High impedance fault detection in power distribution networks using time–frequency transform and probabilistic neural network
- 1 January 2008
- journal article
- Published by Institution of Engineering and Technology (IET) in IET Generation, Transmission & Distribution
- Vol. 2 (2), 261-270
- https://doi.org/10.1049/iet-gtd:20070319
Abstract
An intelligent approach for high impedance fault (HIF) detection in power distribution feeders using advanced signal-processing techniques such as time–time and time–frequency transforms combined with neural network is presented. As the detection of HIFs is generally difficult by the conventional over-current relays, both time and frequency information are required to be extracted to detect and classify HIF from no fault (NF). In the proposed approach, S- and TT-transforms are used to extract time–frequency and time–time distributions of the HIF and NF signals, respectively. The features extracted using S- and TT-transforms are used to train and test the probabilistic neural network (PNN) for an accurate classification of HIF from NF. A qualitative comparison is made between the HIF classification results obtained from feed forward neural network and PNN with same features as inputs. As the combined signal-processing techniques and PNN take one cycle for HIF identification from the fault inception, the proposed approach was found to be the most suitable for HIF classification in power distribution networks with wide variations in operating conditions.Keywords
This publication has 16 references indexed in Scilit:
- The S‐transform with windows of arbitrary and varying shapeGeophysics, 2003
- A de-noising scheme for enhancing wavelet-based power quality monitoring systemIEEE Transactions on Power Delivery, 2001
- Fuzzy detection of high impedance faults in radial distribution feedersElectric Power Systems Research, 1999
- Characteristics of earth faults in electrical distribution networks with high impedance earthingElectric Power Systems Research, 1998
- Localization of the complex spectrum: the S transformIEEE Transactions on Signal Processing, 1996
- Detecting arcing downed-wires using fault current flicker and half-cycle asymmetryIEEE Transactions on Power Delivery, 1994
- Detection of high impedance arcing faults using a multi-layer perceptronIEEE Transactions on Power Delivery, 1992
- A digital signal processing algorithm for detecting arcing faults on power distribution feedersIEEE Transactions on Power Delivery, 1989
- Behaviour of low frequency spectra during arcing fault and switching eventsIEEE Transactions on Power Delivery, 1988
- Detection of Distribution High Impedance Faults Using Burst Noise Signals near 60 HZIEEE Transactions on Power Delivery, 1987