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Identification of Catastrophic Failures in Power System Using Pattern Recognition and Fuzzy Estimation

机译:基于模式识别和模糊估计的电力系统灾难性故障识别

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摘要

This paper presents a new approach for finding the sequence of events that may lead to catastrophic failure in a power system. The probable sequences (of events) leading to catastrophic failures are identified using risk indices which incorporate the severity as well as the probability of the contingencies. Probable collapse sequences are identified offline for different possible loading conditions using a modified fast decoupled load flow method which considers the voltage and frequency dependence of loads and generator regulation characteristics and stored in a knowledge base. Pattern recognition method and fuzzy estimation are used for online identification of collapse sequences for any operating condition from the stored database (knowledge base).
机译:本文提出了一种新的方法来查找可能导致电力系统灾难性故障的事件序列。导致灾难性故障的(事件的)可能顺序是使用风险指数来识别的,该风险指数包括了严重性和突发事件的概率。使用修改后的快速解耦潮流方法,离线考虑不同负载条件下可能的坍塌序列,该方法考虑了负载的电压和频率依赖性以及发电机调节特性,并存储在知识库中。模式识别方法和模糊估计用于从存储的数据库(知识库)针对任何运行条件在线识别坍塌序列。

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