基于数据挖掘技术的电力系统暂态稳定预测

Power system transient stability prediction based on data mining

提出了相量测量装置历史数据挖掘方案,以暂态稳定监测为例,建立了一套数据挖掘流程。利用各种数据源建立了暂态稳定监测数据集市,该集市不仅便于联机分析处理,同时还可利用其建立多种数据挖掘模型,获取更多的暂态稳定知识。在6机22节点系统中的应用结果证明了该方法对电力系统暂态稳定监测的有效性。

This paper presents a data mining framework for the historical data of PMUs. Taking example for transient stability monitor, this paper establishes a data mining flow. The data market of transient stability monitor is built up by all kinds of data sources. The data market is convenient for online analytical processing. The test system that includes 6 machines and 22 nodes is employed to demonstrate the validity of the proposed approach. <