基于电压、电流不平衡度差值的干式变压器匝间短路故障识别方法

干式变压器绕组发生轻微匝间短路时，相电压、相电流等电气量变化甚微，不能作为表征匝间短路故障的敏感特征量，导致相应保护措施缺失，运行过程中设备烧毁事故时有发生。通过建立干式变压器“场-路”耦合仿真模型，利用实际试验和工程计算获取的状态参数，验证模型的准确性。通过建立和分析其绕组匝间短路故障数学模型，提取相电压、相电流不平衡度标幺值的差值，作为判断匝间短路故障的特征量。通过仿真分析不同工况下其绕组发生匝间短路故障时不同电气量的变化情况，论证了所提新故障特征量不仅能提前感知绕组匝间短路故障，而且能够克服固有的三相不对称及不平衡运行带来的影响，有效性、灵敏性兼顾，为实时监测干式变压器绕组匝间绝缘状态提供一种新方法。

Identification method for an inter-turn short circuit fault of a dry-type transformer based onvoltage and current imbalance difference

When a slight inter-turn short circuit occurs in the winding of a dry-type transformer, electrical quantities such as phase voltage and phase current change little, and thus cannot be used as a sensitive characteristic quantity to characterize the inter-turn short circuit fault. This results in the lack of corresponding protection measures, and equipment burning accidents occur frequently during operation. In this paper, a ''field-circuit'' coupling simulation model of a dry-type transformer is established, and the state parameters obtained by actual test and engineering calculation are used to verify the accuracy of the model. By establishing and analyzing the mathematical model of an inter-turn short circuit fault of a dry-type transformer winding, the difference of per unit value of phase voltage and phase current imbalance is extracted as the characteristic quantity to judge the inter-turn short circuit fault of the winding. Through the simulation analysis of the changes of different electrical quantities when the inter-turn short circuit fault occurs in the dry-type transformer winding under different working conditions, it is demonstrated that the new fault characteristic quantity proposed in this paper can not only perceive the inter-turn short circuit fault of the winding in advance, but also overcome the inherent three-phase asymmetry and unbalanced operation. Effectiveness and sensitivity are taken into account, and this provides a new method for real-time monitoring of the inter-turn insulation state of a dry-type transformer winding.

This work is supported by the National Key Research and Development Program of China (No. 2017YFB0902800).