Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/62771
Title: Solving transient-stability constrained optimal power flow problems with wavelet mutation based hybrid particle swarm optimization
Authors: Chan, KY
Ling, SH
Chan, KW 
Pong, GTY
Iu, HHC
Keywords: Particles swarm optimization
Genetic algorithm
Wavelet theory
Mutation
Multi-contingency transient stability constrained optimal power flow problems
Issue Date: 2008
Publisher: Institute for Scientific Computing and Information
Source: International journal of information and systems sciences, 2008, v. 4, no. 4, p. 585-601 How to cite?
Journal: International journal of information and systems sciences 
Abstract: The paper extends our pervious work on solving multi-contingency transient stability constrained optimal power flow problems (MC-TSCOPF) with the approach of particles swarm optimization (PSO). A hybrid PSO method that incorporates with a new wavelet theory based mutation operation, intends to improve the searching strategies on previously used PSO methods, is proposed to solve MC-TSCOPF problems. It employs wavelet theory in enhancing PSO methods in exploring solution spaces more effectively and robustly in reaching better solutions. A case study on the New England 39-bus system indicates that the proposed hybrid PSO outperforms significantly existing PSO methods in terms of solution quality and stability. As a result, reasonable solutions can be reached with faster convergence speeds and smaller computational efforts.
URI: http://hdl.handle.net/10397/62771
ISSN: 1708-296X
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