DocumentCode :
3508763
Title :
Optimal VAr allocation by genetic algorithm
Author :
Iba, Kenji
Author_Institution :
Mitsubishi Electric Corp., Hyogo, Japan
fYear :
1993
fDate :
1993
Firstpage :
163
Lastpage :
168
Abstract :
Keeping up with the times and computer technology, many researchers have applied new mathematical approaches extensively to solve various problems in power systems. AI technology, fuzzy theory and artificial neural networks are recent trends. This paper presents a new optimization method for reactive power planning using genetic algorithms. The genetic algorithm (GA) is a kind of search algorithm based on the mechanics of natural selection and genetics. This algorithm can search for a global solution using a multiple path and have a structure fit to integer problems. The proposed method was applied to practical 51-bus and 224-bus systems to show its feasibility and capabilities.
Keywords :
genetic algorithms; power engineering computing; power system planning; reactive power; AI; artificial neural networks; fuzzy theory; genetic algorithm; global solution; natural selection; optimisation; power engineering computing; power system planning; reactive power; search algorithm; Artificial intelligence; Capacitors; Genetic algorithms; Inductors; Linear programming; Load flow; Power system control; Power system planning; Reactive power; Shunt (electrical);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of
Conference_Location :
Yokohama, Japan
Print_ISBN :
0-7803-1217-1
Type :
conf
DOI :
10.1109/ANN.1993.264296
Filename :
264296
Link To Document :
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