems; wind power plants; ABC; GA; Iran; PSO; artificial bee colony; genetic algorithm; hybrid power system; isolated load demand; lead-acid battery bank; particle swarm optimization; photovoltaic; stand-alone hybrid system; wind; Batteries; Genetic algorithms; Hybrid power systems; Reliability; Wind speed; Wind turbines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Electronics Engineering (ELECO), 2011 7th International Conference on
Conference_Location :
Bursa
Print_ISBN :
978-1-4673-0160-2
Type :
conf
Filename :
6140254
Link To Document :
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