Paper Info
Title
Cooperative co-evolutionary approach applied in reactive power optimization of power system
Abstract
Cooperative Co-evolutionary Approach (CCA) is a new architecture of evolutionary computation. Based on CCA, the paper proposes a new method for reactive power optimization problem in power system, which is non-convex, non-linear, discrete, and usually with a large number of control variables. According to the decomposition-coordination principle, the reactive power optimization problem is decomposed into a number of sub-problems, which is optimized by a single evolutionary algorithm population. The populations interact with each other through a common system model and co-evolve and result in the continuous evolution of the whole system. The reactive power optimization problem is solved when the co-evolutionary process ends. Simulation results show that compared with conventional Genetic Algorithm (GA), CCA not only can obtain better optimal results, but also has better convergence property. CCA reduce the over-long computational time of GA and is more suitable for solving large-scale optimization problems.
Year
DOI
Venue
2006
10.1007/11881070_85
ICNC (1)
Keywords
Field
DocType
common system model,reactive power optimization problem,large-scale optimization problem,evolutionary computation,new architecture,single evolutionary algorithm population,large number,new method,power system,whole system,cooperative co-evolutionary approach,evolutionary algorithm,genetic algorithm,reactive power,system modeling,optimization problem,evolutionary computing
Population,Mathematical optimization,Evolutionary algorithm,Computer science,Electric power system,Evolutionary computation,AC power,Optimization problem,Genetic algorithm,System model
Conference
Volume
ISSN
ISBN
4221
0302-9743
3-540-45901-4
Citations 
PageRank 
References 
0
0.34
3
Authors
5
Name
Order
Citations
PageRank
Jianxue Wang101.35
Weichao Wang250033.87
Wang Xifan3115.77
Haoyong Chen4196.81
Xiuli Wang500.34