Pregled bibliografske jedinice broj: 1278705
Artificial Neural Network for High-Impedance-Fault Detection in DC Microgrids
Artificial Neural Network for High-Impedance-Fault Detection in DC Microgrids // 2023 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East)
Abu Dhabi, Ujedinjeni Arapski Emirati: Institute of Electrical and Electronics Engineers (IEEE), 2023. str. 1-5 doi:10.1109/isgtmiddleeast56437.2023.10078693 (poster, međunarodna recenzija, sažetak, znanstveni)
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Naslov
Artificial Neural Network for High-Impedance-Fault
Detection in DC Microgrids
Autori
Grcić, Ivan ; Pandžić, Hrvoje
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Skup
2023 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East)
Mjesto i datum
Abu Dhabi, Ujedinjeni Arapski Emirati, 12.03.2023. - 15.03.2023
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
DC microgrid ; fault detection ; recurrent neural network ; high-impedance fault
Sažetak
In this paper, we present a novel method for detect-ing high-impedance faults (HIFs) in DC microgrids. HIFs are more difficult to detect than other types of faults because their voltage and current values are not significantly different from those under normal operating conditions. We propose a recurrent neural network (RNN)-based method that can detect events from the temporal behaviour of a current signal, including HIFs and load changes. The method proves to be accurate, distinguishing between HIFs and other waveforms with a high score above 95% on accuracy and Fl- score metrics.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
