Novel approach for a ladder network model of the transformer winding high-frequency parameters identification based on FRA data

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dc.contributor.authorChanane, Abdallah
dc.contributor.authorBelazzoug, Messaoud
dc.date.accessioned2025-04-21T21:23:22Z
dc.date.available2025-04-21T21:23:22Z
dc.date.issued2021
dc.description.abstractThe identification of the high-frequency ladder network model (LNM) parameters for the transformer winding is the way to confirm its actual condition. This paper aims to present the application of one of the latest approach algorithms, namely, Particle Swarm Optimization with Invasive Weed Optimization (PSO-IWO) method for the identification of the high frequency LNM parameters for the transformer winding. The physical realizability of the LNM is ensured and it is based on the frequency response analysis FRA data and some terminal measurements of a transformer winding. The results are agreement and indicate that the identified model, is superior in terms of representing the physical behavior of the transformer winding in high frequency.
dc.identifier.urihttp://dspace.univ-oeb.dz:4000/handle/123456789/21966
dc.language.isoen
dc.publisherUniversity of Oum El Bouaghi
dc.subjectIdentification; Transformer winding; Diagnosis; Equivalent circuit; PSO-IWO
dc.titleNovel approach for a ladder network model of the transformer winding high-frequency parameters identification based on FRA data
dc.typeArticle
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The 1 ST international conference on electronics, artificial intelligence and technologies ICEAINT 2021