基于历史数据聚类分析的暂态功角稳定故障筛选

大电网中有上千个暂态稳定故障,若对每个故障分别进行暂态评估,难以满足在线评估对时间的要求。为了满足电网在线暂态安全稳定评估快速性的要求,提出了一种基于电网运行历史数据聚类分析的暂态功角稳定故障筛选方法。基于历史数据中的电网运行方式和暂态功角稳定评估结果,提取关键特征量,通过计及稳定模式的矢量量化方法确定聚类数和初始聚类中心,采用K中心点算法对聚类中心进行优化。针对分类后暂态功角稳定的考察故障快速估算其暂态功角裕度,最后得到包含暂态功角失稳和估算裕度低于门槛值的故障组成的用于暂态稳定分析计算的严重故障集。通过对实际省级电网运行历史数据的聚类分析,验证了所述方法的有效性和实用性。

Transient power angle stability contingency screening based on clustering analysis of historical data

There are thousands of transient stability faults in large scale power system. Transient stability analysis cannot be finished in given time required by online assessment. To meet the requirement of calculation time of on-line transient security and stabiliby assessment,an transient power angle security and stability contingency screening method base on clustering analysis of power grid operation history data.Extracting key feature quantities based on power grid operation mode and transient power angle stability assessment results in historical data.Determine the number of clusters and the initial clustering center by vector quantization method that takes into account the stable mode.Optimization of clustering center points using K-Medoids algorithm. The transient power angle margin is quickly estimated for the faults of the transient power angle stability after classification. Finally, a severe contingency set consisting of the faults of the transient power angle instability and the estimated margin below the threshold is obtained. According to the clustering analysis of actual history data,the validity and practicability fo the proposed method can be verified.