DocumentCode :
2594455
Title :
Pseudo-parallel genetic algorithm for reactive power optimization
Author :
Wang, Z.H. ; Yin, X.G. ; Zhang, Z. ; Yang, J.C.
Author_Institution :
Dept. of Electr. & Electron. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
2
fYear :
2003
fDate :
13-17 July 2003
Abstract :
In this paper, static voltage stability is considered in reactive optimization via the minimum singular value of the Jacobian matrix of converged power flow, and a pseudo-parallel genetic algorithm is introduced to find the global optimal results and avoid premature of conventional simple genetic algorithm. Two simple test systems are employed to verify the effectiveness of the proposed model and algorithm. Simulations results show that both operational and economical performances of test power systems are improved after optimization, and either the optimal results or the convergent characteristics of the proposed algorithm are superior to those of the simple genetic algorithm.
Keywords :
Jacobian matrices; genetic algorithms; load flow; parallel algorithms; power system simulation; reactive power control; singular value decomposition; Jacobian matrix; PGA; economical performances; global optimal results; parallel genetic algorithm; power flow; power systems; reactive power optimization; simulations results; singular value decomposition; static voltage stability; Genetic algorithms; Jacobian matrices; Load flow; Power system economics; Power system modeling; Power system simulation; Reactive power; Stability; System testing; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering Society General Meeting, 2003, IEEE
Print_ISBN :
0-7803-7989-6
Type :
conf
DOI :
10.1109/PES.2003.1270428
Filename :
1270428
Link To Document :
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