Paper Info
Title
Solving Multi-Contingency Transient Stability Constrained Optimal Power Flow Problems With An Improved Ga
Abstract
In this paper, an improved genetic algorithm has been proposed for solving multi-contingency transient stability constrained optimal power flow (MC-TSCOPF) problems. The MC-TSCOPF problem is formulated as an extended optimal power flow (OPF) with additional generator rotor angle constraints and is converted into an unconstrained optimization problem, which is suitable for genetic algorithms to deal with, using a penalty function. The improved genetic algorithm is proposed by incorporating an orthogonal design in exploring solution spaces. A case study indicates that the improved genetic algorithm outperforms the existing genetic algorithm-based method in terms of robustness of solutions and the convergence speed while the solution quality can be kept.
Year
DOI
Venue
2007
10.1109/CEC.2007.4424840
2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS
Keywords
Field
DocType
genetic algorithms,power flow,penalty function,orthogonal design,load flow,genetic algorithm,constrained optimization
Convergence (routing),Mathematical optimization,Power flow,Computer science,Control theory,Meta-optimization,Robustness (computer science),Optimization problem,Contingency,Genetic algorithm,Penalty method
Conference
Citations 
PageRank 
References 
1
0.42
5
Authors
5
Name
Order
Citations
PageRank
K. Y. Chan1735.64
S. H. Ling260940.29
Wai Kin Chan314515.36
Herbert H. C. Iu433460.21
G. T. Y. Pong521.11