DocumentCode :
2119740
Title :
A Combination Strategy for Reactive Power Optimization Based on Model of Soft Constrain Considered Interior Point Method and Genetic-Simulated Annealing Algorithm
Author :
Liya, Guo ; Xiaoqun, Ding ; Guangyu, Chen ; Jizhong, Song ; Qihui, Cui ; Wenhua, Liu
Author_Institution :
Dept. of Energy & Electr., HoHai Univ., Nanjing, China
Volume :
2
fYear :
2010
fDate :
7-8 Aug. 2010
Firstpage :
151
Lastpage :
154
Abstract :
In this paper a combination strategy for reactive power optimization is proposed. It bases on the optimal reasult of Genetic-Simulated Annealing Algorithm and Primal-Dual Interior Point(PDIP) Algorithm, and solves the problem of discrete and continuous control variables in reactive power optimization effectively. Simultaneity, it introduces the soft costraint to handle the infeasibility problem appearing in the course of reactive power optimization. Numeriacal simulation results on the IEEE57 and the IEEE118 test system show that the proposed method can brings up the speed and the convergence of computation, and illustrate that the proposed method can effectively handle and detect the infeasibility problem caused by bottleneck constraints and get a reasonable solution fast.
Keywords :
genetic algorithms; numerical analysis; reactive power control; simulated annealing; IEEE118 test system; IEEE57; bottleneck constraints; continuous control variables; genetic-simulated annealing algorithm; infeasibility problem; numerical simulation; primal-dual interior point algorithm; reactive power optimization; soft constrain considered interior point method; Annealing; Convergence; Hybrid power systems; Reactive power; Simulated annealing; Annealing Algorithm; Genetic-Simulated; Primal-Dual Interior Point Algorithm; reactive power optimization; soft constraint; the infeasibility problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Management Engineering (ISME), 2010 International Conference of
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-7669-5
Electronic_ISBN :
978-1-4244-7670-1
Type :
conf
DOI :
10.1109/ISME.2010.270
Filename :
5573912
Link To Document :
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