Synchronous machine parameter identification using particle swarm optimization

G. I. Hutchison, B. Zahawi, K. Harmer, B. Stedall, D. Giaouris

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Synchronous machines are the most widely used machines in power generation. Identifying their parameters in a non invasive way is very challenging due to the inherent nonlinearity of machine performance. This paper proposes a synchronous machine parameter identification method using particle swarm optimization (PSO) with a constriction factor. The PSO allows a synchronous machine model output to be used as the objective function to give a new, more efficient method of parameter identification. This paper highlights the effectiveness of the proposed method for the identification of synchronous machine model parameters, using both simulation and manufacturers measured experimental data. The paper will also consider the effectiveness of the method as the number of parameters to be identified is increased.

Original languageBritish English
Title of host publication5th IET International Conference on Power Electronics, Machines and Drives, PEMD 2010
Edition563 CP
DOIs
StatePublished - 2010
Event5th IET International Conference on Power Electronics, Machines and Drives, PEMD 2010 - Brighton, United Kingdom
Duration: 19 Apr 201021 Apr 2010

Publication series

NameIET Conference Publications
Number563 CP
Volume2010

Conference

Conference5th IET International Conference on Power Electronics, Machines and Drives, PEMD 2010
Country/TerritoryUnited Kingdom
CityBrighton
Period19/04/1021/04/10

Keywords

  • Parameter identification
  • Particle swarm optimization
  • PSO
  • Synchronous machines

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