Characterization Method of Paper Insulation Aging State at Transformer Hot Spots Based on Genetic Algorithm and Finite Element Simulation

doi:10.3969/j.issn.1008-0198.2024.03.006

Abstract

Abstract: :Current assessment method based on frequency domain dielectric spectrum(FDS)cannot reflect the aging state of the insulation at the hot spots. Therefore,an“inverse model”is proposed by combining multi-objective genetic algorithm and finite element simulation method to obtain the aging information of paper insulation in high-temperature areas of transformers.A finite element model of oil-paper insulation under non-uniform aging is constructed,which can establish the mapping relationship between the aging state of oil-paper insulation and FDS data in different aging regions. Based on the measured FDS data of the oil-paper insulation system,a multi-objective genetic algorithm is designed to solve the parameter distribution in the finite element model.The validation experiment results show that the extracted parameters of the FEM simulation model can well characterize the aging state of the paper insulation in the hot spot area and the relative error of the model is less than 7% under laboratory conditions.

Key words: frequency domain spectroscopy, oil-paper insulation, non-uniform aging, transformers, finite element simulation

CLC Number:

TM403.3

LU Bingrong, WANG Qingyin. Characterization Method of Paper Insulation Aging State at Transformer Hot Spots Based on Genetic Algorithm and Finite Element Simulation[J]. Hunan Electric Power, 2024, 44(3): 40-47.

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