DocumentCode
1065644
Title
A hybrid genetic algorithm-interior point method for optimal reactive power flow
Author
Yan, Wei ; Liu, Fang ; Chung, C.Y. ; Wong, K.P.
Author_Institution
Minist. of Educ., Key Lab. of High Voltage Eng. & Electr. New Technol., Chongqing
Volume
21
Issue
3
fYear
2006
Firstpage
1163
Lastpage
1169
Abstract
By integrating a genetic algorithm (GA) with a nonlinear interior point method (IPM), a novel hybrid method for the optimal reactive power flow (ORPF) problem is proposed in this paper. The proposed method can be mainly divided into two parts. The first part is to solve the ORPF with the IPM by relaxing the discrete variables. The second part is to decompose the original ORPF into two sub-problems: continuous optimization and discrete optimization. The GA is used to solve the discrete optimization with the continuous variables being fixed, whereas the IPM solves the continuous optimization with the discrete variables being constant. The optimal solution can be obtained by solving the two sub-problems alternately. A dynamic adjustment strategy is also proposed to make the GA and the IPM to complement each other and to enhance the efficiency of the hybrid proposed method. Numerical simulations on the IEEE 30-bus, IEEE 118-bus and Chongqing 161-bus test systems illustrate that the proposed hybrid method is efficient for the ORPF problem
Keywords
genetic algorithms; load flow; Chongqing 161-bus test systems; IEEE 118-bus test systems; IEEE 30-bus test systems; continuous optimization; discrete optimization; dynamic adjustment strategy; hybrid genetic algorithm; nonlinear interior point method; optimal reactive power flow; Genetic algorithms; Helium; Laboratories; Numerical simulation; Power generation; Programming profession; Reactive power; System testing; Transformers; Voltage control; Genetic algorithm (GA); interior point method (IPM); nonlinear programming; optimal reactive power flow (ORPF);
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/TPWRS.2006.879262
Filename
1664951
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