 Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A reviewM. Fadaee and M.A.M. Radzi Renewable and Sustainable Energy Reviews, 2012, vol. 16, issue 5, pages 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) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: http://EconPapers.repec.org/RePEc:eee:rensus:v:16:y:2012:i:5:p:3364-3369 Ordering information: This journal article can be ordered from Access Statistics for this article Renewable and Sustainable Energy Reviews is edited by L. Kazmerski More articles in Renewable and Sustainable Energy Reviews from Elsevier |
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