Investigation of the transformer winding high-frequency parameters identification using particle swarm optimisation method

• Published in: IET electric power applications Vol. 10; no. 9; pp. 923 - 931
• Main Authors: Chanane, Abdallah, Bouchhida, Ouahid, Houassine, Hamza
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.11.2016
• Subjects: air core; Diagnostic systems; genetic algorithm; genetic algorithms; high‐frequency parameter identification; high‐frequency transformer winding; intelligent method; Optimization; Parameter identification; Parameters; particle swarm optimisation; particle swarm optimisation method; PSO method; Robustness; Swarm intelligence; transfer function; transfer functions; transformer windings; Transformers; Winding; transfer function; genetic algorithm; transformer windings; particle swarm optimisation; intelligent method; high-frequency transformer winding; PSO method; particle swarm optimisation method; transfer functions; genetic algorithms; high-frequency parameter identification; air core

Intelligent methods are used more and more nowadays, in various fields, whose main purpose is to find better solutions to problems that are considered difficult. Identifying the parameters of transformer winding is a crucial problem. In this study, the authors shall use the ‘particle swarm optimisat...