Enhancement of Anomalous Data Mining in Power System Predicting-Aided State Estimation

Shyh Jier Huang; Jeu Min Lin

doi:10.1109/TPWRS.2003.818726

Enhancement of Anomalous Data Mining in Power System Predicting-Aided State Estimation

Shyh Jier Huang
, Jeu Min Lin

電機工程學系

研究成果: Article › 同行評審

42 引文斯高帕斯（Scopus）

摘要

An approach for predicting-aided state estimation including bad data mining in a power system is proposed in this paper. In the method, the sliding surface-enhanced fuzzy control and optimal cluster numbers estimation techniques are both employed for the enhancement of state estimation. This proposed approach has been applied to test systems. Test results reveal the feasibility of the method for the applications considered.

原文	English
頁（從 - 到）	610-619
頁數	10
期刊	IEEE Transactions on Power Systems
卷	19
發行號	1
DOIs	https://doi.org/10.1109/TPWRS.2003.818726
出版狀態	Published - 2004 2月

All Science Journal Classification (ASJC) codes

能源工程與電力技術
電氣與電子工程

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10.1109/TPWRS.2003.818726

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AB - An approach for predicting-aided state estimation including bad data mining in a power system is proposed in this paper. In the method, the sliding surface-enhanced fuzzy control and optimal cluster numbers estimation techniques are both employed for the enhancement of state estimation. This proposed approach has been applied to test systems. Test results reveal the feasibility of the method for the applications considered.

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Enhancement of Anomalous Data Mining in Power System Predicting-Aided State Estimation

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