电力数据通信网络阻塞故障节点快速辨识研究

Research on fast identification of blocking fault node in power data communication network

由于电力通信与网络相互依存,使用传统方法存在节点负荷损失和通信中断时间辨识不精准的问题,为此提出了电力数据通信网络阻塞故障节点快速辨识研究。引入潮流熵作为阻塞故障点识别指标,计算潮流中心节点电流,使潮流逼近线路传输极限。计算节点潮流熵,分析电力数据通信网络连通性。通过通信网络节点阵列分布情况,构建通信信道特征分解函数,确定故障节点分布特征。考虑支路节点与中心通信节点间距离,构建阻塞故障节点辨识模型,根据该模型设计故障节点跟踪命令,利用辨识矩阵计算网络阻塞程度,完成故障节点快速辨识。由实验结果可知,该方法损失负荷最大值为40 MW,最小值为20 MW,中断时间始终保持2 s不变,辨识结果与实际结果一致,具有精准快速辨识效果。

Due to the interdependence between power communication and network,the traditional methods have the problems of inaccurate identification of node load loss and communication interruption time.Therefore,a study on fast identification of blocking fault nodes in power data communication network is proposed.Power flow entropy is introduced as the identification index of blocking fault points,and the current of power flow center node is calculated to make the power flow approach the transmission limit of the line.The node power flow entropy is calculated,and the connectivity of power data communication network is analyzed.Through the distribution of communication network node array,the characteristic decomposition function of communication channel is constructed to determine the distribution characteristics of fault nodes.Considering the distance between the branch node and the central communication node,the identification model of the blocking fault node is constructed.According to the model,the fault node tracking command is designed,and the network blocking degree is calculated using the identification matrix to complete the rapid identification of the fault node.It can be seen from the experimental results that the maximum value of the load loss of this method is 40 MW,the minimum value is 20 MW,and the interruption time remains unchanged for 2 s.The identification results are consistent with the actual results,with accurate and fast identification effects.