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

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  • Fadaee, M.
  • Radzi, M.A.M.

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.

Suggested Citation

  • Fadaee, M. & Radzi, M.A.M., 2012. "Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3364-3369.
    • Handle: RePEc:eee:rensus:v:16:y:2012:i:5:p:3364-3369
    DOI: 10.1016/j.rser.2012.02.071
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