摘要
研究电网故障挖掘的优化问题。电力网络处在随机云层笼罩中时,云层中会形成极高的浪涌云层电压,电压与电力设备形成回路,造成电网承压瞬间增大,出现过压干扰,这种干扰极强,会对故障特征模型形成冲击。传统的电网故障检测模型在这种干扰下提取的电网故障特征会大幅偏离真实值,造成云层浪涌电压干扰下的电网故障检测失真。为解决上述问题,提出了一种基于关联故障特征算法的电网故障挖掘技术。建立电网故障特征搜素模型,在浪涌电压的干扰下获取准确的电网故障特征。利用关联故障特征方法,对电网故障进行挖掘。实验结果表明,关联故障特征算法能够有效提高在浪涌电压干扰的情况下进行电网故障挖掘的准确性。
In this article, the optimization of grid fault mining was researched. Electricity network is shrouded in random clouds. Clouds can form a high voltage surge, and then the voltage and power devices may form a loop, cau- sing momentary increasing pressure - bearing of electricity network. To solve these problems, we proposed a grid fault mining method based on associated fault characteristics algorithm. Firstly, the feature searching model of grid faults was established, and then the accurate grid fault characteristics were obtained in the interference of surge volt- age. By using the method of associated fauh characteristics, the grid fault was carried out. Experimental results show that the associated fault characteristics algorithm can effectively improve the accuracy of the grid fault mining under the interference of snr^es voltage.
出处
《计算机仿真》
CSCD
北大核心
2013年第10期153-156,228,共5页
Computer Simulation
基金
江苏省科技支撑计划-工业部分(BE2011133)