Parameters Identification of Synchronous Machine Based on Particale Swarm Optimization

This paper, deals with a meta-heuristic method, the Particle Swarm Optimization (PSO), for operational parameters identification of synchronous machine. The considered method consists of minimizing quadratic criterion that represents the difference between simulated model at standstill frequency res...

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Bibliographic Details
Published inE3S web of conferences Vol. 336; p. 52
Main Authors Elrachid, Bendaoud, Hammoud, Radjeai, Oussama, Boutalbi
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 2022
Subjects
Frequency dependence
Frequency response
Heuristic methods
Mathematical models
Parameter identification
Particle swarm optimization
Synchronous machines
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Summary:This paper, deals with a meta-heuristic method, the Particle Swarm Optimization (PSO), for operational parameters identification of synchronous machine. The considered method consists of minimizing quadratic criterion that represents the difference between simulated model at standstill frequency response output and those computed from the model to be identified. The obtained results by simulation show that the method based on particle swarm optimization is efficient in terms of convergence speed and gives optimal solution.
ISSN:2267-1242
2555-0403
2267-1242
DOI:10.1051/e3sconf/202233600052