Hybrid GA neuro-fuzzy damping control system for UPFC

Laiq Khan, K.L. Lo, S. Jovanovic

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The aim of the paper is to develop a novel genetic algorithm (GA)-based supplementary NeuroFuzzy damping control system for the unified power flow controller (UPFC). The designed scheme employs a micro-GA (µ-GA) to avoid being trapped in a local minimum as opposed to the use of the classical back-propagation technique. The scheme also uses the "Grand-Parenting" technique for seeding the initial population to hasten the GA convergence speed. To further speed up the GA for solving the optimization problem, a parallel µ-GA scheme is also used. It has been discovered that a parallel µ-GA scheme with three computers setup is approximately three times faster than the µ-GA with a single computer node. Also when µ-GA is integrated with the "Grand-Parenting" technique for seeding the initial population, it would hasten the convergence speed. The control scheme exhibits strong robustness and excellent damping performance when tested on a multi-machine power system.
Original languageEnglish
Pages (from-to)841-861
Number of pages20
JournalCOMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
Volume25
Issue number4
DOIs
Publication statusPublished - 2006

Keywords

  • electric power systems
  • fuzzy control
  • programming
  • algorithm theory

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