摘要
现有电力系统警报处理方法完全没有利用或没有充分利用警报的时序特性。在人工智能研究领域发展起来的时序约束网络是一种能够清晰而直观地表示时序逻辑的有向无环图,适于解决计及警报信息时序特性的警报处理问题。在此背景下,构建了充分利用时序信息的警报处理解析模型。该模型不仅能够分析导致警报产生的具体事件以及该事件所在的时间区间,而且可以识别异常或遗漏的警报。基于时序约束网络中时间点和时间距离约束等相关概念,研究了事件发生时间的不确定性问题,避免了现有的计及时序特性的模型必须对时间精确定义的缺点。最后,用实际电力系统的警报处理案例对所提出的模型和方法进行了说明。
Up to now, temporal information of alarms has not yet been fully utilized in existing alarm processing methods. The temporal constraint network is a kind of directed acyclic graph （DAG）, and could well represent temporal logics. Given this background, an analytic model for alarm processing with temporal information taken into account is developed. The model could not only find out the events causing the reported alarms together with the time domain concerned, but also identify abnormal and missing alarms. The concepts of the time-point and time-distance constraints in the temporal constraint network provide a path for describing the uncertainty of the event occurrences, and hence precise timing is no longer required as in the existing alarm processing models accommodating temporal information. Finally, an actual power system is served for demonstrating the feasibility and efficiency of the proposed model and method.
出处
《电力系统自动化》
EI
CSCD
北大核心
2009年第21期36-42,65,共8页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(50477029)~~
关键词
警报处理
时序信息
解析模型
时序约束网
电力系统
alarm processing
temporal information
analytic model
temporal constraint network
power system
