基于小波神经网络的特高压直流输电线路故障测距方法

Fault Location Method for Ultra-High Voltage Direct Current Transmission Lines Based on Wavelet Neural Networks

传统特高压直流输电线路故障测距方法直接对故障区段进行识别,未对故障电压信号空间状态模型进行构建,这导致了传统方法测距的精度存在较大误差。针对这一问题,文章提出了基于小波神经网络的特高压直流输电线路故障测距方法。通过构建故障电压信号空间状态模型进行故障区段识别,最后基于小波神经网络实现故障测距。对比实验结果表明,本文研究方法测距精度误差较小,具有重要的实际应用价值。

Traditional fault location methods for ultra-high voltage direct current transmission lines directly identify the fault section without constructing a spatial state model of the fault voltage signal,which leads to significant errors in the location accuracy.In response to this issue,this paper proposes a fault location method for ultra-high voltage direct current transmission lines based on wavelet neural networks.The method involves constructing a spatial state model of the fault voltage signal to identify the fault section,followed by fault location using the wavelet neural network.Comparative experimental results show that the proposed method has a smaller location accuracy error,demonstrating significant practical application value.