Automatic J–A Model Parameter Tuning Algorithm for High Accuracy Inrush Current Simulation

Xishan Wen, Jingzhuo Zhang and Hailiang Lu
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Xishan Wen: School of Electric Engineering, Wuhan University, Wuhan 430072, China
Jingzhuo Zhang: School of Electric Engineering, Wuhan University, Wuhan 430072, China
Hailiang Lu: School of Electric Engineering, Wuhan University, Wuhan 430072, China

Energies, 2017, vol. 10, issue 4, 1-15

Abstract: Inrush current simulation plays an important role in many tasks of the power system, such as power transformer protection. However, the accuracy of the inrush current simulation can hardly be ensured. In this paper, a Jiles–Atherton (J–A) theory based model is proposed to simulate the inrush current of power transformers. The characteristics of the inrush current curve are analyzed and results show that the entire inrush current curve can be well featured by the crest value of the first two cycles. With comprehensive consideration of both of the features of the inrush current curve and the J–A parameters, an automatic J–A parameter estimation algorithm is proposed. The proposed algorithm can obtain more reasonable J–A parameters, which improve the accuracy of simulation. Experimental results have verified the efficiency of the proposed algorithm.

Keywords: inrush current; transformer modeling; transient simulation; J–A model; feature representation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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