DocumentCode :
403405
Title :
Computational enhancement of genetic algorithm via control device pre-selection mechanism for power system reactive power/voltage control
Author :
Bakare, G.A. ; Aliyu, U.O. ; Krost, G. ; Venayagamoorthy, G.K.
Author_Institution :
Abubakar Tafawa Balewa Univ., Bauchi, Nigeria
Volume :
3
fYear :
2003
fDate :
13-17 July 2003
Abstract :
In this paper, the application of a novel and computationally enhances genetic algorithm (GA) for solving the reactive power dispatch problem is presented. In order to attain a significant reduction in the computational time of GA, a systematic procedure of reactive power control device pre-selection mechanism is herein proposed to choose a-priori subsets of the available control devices, which maximally influence buses experiencing voltage limit violations. The GA reactive power dispatch module then accesses such judiciously pre-selected control device candidates to determine their optimal settings. A pragmatic scheme aimed at further curtailing the number of the final control actions entertained is also set forth. The far-reaching simulation results obtained for two case study scenarios using the proposed algorithmic procedures on a German utility network of Duisburg, replicated on an operator-training simulator, are presented and fully discussed in depth.
Keywords :
genetic algorithms; power system control; reactive power control; voltage control; Duisburg; German utility network; control device pre-selection mechanism; genetic algorithm; operator-training simulator; power system reactive power control; reactive power dispatch problem; varying fitness function; voltage control; Control systems; Genetic algorithms; Optimal control; Power system control; Power system simulation; Power systems; Reactive power; Reactive power control; Shunt (electrical); Voltage control;
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.2003.1267411
Filename :
1267411
Link To Document :
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