基于数据挖掘技术的负荷曲线对故障反应相似性的研究

各种故障都对电力系统负荷的变化有显著影响,深入地理解和掌握这些影响是十分有益的。文中把数据挖掘技术应用于CLP(Chinese Lighting Power)公司的数据库,分析了在故障影响下母线负荷曲线的聚类,获得了与CLP系统中的特定变电站AAA母线具有相似负荷变化曲线的母线组或区域,从而可以更好地估计和抑制未来故障对这些负荷所造成的损失(例如对它们采取一致的策略等),有利于系统的安全稳定运行。

Study on Similarity of Load Profiles Following Disturbances Based on Data Mining

Various disturbances including faults have conspicuous influence on variations of system load. It is very useful to acquire better understanding of the influence. This paper applies data-mining techniques to the CLP Power database to analyze the cluster of load profiles in various buses in response to disturbances. The bus group or region, whose load profiles are very similar with that of the special station (station AAA) at CLP system are achieved. Therefore, it could be more accurately to assess and reduce the loss and influence to these loads resulted from the future disturbance (such as adopting same measure or strategy to prevent or deal with the disturbance for these loads), which is very helpful to enhance the security and stability operation of power system.