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Learning to recognize vulnerable patterns due to undesirable Zone‐3 relay operations
Author(s) -
Yamashita Koji,
Li Juan,
Liu ChenChing,
Zhang Pei,
Hofmann Michael
Publication year - 2009
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.20413
Subject(s) - relay , line (geometry) , electrical impedance , time domain , domain (mathematical analysis) , state (computer science) , steady state (chemistry) , computer science , reliability engineering , engineering , control theory (sociology) , electrical engineering , mathematics , algorithm , artificial intelligence , physics , power (physics) , mathematical analysis , chemistry , geometry , control (management) , quantum mechanics , computer vision
Undesirable zone 3 relay operations caused by unexpected loading conditions can contribute to the cascaded events, leading to catastrophic outages. Identifying the basic patterns of zone 3 relay operations in advance is an effective way to help prevent cascaded events. The postcontingency impedances seen by zone 3 relays can be calculated on line in a steady state security assessment framework. However, their accuracy is inadequate compared with the postcontingency apparent impedance obtained from off‐line time domain dynamic simulations. This paper proposes a fuzzy inference system (FIS) to correct discrepancies between the postcontingency apparent impedances obtained from the results of steady state security assessment and the corresponding values obtained by time‐domain simulations. The postcontingency apparent impedances obtained from the results of steady state security assessment can be corrected on line using correction terms provided by the FIS. The dynamic model of a 200‐bus system is used to validate the performance of the proposed FIS. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.