基于交互式主动探测的电力综合数据网故障定位算法

Fault Location Algorithm of Integrated Data Network for Power System Based on Interactive Active Detection

针对电力综合数据网对故障定位的准确性和时效性要求,提出一种交互式故障诊断机制,并重点解决该机制中故障定位集的选取问题,提出一种基于交互式主动探测的故障定位集选择算法(IPCA)。建立电力综合数据网与候选定位集的贝叶斯模型,借助贝叶斯网络条件独立性将候选定位集划分为若干子集,并引入探测价值衡量探测的诊断能力,利用探测价值交互更新过程的子模性降低故障定位集选取的时间复杂度。仿真结果显示,IPCA在确保故障定位准确性的同时平均可缩短20%左右的定位时间。

In view of the accuracy and efficiency requirements on fault location in the integrated data network for power system, an interactive fault diagnosing mechanism is proposed. To resolve the fault location set selection problem in the mechanism, an interactive probing choice algorithm （IPCA） is proposed. A Bayesian model is built for the nodes of power integrated data network and the candidate set of location probes. The set is divided into several subsets with the help of conditional independence character of Bayesian networks. The detection value is introduced to measure the diagnostic capacity of the probe and the time complexity of the fault location set selection is reduced using the submodular character in the interaction update process. Simulation results show that IPCA shortens the location time by 20%on average while ensuring the accuracy of fault location.