摘要
以地区电网的变电站自动化系统为研究对象,提出基于远程的变电站自动化智能数据挖掘体系。应用数据挖掘技术对原始告警数据进行分类、标准化处理,并与设备台账系统关联,得到设备参数、状态信息以及相关历史故障信息的数据仓库;在此基础上,采用改进Apriori算法从数据仓库中提取出满足最小信任度阈值的强关联规则,为变电站设备运行维护管理提供决策依据;通过现场案例验证了所提出的数据挖掘方法的有效性。
Taking substation automation system in regional power grid as study object,this paper proposes automation intelli-gent data mining system based on long-distance.Applying data mining technology to proceed classification and standardiza-tion handling for original warning data and by associating with equipment parameter system,it acquires equipment parame-ters,state information and data warehouse of correlated historical fault information.On the basis of the above study,it uses improved Apriori algorithm to attract strong association rules which is able to satisfy minimum trust threshold in the data warehouse in order to provide decision-making basis for equipment operational maintenance and management of the substa-tion.By on-scene examples,it verifies effectiveness of the proposes data mining method.
出处
《广东电力》
2014年第3期73-79,共7页
Guangdong Electric Power
基金
国家自然科学基金资助项目(51077056)
