Parameter identification of Jiles-Atherton hysteresis model of current transformer based on hybrid genetic simulated annealing algorithm

Songhui Zhang; Xinguang Xu; Yu Xing; Jian Yang; Tao Liu; Xianguang Dong; Yuqi Wang

doi:10.1117/12.2620588

29 November 2021 Parameter identification of Jiles-Atherton hysteresis model of current transformer based on hybrid genetic simulated annealing algorithm

Songhui Zhang, Xinguang Xu, Yu Xing, Jian Yang, Tao Liu, Xianguang Dong, Yuqi Wang

Author Affiliations +

Proceedings Volume 12080, 4th International Symposium on Power Electronics and Control Engineering (ISPECE 2021); 1208009 (2021) https://doi.org/10.1117/12.2620588
Event: 4th International Symposium on Power Electronics and Control Engineering (ISPECE 2021), 2021, Nanchang, China

Abstract

Aiming at the problem that it is difficult to obtain the core parameters of the current transformer simulation model, a genetic simulated annealing algorithm is proposed in this paper. This method combines simulated annealing algorithm with genetic algorithm to overcome the premature phenomenon of traditional genetic algorithm. It realizes the fast fitting of core specific parameters of current transformer J-A model, and can quickly build the current transformer simulation model. The effectiveness of the algorithm is verified by example simulation.

Citation Download Citation

Songhui Zhang, Xinguang Xu, Yu Xing, Jian Yang, Tao Liu, Xianguang Dong, and Yuqi Wang "Parameter identification of Jiles-Atherton hysteresis model of current transformer based on hybrid genetic simulated annealing algorithm", Proc. SPIE 12080, 4th International Symposium on Power Electronics and Control Engineering (ISPECE 2021), 1208009 (29 November 2021); https://doi.org/10.1117/12.2620588

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