DocumentCode :
605453
Title :
Distributed generation siting and sizing with implementation feasibility analysis
Author :
Eroshenko, S.A. ; Khalyasmaa, A.I. ; Dmitriev, S.A. ; Pazderin, A.V. ; Karpenko, A.A.
Author_Institution :
Ural Fed. Univ., Ekaterinburg, Russia
fYear :
2013
fDate :
6-8 Feb. 2013
Firstpage :
717
Lastpage :
721
Abstract :
This paper addresses the problem of distributed generation siting and sizing optimization with subsequent equipment configuration assessment. The proposed methodology is based on the combination of genetic algorithms and indicative analysis, which gives an opportunity to assess power system interaction with incident infrastructures and take into account technical, economical, regulatory, ecological and other criteria. Two-step algorithm implementation makes the decision process more flexible and comprehensive. The case study is provided for proposed approach verification.
Keywords :
distributed power generation; genetic algorithms; power distribution planning; power generation planning; distributed generation siting; distributed generation sizing; equipment configuration assessment; genetic algorithm; incident infrastructure; indicative analysis; Distributed power generation; Engines; Estimation; Genetic algorithms; Optimization; Power systems; distributed generation; distribution network; genetic algorithm; indicative analysis; optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power, Energy and Control (ICPEC), 2013 International Conference on
Conference_Location :
Sri Rangalatchum Dindigul
Print_ISBN :
978-1-4673-6027-2
Type :
conf
DOI :
10.1109/ICPEC.2013.6527749
Filename :
6527749
Link To Document :
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