Using immune genetic algorithm to optimize the reactive power
Huang, Wei, Hu, Eric and Ghamami, Khayam 2004, Using immune genetic algorithm to optimize the reactive power, in AUPEC 2004 : Australasian Universities Power Engineering Conference Brisbane, Australia, University of Queensland, School of Information Technology & Electrical Engineering, Brisbane, Qld, pp. 1-8.
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Title
Using immune genetic algorithm to optimize the reactive power
AUPEC 2004 : Australasian Universities Power Engineering Conference Brisbane, Australia
Editor(s)
Saha, Tapan
Publication date
2004
Start page
1
End page
8
Publisher
University of Queensland, School of Information Technology & Electrical Engineering
Place of publication
Brisbane, Qld
Summary
A novel algorithm, immune genetic algorithm (IGA) is proposed for reactive power optimization of power system. While retaining excellent characteristics of genetic algorithm (GA), through imitating the biological immune system, the algorithm evaluates and selects the optimal solutions by the affinities between antigens and antibodies. With the regulation of the activating and suppressing of antibodies, IGA can achieve the dynamic balance between individual diversity and population convergence, and avoid getting into the local optimal solution. The proposed IGA is applied to the IEEE 30-bus system, and the results show that it is superior to the GA with good population convergence and fast computing speed.
ISBN
1864997753 9781864997750
Language
eng
Field of Research
090699 Electrical and Electronic Engineering not elsewhere classified