Fast Fault Location Method for a Distribution System with High Penetration of PV Jimenez Aparicio, Miguel Grijalva, Santiago Reno, Matt 2020-12-24T19:39:27Z 2020-12-24T19:39:27Z 2021-01-05
dc.description.abstract Distribution 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.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2021.390
dc.identifier.isbn 978-0-9981331-4-0
dc.language.iso English
dc.relation.ispartof Proceedings of the 54th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Monitoring, Control and Protection
dc.subject continuous wavelet transform (cwt)
dc.subject convolutional neural network (cnn)
dc.subject fault location
dc.subject photovoltaic (pv) system
dc.subject traveling waves
dc.title Fast Fault Location Method for a Distribution System with High Penetration of PV
prism.startingpage 3205
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