Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review

M. Fadaee and M.A.M. Radzi

Renewable and Sustainable Energy Reviews, 2012, vol. 16, issue 5, 3364-3369

Abstract: Hybrid renewable energy system has been introduced as a green and reliable power system for remote areas. There is a steady increase in usage of hybrid renewable energy units and consequently optimization problem solving for this system is a necessity. In recent years, researchers are interested in using multi-objective optimization methods for this issue. Therefore, in the present study, an overview of applied multi-objective methods by using evolutionary algorithms for hybrid renewable energy systems was proposed to help the present and future research works. The result shows that there are a few studies about optimization of many objects in a hybrid system by these algorithms and the most popular applied methods are genetic algorithm and particle swarm optimization.

Keywords: Multi-objective optimization; Hybrid system; Stand-alone; Renewable energy; Evolutionary algorithms (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (94)

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DOI: 10.1016/j.rser.2012.02.071

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