Fast Fault Location Method for a Distribution System with High Penetration of PV

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dc.contributor.authorJimenez Aparicio, Miguel
dc.contributor.authorGrijalva, Santiago
dc.contributor.authorReno, Matt
dc.date.accessioned2020-12-24T19:39:27Z
dc.date.available2020-12-24T19:39:27Z
dc.date.issued2021-01-05
dc.description.abstractDistribution systems with high levels of solar PV may experience notable changes due to external conditions, such as temperature or solar irradiation. Fault detection methods must be developed in order to support these changes of conditions. This paper develops a method for fast detection, location, and classification of faults in a system with a high level of solar PV. The method uses the Continuous Wavelet Transform (CWT) technique to detect the traveling waves produced by fault events. The CWT coefficients of the current waveform at the traveling wave arrival time provide a fingerprint that is characteristic of each fault type and location. Two Convolutional Neural Networks are trained to classify any new fault event. The method relays of several protection devices and doesn’t require communication between them. The results show that for multiple fault scenarios and solar PV conditions, high accuracy for both location and type classification can be obtained.
dc.format.extent9 pages
dc.identifier.doi10.24251/HICSS.2021.390
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/71005
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectMonitoring, Control and Protection
dc.subjectcontinuous wavelet transform (cwt)
dc.subjectconvolutional neural network (cnn)
dc.subjectfault location
dc.subjectphotovoltaic (pv) system
dc.subjecttraveling waves
dc.titleFast Fault Location Method for a Distribution System with High Penetration of PV
prism.startingpage3205

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