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High impedance fault detection and identification based on pattern recognition of phase displacement computation
Author(s) -
Ali Mohd Syukri,
Abu Bakar Ab Halim,
Tan Chia Kwang,
Arof Hamzah,
Mokhlis Hazlie
Publication year - 2018
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.22600
Subject(s) - computation , fault (geology) , identification (biology) , displacement (psychology) , electrical impedance , event (particle physics) , pattern recognition (psychology) , three phase , voltage , feature (linguistics) , computer science , phase (matter) , capacitor , fault detection and isolation , engineering , algorithm , artificial intelligence , electronic engineering , electrical engineering , physics , botany , psychology , quantum mechanics , seismology , actuator , psychotherapist , biology , geology , linguistics , philosophy
This paper proposes a new algorithm for high‐impedance‐fault (HIF) detection based on phase displacement computation (PDC). The PDC is calculated between the measured and reference three‐phase voltage signals. There are two stages in this algorithm. In the first stage, the pattern of the PDC is analyzed to detect the occurrence of an event. In the second stage, the peak of the PDC is used as a feature to distinguish between HIF and non‐HIF events. Subsequently, an automatic HIF classification algorithm based on predefined indices is proposed to perform event identification and HIF detection. Different types of HIF events and non‐HIF events, such as load switching, motor starting, and capacitor switching, have been simulated in PSCAD/EMTDC. The proposed algorithm is able to classify the events accurately for both single and multiple events occurrence. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.