Hybrid PSO-complex algorithm based parameter identification for a composite load model

Manuelito Y. Del Castillo, Hwachang Song, Byong Jun Lee

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper proposes a hybrid searching algorithm based on parameter identification for power system load models. Hybrid searching was performed by the combination of particle swarm optimization (PSO) and a complex method, which enhances the convergence of solutions closer to minima and takes advantage of global searching with PSO. In this paper, the load model of interest is composed of a ZIP model and a third-order model for induction motors for stability analysis, and parameter sets are obtained that best-fit the output measurement data using the hybrid search. The origin of the hybrid method is to further apply the complex method as a local search for finding better solutions using the selected particles from the performed PSO procedure.

Original languageEnglish
Pages (from-to)464-471
Number of pages8
JournalJournal of Electrical Engineering and Technology
Volume8
Issue number3
DOIs
Publication statusPublished - 2013 May 1

Fingerprint

Particle swarm optimization (PSO)
Identification (control systems)
Composite materials
Induction motors

Keywords

  • Complex method
  • Composite load model
  • Hybrid search
  • Parameter identification
  • Particle swarm optimization

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Hybrid PSO-complex algorithm based parameter identification for a composite load model. / Del Castillo, Manuelito Y.; Song, Hwachang; Lee, Byong Jun.

In: Journal of Electrical Engineering and Technology, Vol. 8, No. 3, 01.05.2013, p. 464-471.

Research output: Contribution to journalArticle

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