Quantum Genetic Algorithm and its Application in Power System Reactive Power Optimization

Author

Miao, Hongxia ; Wang, Honghua ; Deng, Zhixiang

Volume

1

fYear

2009

fDate

11-14 Dec. 2009

Firstpage

107

Lastpage

111

Abstract

Quantum Genetic Algorithm (QGA) is a genetic algorithm (GA) based on principles of quantum computing (QC). It uses quantum bit coding, whole interference crossover and quantum gate as update operator to complete evolution search. Compared with conventional GA, QGA is characterized by small population size, rapid convergence and strong global search capability. In this paper, QGA is applied in power system reactive power optimization. Simulation and calculation is carried out in IEEE-6 node test system, and the validity and superiority of the proposed algorithm are proved.

Keywords

genetic algorithms; power systems; reactive power; IEEE-6 node test system; convergence; global search capability; power system reactive power optimization; quantum bit coding; quantum gate; quantum genetic algorithm; whole interference crossover; Biological cells; Constraint optimization; Convergence; Genetic algorithms; Interference; Power engineering computing; Power system security; Power systems; Quantum computing; Reactive power; QGA; quantum rotation gate; reactive power optimization; whole interference crossover;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security, 2009. CIS '09. International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-5411-2

Type

conf

DOI

10.1109/CIS.2009.133

Filename

5376701