Investigation of hybrid particle swarm optimization methods for solving transient-stability constrained optimal power flow problems

K.Y. Chan, G.T.Y. Pong, Ka Wing Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

In this paper, hybrid particle swarm optimization (PSO) is proposed for solving the challenging multi-contingency transient stability constrained optimal power flow (MC-TSCOPF) problem. The objective of this nonlinear optimization problem is to minimize the total fuel cost of the system and at the same time fulfil the transient stability requirements. The optimal power flow (OPF) with transient stability constraints considered is re-formulated as an extended OPF with additional rotor angle inequality constraints, which is suitable for hybrid PSO to solve. Comparison between various existing hybrid PSO techniques is carried out by solving the New England 39-bus system. Experimental results indicate that the hybrid PSO integrated with the mutation operation of genetic algorithms is better than the other existing hybrid PSO methods in both 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)61-67
Number of pages7
JournalEngineering Letters
Volume16
Issue number1
Publication statusPublished - 2008

Keywords

  • Particle swarm optimization
  • Genetic algorithms
  • Transient stability
  • Optimal power flow
  • Constrained optimization

ASJC Scopus subject areas

  • Engineering(all)

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