2015
DOI: 10.1016/j.ijepes.2014.07.039
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An effective combined method for symmetrical faults identification during power swing

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Cited by 54 publications
(22 citation statements)
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“…When symmetrical fault occurs, there are no zero‐sequence and negative‐sequence components in the system; thus, it is difficult to distinguish between symmetrical fault and oscillation . This paper mainly focuses on the discrimination between symmetrical fault and oscillation.…”
Section: Theorymentioning
confidence: 99%
“…When symmetrical fault occurs, there are no zero‐sequence and negative‐sequence components in the system; thus, it is difficult to distinguish between symmetrical fault and oscillation . This paper mainly focuses on the discrimination between symmetrical fault and oscillation.…”
Section: Theorymentioning
confidence: 99%
“…Methods based on the derivative of the three-phase power, 14 the decaying dc component of the fault current, 15 the power differential technique, 16 and the fast Fourier transform coefficient of the active power 17 are proposed for detection of symmetrical faults. Methods based on advanced signal processing techniques such as S-transform and probabilistic neural network, 18 transient monitor function, 19 phase-space approach, 20 Fisher asymmetry coefficient, 21 and zerofrequency filtering 22 are proposed for fast detection of symmetrical faults.…”
Section: Introductionmentioning
confidence: 99%
“…The machine learning techniques are popular for classification of different power system events because of their high accuracy. Different intelligent tools such as adaptive neuro‐fuzzy interface system [21], neural network [22, 23], support vector machine (SVM) [24, 25], decision tree (DT) [26] and random forest (RF) [26] are applied to isolate faults from power swing. Features are extracted from the fault signals by different techniques for training these tools.…”
Section: Introductionmentioning
confidence: 99%