DocumentCode
3090457
Title
A new evolutionary algorithm for placement of distributed generation
Author
Bahmanifirouzi, Bahman ; Niknam, Taher ; Taheri, Seyed Iman
Author_Institution
Dept. of Electr. Eng., Islamic Azad Univ., Marvdasht, Iran
Volume
1
fYear
2011
fDate
8-9 Sept. 2011
Firstpage
104
Lastpage
107
Abstract
The impacts of DG on various aspects of distribution system operation depend highly on location and size of DG. In this paper, a multi-objective optimization algorithm for the siting and sizing of distributed generation is proposed. The objectives consist of minimization costs and losses of distributed system and optimization of voltage profile. This multi-objective optimization is solved by the improved honey bee mating optimization (HBMO) algorithm. HBMO is modified on mating step because of it´s converges to local optima. In many cases, these objectives contradict each other and cannot be handled by conventional single or multi objective optimization techniques. For this reason, a fuzzy system is used. This algorithm is executed on a typical 70-bus test system. Results show the proper siting and sizing of DGs are important to improve the voltage profile, reduce costs and losses of distribution system. Accuracy and speed to achieved aims are the most important advantage of this algorithm.
Keywords
distributed power generation; evolutionary computation; fuzzy systems; power distribution planning; power generation planning; cost minimization; distributed generation placement; distributed generation siting; distributed generation sizing; distribution system operation; evolutionary algorithm; fuzzy system; honey bee mating optimization algorithm; loss minimization; multiobjective optimization algorithm; voltage profile optimization; Distributed power generation; Fuel cells; Heuristic algorithms; Minimization; Optimization; Probability; Turbines; Distributed generation (DG) placement; honey bee mating optimization; multi-objective;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Engineering and Automation Conference (PEAM), 2011 IEEE
Conference_Location
Wuhan
Print_ISBN
978-1-4244-9691-4
Type
conf
DOI
10.1109/PEAM.2011.6134806
Filename
6134806
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