电力系统自动化2017，Vol.41Issue(18)：137-145,9.DOI:10.7500/AEPS20161228011
基于高风险模式树挖掘方法的电力系统风险设备集分析
High Risk Tree Mining Method for Analysis of Power System Risk Device Set
摘要
Abstract
The rapid accumulation of big data in the power grid dispatching and control system provides a sufficient condition for the risk analysis of power grid equipment.Based on the analysis of characteristics of big data in the dispatching and control system,a universal analysis framework of big data in power dispatching and control system is built,and on basis of the application of risk management and control in power grid,a data mining method for high risk equipment based on high risk tree (HRT) is proposed.From the perspective of multiple factor analysis of equipment risk,considering impact of equipment importance and equipment hidden danger on equipment risk,equipment risk influence degree is defined,equipment importance indicators and equipment hidden danger indicators are proposed.The equipment risk value as the target of mining high risk equipment,the construction of HRT retaining the original database of equipment risk value and equipment risk prior knowledge information is for mining high risk equipment set,specifically the high risk equipment risk set meeting the threshold will be obtained according to the HRT path information.Finally,the proposed method is simulated based on massive historical alarm data in dispatching and control system.The simulation results show that HRT can quickly deal with the alarm data to get high risk equipment set meeting the conditions,and it can reflect the potential association between high risk equipment,so it will provide reference for the follow-up of power grid risk management and control.关键词
大数据/数据挖掘/风险影响度/高风险模式树(HRT)Key words
big data/data mining/risk influence degree/high risk tree引用本文复制引用
吴润泽,陈文伟,唐良瑞,范军丽..基于高风险模式树挖掘方法的电力系统风险设备集分析[J].电力系统自动化,2017,41(18):137-145,9.基金项目
This work is supported by National Natural Science Foundation of China (No.51507063) and State Grid Corporation of China (No.B34681150152).国家自然科学基金资助项目(51507063) （No.51507063）
国家电网公司科技项目(B34681150152). （B34681150152）
