基于相关矩阵和动态集合覆盖的配电网故障诊断方法

作为电力网络中直接向用户供电的关键环节，配电网的工作状态直接影响电力用户的用电质量和用电体验。为解决配电网故障线路区段的定位问题，提出了一种基于相关矩阵和动态集合覆盖的配电网故障诊断方法。根据配电网拓扑建立故障电流信息和故障线路区段相关矩阵，引入隐马尔科夫模型刻画每条线路区段随时间变化的状态序列; 基于每个时间周期上馈线终端单元上报的故障电流信息集合，建立动态集合覆盖的配电网故障诊断模型，使用维特比译码求解满足集合覆盖条件的线路区段工作状态序列，实现对配电网的在线故障定位。通过仿真实例验证了基于相关矩阵和动态集合覆盖的配电网故障诊断方法的定位准确性和稳定性。

Dependency matrix and dynamic set-covering based fault diagnosis method for power distribution networks

As a key part of the power network that directly supplies power to users, the working states of the power distribution networks influence the power quality and experience of users directly. In order to solve the problem of localizing the faulty sections in the power distribution networks, we propose a dependency matrix and dynamic set-covering based fault diagnosis method in this paper. Firstly, we establish the dependency matrix between the fault current information and the faulty sections according to the topology of the power distribution network. Then, the hidden Markov model is introduced to describe the state sequence of each section over time. Based on the set of fault current information reported by the feeder terminal unit, we establish a dynamic set-covering based fault diagnosis model and use Viterbi Decoding to obtain the state sequence of each section that satisfies the covering constraints and realize the online faulty section localization in power distribution networks. Finally, simulation results validate the accuracy and stability of the proposed dependency matrix and dynamic set-covering based fault diagnosis method.