摘要
为了及时监测配电网运行情况进而快速准确甄别配电网的正常、异常以及故障状态,提出基于小波包时间熵的配电网运行状态特征提取方法,给出其小波基函数、分解层数和尺度、时间窗等相关参数的选择规范,分析该小波熵对系统状态表征的机理。搭建典型配电网模型,针对各种运行工况下典型配电网运行状态进行模拟仿真,仿真结果表明,所提方法能够正确区分配电网典型运行状态,并且不受网络拓扑、线路类型、故障类型、故障时刻、故障位置、过渡电阻等因素的影响,具有较好的适应性。
A method of feature extraction based on the wavelet-packet time entropy is proposed ior the timely monitoring of distribution network and the quick identification of its operating states ：normal,abnormal and faulty. The selection principle of its relevant parameters,such as wavelet basis function,decomposition level ＆ scale,time window,etc, are given and the mechanism of expressing the system state by wavelet entropy is analyzed. A typical distribution network model is built and the network operating states under different conditions are simulated. The simulative results show that,with better adaptability and being immune to the network topology,line type,fault type,fault occurrence time,fault location and transition resistance ,the proposed method can correctly identify the typical operating states of distribution network.
出处
《电力自动化设备》
EI
CSCD
北大核心
2014年第9期64-71,79,共9页
Electric Power Automation Equipment
基金
国家自然科学基金面上项目(51277135)
南方电网公司重点科技项目(K-GD2012-343)~~
关键词
配电
运行状态
特征提取
小波包时间熵
模型
监测
electric power distribution
operating states
feature extraction
wavelet-packet time entropy
models
monitoring
