Remanence Prediction of Transformer Based on J-A Hysteresis Theory

LONG Qi; YANG Xu; JIANG Keru; ZHANG Changhong; HOU Mingchun; XIN Yu; XIONG Dehua; DUAN Xiongying

doi:10.13296/j.1001-1609.hva.2026.10.008

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Remanence Prediction of Transformer Based on J-A Hysteresis Theory

Research & Analysis | 更新时间：2026-10-14

- Remanence Prediction of Transformer Based on J-A Hysteresis Theory
- High Voltage Apparatus Vol. 62, Issue 10, Pages: 68-75(2026)
- 作者机构：
  
  中国南方电网超高压输电公司电力科研院，广州 510663
  大连理工大学电气工程学院，辽宁大连 116024
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2026.10.008
  CLC：
- Received：09 May 2026，
  
  Revised：2026-07-12，
  
  Published：16 October 2026
- 稿件说明：
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LONG Qi, YANG Xu, JIANG Keru, et al. Remanence Prediction of Transformer Based on J-A Hysteresis Theory[J]. High Voltage Apparatus, 2026, 62(10): 68-75.
DOI：

LONG Qi, YANG Xu, JIANG Keru, et al. Remanence Prediction of Transformer Based on J-A Hysteresis Theory[J]. High Voltage Apparatus, 2026, 62(10): 68-75. DOI： 10.13296/j.1001-1609.hva.2026.10.008.

摘要

用断路器实现变压器的选相投切是减小励磁涌流的有效措施，选相合闸的核心是根据分闸后的剩磁得到合适的合闸角度。针对剩磁的预测，电压积分法存在积分上限不易确定的问题，而Jiles-Atherton（J-A）模型具有参数物理含义明晰，计算准确等优点。首先，针对目前提取J-A模型参数的粒子群算法（particle swarm optimization，PSO）收敛速度慢、容易陷入局部最优解的问题，提出了一种改进粒子群优化算法，通过优化粒子的速度和位置更新公式，解决了传统粒子群算法收敛速度慢，容易陷入局部最优解的问题。这种新的算法不仅加快了收敛速度，也平衡了整体和局部的搜寻能力。然后，基于J-A模型对变压器进行剩磁预测，搭建变压器空载合闸实验平台，使用PSCAD/EMTDC搭建结合J-A模型和经典变压器的仿真模型，在不同的合闸角度下预测变压器的剩磁。最后，将仿真与实际实验录波数据相结合，通过比较励磁涌流的峰值验证了剩磁预测的准确性。

Abstract

Using circuit breaker to achieve phase-controlled switching of transformer is an effective measure to reduce inrush current. The core of phase-controlled closing is to obtain the appropriate closing angle based on the remanent flux after opening. In the context of remanence prediction

the voltage integration method has the problem that the upper integration limit is difficult to determine

while the Jiles-Atherton(J-A)model has the advantages of clear physical meaning of parameters and accurate calculation. First

to address the problems of slow covergence and a tendency to fall into local optimal solutions in the particle swarm optimization(PSO)algorithm currently used for extracting J-A model parameters

an improved particle swarm-optimization algorith is proposed. By optimizing the velocity and position update formulas of the particles

the issue of slow convergence and susceptibility to local optima in the traditional PSO algorithm are resolved.This new algorithm not only accelerates the convergence speed but also balances the global and local search capabilities.Then

the remanence prediction of the transformers is carried out based on J-A model. A transformer no-load closing exprimental platform is established

and a simulation model combining the J-A model and the classifical transformer model is built using PSCAD/EMTDC to predict the remanence flux under difefrent closing angles.Finally

the accuracy of remanence prediction is verified by comparing the peak value of inrush current by way of combining simulation with experimental recorded data.

关键词

Keywords

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