DocumentCode
2823155
Title
Novel Adaptive Genetic Algorithm for Reactive Power Optimization of Power System
Author
Yang Guang ; Liu Xin-rong
Author_Institution
Inst. of Opt-Electron. Inf. Technol., Yantai Univ., Yantai, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
In order to avoid the premature convergence and improve convergence rate, a novel adaptive genetic algorithm for reactive power optimization is discussed in detail. In reproduction operator, the method of retaining optimal individual is used to ensure the convergence and at the same time, the competition method is also adopted to keep the better dispersal of all individuals. In Mutation operator, the mutation probability Pm is improved based on adaptive genetic algorithm. When fitness of individuals in the population tends to be identical, Pm can be adjusted to make bigger, and the local convergence can be avoided greatly. The algorithm has been applied to IEEE 30-bus testing system .The test shows that this algorithm is feasible and practical.
Keywords
genetic algorithms; power systems; reactive power; IEEE 30-bus testing system; adaptive genetic algorithm; mutation operator; power system; reactive power optimization; Evolutionary computation; Genetic algorithms; Genetic mutations; Mathematical model; Power engineering and energy; Power generation; Power systems; Reactive power; System testing; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5363700
Filename
5363700
Link To Document