基于巴氏系数的变压器励磁涌流和故障差流识别新判据

传统变压器励磁涌流识别方法在复杂电磁环境以及电流互感器(CT)饱和等情况下会受到干扰而导致保护动作速度变慢或者误动。为解决此问题,提出一种利用电流波形分布特征识别励磁涌流的变压器差动保护新判据。结合巴氏系数图像匹配算法,对比差动电流和正弦信号的波形相似度以区分励磁涌流和故障电流。并利用PSCAD/EMTDC软件仿真以及动模试验验证了该判据在变压器空载合闸、区内和区外故障、带故障合闸以及CT饱和等工况下的有效性。

A novel criterion to distinguish inrush current from fault current based on the Bhattacharyya coefficient

Because of a complicated electromagnetic environment and Current Transformer (CT) saturation, the conventional methods of transformer inrush current identification may operate with a long time delay or even mal-operate. To solve this problem, a new magnetizing inrush identification method based on the distribution characteristics of the current waveform is proposed. The fault differential current and inrush current are distinguished by comparing the waveform similarity between the differential current and the sinusoidal signal using the Bhattacharyya coefficient. Based on a PSCAD/EMTDC simulation and dynamic experiment tests, the validity of the criterion is verified under the conditions of unloaded transformer energization, internal and external faults, energizations with faults and CT saturation, as well as faults accompanied with CT saturation. This work is supported is supported by National Natural Science Foundation of China (No. 51607106) and Open Foundation of Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station (China Three Gorges University) (No. 2018KJX05).