吴星;刘天琪;李兴源;李从善;

• 1:四川大学电气信息学院

摘要(Abstract)：

针对当前应用于状态估计的广域量测系统(wide area measurement system,WAMS)和SCADA系统混合量测中相量测量单元(phasor measurement unit,PMU)最优配置点的选取问题,在分析WAMS/SCADA数据差异的基础上,提出一种基于数据兼容和改进模糊C均值(fuzzy C-means,FCM)聚类算法的PMU最优配置方案。采用大数据挖掘理念,通过改进FCM聚类算法对SCADA数据依据相关度分区,在分区内可观测度最大的节点配置PMU,各分区内采用该PMU节点的最优平滑系数进行Vondrak插值,得到满足兼容性的数据,应用于混合模型的状态估计。相对只考虑可观测度的PMU配置方案,新方案不仅可以实现WAMS/SCADA数据有效兼容,提高估计精度,应用混合量测的状态估计还可有效控制系统负荷快速变化时的估计误差。通过在IEEE 39节点系统上模拟日负荷变化,验证了该PMU最优配置方案的有效性。

关键词(KeyWords)： 状态估计;SCADA;广域量测系统;大数据挖掘;数据兼容;改进FCM聚类算法;PMU最优配置;Vondrak插值算法

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金资助项目(51037003)~~

作者(Author): 吴星;刘天琪;李兴源;李从善;

Email:

DOI: 10.13335/j.1000-3673.pst.2014.03.032

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