电力系统接地极线路故障类型识别技术研究

Research on Fault Type Identification Technology of Power System Grounding Pole Line

针对电力系统接地极线路故障类型识别中存在的响应速度慢、识别精度低等问题,提出一种基于信号处理、模式识别以及数据融合的故障类型识别方法。首先利用小波变换和经验模态分解(Empirical Mode Decomposition,EMD)提取故障电流、电压信号的时频域特征量,其次分别构建支持向量机(Support Vector Machine,SVM)和概率神经网络(Probabilistic Neural Network,PNN)故障识别模型,最后采用证据理论融合两种模型的诊断结果,得到最终的故障类型判断。实验结果表明,该方法能够有效识别单相金属性接地、单相高阻接地以及两相短路等典型故障类型,识别精度高、可靠性强,为保障电力系统的安全运行提供有力支撑。

Aiming at the problems of slow response speed and low recognition accuracy in fault type identification of grounding lines in power system,a fault type identification method based on signal processing,pattern recognition and data fusion is proposed.Firstly,wavelet transform and empirical mode decomposition are used to extract the time-frequency domain features of fault current and voltage signals.Secondly,support vector machine and probabilistic neural network fault identification models are constructed respectively.Finally,the diagnosis results of the two models are fused by evidence theory,and the final fault type judgment is obtained.The experimental results show that this method can effectively identify typical fault types such as single-phase metallic grounding,single-phase high-resistance grounding and two-phase short circuit,with high identification accuracy and strong reliability,which provides a strong support for ensuring the safe operation of power system.