基于神经网络的中性点经消弧线圈接地系统故障选线方法

中性点经消弧线圈接地系统的单相接地故障选线问题一直没有得到很好的解决,通常采用的单一故障选线方法如小波变换法、5次谐波电流法和零序电流有功分量法等只能对部分故障信息进行处理,选线可靠性不高.文章通过构造每种选线方法的相对故障测度函数和可确定故障测度函数来确定其故障测度函数,再利用神经网络对每种选线方法的实际故障测度进行智能融合,从而得到可靠性较高的故障选线结果.EMTP仿真结果表明该方法得出的选线结果具有较高的精度和较强的鲁棒性.

Neural Network Based Faulty Line Detection Method for Power System with Neutral Grounding via Arc Suppression Coil

The faulty line detection of single-phase-to-earth fault in power system with neutral grounding via arc suppression coil has not been well solved.The commonly used single faulty line detection methods,such as wavelet transform method,the fifth harmonic current method and zero sequence current active components method,etc.,can only process partial fault information,so their reliability of faulty line detection is not satisfied.Here,by means of constructing both relative fault measurement function and confirmable fault measurement function the fault measurement function of each faulty line detection method is determined,then using neural network the intelligent fusion of practical fault measurements of those faulty line detection methods is conducted,thereby the faulty line detection result with higher reliability can be obtained.Simulation results by EMTP show that the faulty line detection result by the proposed method is more precise and possesses stronger robustness.