DocumentCode
686544
Title
Multi-objective optimization for renewable energy distributed generation based on fuzzy satisfaction
Author
Jia Panpan ; Zeng Jun ; Chen Chuanchuan
Author_Institution
Coll. of Electr. Power, South China Univ. of Technol., Guangzhou, China
fYear
2013
fDate
11-13 Dec. 2013
Firstpage
1
Lastpage
4
Abstract
This paper presents a new approach to the multi-objective optimization for the hybrid renewable energy distributed generation system based on fuzzy satisfaction degree. Firstly, based on the analysis of the characteristics of the distributed power supply, three indexes, including economy cost, power supply reliability and power factor, are chosen. And then, the fuzzy satisfaction degree is proposed based on the concept of fuzzy mathematics to reflect the objective function with more comprehensively, veritably and naturally. And then the three individual indexes are converted and unified to overall satisfaction degree. Then, the event driven optimization process is established and global optimization is achieved by genetic algorithm. Finally, a scenario case study is demonstrated and indicates that the approach is a suitable solution for the multi-objective optimization to the distributed hybrid renewable energy generation system.
Keywords
distributed power generation; fuzzy set theory; genetic algorithms; hybrid power systems; power distribution economics; power distribution reliability; power factor; distributed power supply; economy cost; fuzzy mathematics concept; fuzzy satisfaction degree; genetic algorithm; hybrid renewable energy distributed generation system; multiobjective optimization; power factor; power supply reliability; Batteries; Distributed power generation; Educational institutions; Hybrid power systems; Optimization; Renewable energy sources; Wind turbines; Distributed generation; genetic algorithm; multi-objective; optimization; satisfactory degree;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Electronics Systems and Applications (PESA), 2013 5th International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4799-3276-4
Type
conf
DOI
10.1109/PESA.2013.6828223
Filename
6828223
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