Application of GA, PSO and ABC in optimal design of a stand-alone hybrid system for north-west of Iran

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 b...

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Bibliographic Details
Main Authors: Javadi, M. R., Mazlumi, K., Jalilvand, A.
Format: Conference Proceeding
Language:English
Subjects:
Batteries
Genetic algorithms
Hybrid power systems
Reliability
Wind speed
Wind turbines
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Summary: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.