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.
LanguageEnglish
Pages841-861
Number of pages20
JournalCOMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
Volume25
Issue number4
DOIs
Publication statusPublished - 2006

Fingerprint

Hybrid Genetic Algorithm
Power Flow
Neuro-fuzzy
Damping
Genetic algorithms
Control System
Genetic Algorithm
Control systems
Controller
Controllers
Parallel Genetic Algorithm
Convergence Speed
Parallel algorithms
Back Propagation
Local Minima
Power System
Speedup
Backpropagation
Robustness
Optimization Problem

Keywords

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

Cite this

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Hybrid GA neuro-fuzzy damping control system for UPFC. / Khan, Laiq; Lo, K.L.; Jovanovic, S.

In: COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, Vol. 25, No. 4, 2006, p. 841-861.

Research output: Contribution to journalArticle

TY - JOUR

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AU - Lo, K.L.

AU - Jovanovic, S.

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