Solving transient-stability constrained optimal power flow problems with wavelet mutation based hybrid particle swarm optimization

K.Y. Chan, S.H. Ling, Ka Wing Chan, G.T.Y. Pong, H.H.C. Iu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)585-601
Number of pages17
JournalInternational journal of information and systems sciences
Volume4
Issue number4
Publication statusPublished - 2008

Keywords

  • Particles swarm optimization
  • Genetic algorithm
  • Wavelet theory
  • Mutation
  • Multi-contingency transient stability constrained optimal power flow problems

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