DocumentCode :
2806088
Title :
Genetic Algorithm Based Restoration Scheme for Power System Skeleton
Author :
Wang, Chunyi ; Liu, Yutian ; Qu, Hanbing ; Yuan, Zaiji
Author_Institution :
Shandong Univ., Jinan, China
Volume :
4
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
651
Lastpage :
655
Abstract :
Power system skeleton restoration is a typical semi-structured problem, difficult to establish accurate mathematical model to solve. Integrating heuristic rules and numerical calculation with genetic algorithm, the method for skeleton restoration scheme generating of every subsystem is proposed. In this method, fitness value is given by numerical calculation and global optimization is realized by genetic algorithm. The evaluation function of skeleton restoration scheme presented in this paper can comprehensively consider security margin, restoration duration and economic indicators of loads. During encoding, units and loads are mixed together, while they are divided into two parts in order during decoding. The former part gives the restoration sequence of units and the latter part describes that of loads. Calculation speed of this method is improved by incorporating heuristic rules into the generating process of restoration scheme. Simulation results show this method is feasible and effective.
Keywords :
genetic algorithms; numerical analysis; power system economics; power system restoration; genetic algorithm based restoration scheme; heuristic rules; mathematical model; numerical calculation; power system skeleton restoration; semistructured problem; Decoding; Economic indicators; Encoding; Genetic algorithms; Mathematical model; Optimization methods; Power system modeling; Power system restoration; Security; Skeleton; Genetic Algorithm; Power System; Restoration Scheme; Skeleton Restoration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.60
Filename :
5362724
Link To Document :
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