教師資料查詢 | 類別: 期刊論文 | 教師: 蘇木春 SU MU-CHUN (瀏覽個人網頁)

標題:Rule extraction for voltage security margin estimation
學年88
學期1
出版(發表)日期1999/12/01
作品名稱Rule extraction for voltage security margin estimation
作品名稱(其他語言)
著者蘇木春; Su, Mu-chun; Liu, Chih-wen; Chang, Chen-sung
單位淡江大學電機工程學系
出版者New York: Institute of Electrical and Electronics Engineers (IEEE)
著錄名稱、卷期、頁數IEEE Transactions on Industrial Electronics 46(6), pp.1114-1122
摘要Research efforts have been devoted to estimating voltage security margins which show how close the current operating point of a power system is to a voltage collapse point as assessment of voltage security. One main disadvantage of these techniques is that they require large computations, therefore, they are not efficient for on-line use in power control centers. In this paper, we propose a technique based on hyperrectangular composite neural networks (HRCNNs) and fuzzy hyperrectangular composite neural networks (FHRCNNs) for voltage security margin estimation. The technique provides us with much faster assessments of voltage security than conventional techniques. The two classes of HRCNNs and FHRCNNs integrate the paradigm of neural networks with the rule-based approach, rendering them more useful than either. The values of the network parameters, after sufficient training, can be utilized to generate crisp or fuzzy rules on the basis of preselected meaningful features. Extracted rules are helpful to explain the whole assessment procedure so the assessments are more capable of being trusted. In addition, the power system operators or corresponding experts can delete unimportant features or add some additional features to improve the performance and computational efficiency based on the evaluation of the extracted rules. The proposed technique was tested on 3000 simulated data randomly generated from operating conditions on the IEEE 30-bus system to indicate its high efficiency
關鍵字Fuzzy systems; neural networks; phasor measurement unit; power systems; voltage security
語言英文
ISSN0278-0046
期刊性質國際
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國別美國
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