Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review
- 作者：M. Fadaee ; Mfadaee@gmail.com ; M.A.M. Radzi
- 关键词：RE ; renewable energy ; PV ; photovoltaic ; GA ; genetic algorithm ; RETs ; renewable energy technologies ; VRLA ; valve regulated lead acid ; SOC ; state of charge ; HRES ; hybrid renewable energy system ; LP ; linear programming ; EUE ; expected unnerved energy ; LCOE ; l
- 刊名：Renewable and Sustainable Energy Reviews
- 出版年：2012
- 期刊代码：44_13640321
- 类别：pw
- 出版时间：June, 2012
- 卷：16
- 期：5
- 页码：3364-3369
- 文件大小：671 K
摘要
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.