TY - GEN
T1 - Low Voltage Series Arc Modelling Based on Neural Network Considering Harmonics Load Current
AU - Asfani, Dimas Anton
AU - Made Yulistya Negara, I.
AU - Gusti Ngurah Satriyadi Hernanda, I.
AU - Fahmi, Daniar
AU - Budiawan, Shafirah Khairina
AU - Syahril, Reynaldi
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/7/21
Y1 - 2021/7/21
N2 - Series Arc is one of the electrical fault types in a low voltage power system. Series arc occurred when two points of the same conductor connection have different potential values. It usually happens on a cable with broken insulation. Most people rarely notice the phenomenon of series arc because it may not be visible. When it happens continuously, the temperature around the arc location will increase and potentially cause a fire. The value of the series arc fault current has a similar value as the nominal current and causes protection devices such as circuit-breaker and fuse unable to detect it. Low voltage series arc modeling is necessary to enable protection devices in detecting series arc faults. This experiment conducts low voltage arc modeling on non-linear loads containing THDi values and several line impedance values. The modeling input is the arc voltage, arc current, and arc power before the series arc occurred, and the modeling target is the arc resistance. The modeling method is by using the artificial neural network with feed-forward backpropagation. The experiment shows that the higher the THDi values in the system, the higher the series arc fault current. The modeling results show that the modeling can represent the series arc fault resistance with an MSE value less than 0.04.
AB - Series Arc is one of the electrical fault types in a low voltage power system. Series arc occurred when two points of the same conductor connection have different potential values. It usually happens on a cable with broken insulation. Most people rarely notice the phenomenon of series arc because it may not be visible. When it happens continuously, the temperature around the arc location will increase and potentially cause a fire. The value of the series arc fault current has a similar value as the nominal current and causes protection devices such as circuit-breaker and fuse unable to detect it. Low voltage series arc modeling is necessary to enable protection devices in detecting series arc faults. This experiment conducts low voltage arc modeling on non-linear loads containing THDi values and several line impedance values. The modeling input is the arc voltage, arc current, and arc power before the series arc occurred, and the modeling target is the arc resistance. The modeling method is by using the artificial neural network with feed-forward backpropagation. The experiment shows that the higher the THDi values in the system, the higher the series arc fault current. The modeling results show that the modeling can represent the series arc fault resistance with an MSE value less than 0.04.
KW - Line Impedance
KW - Low Voltage
KW - Series Arc Faults
KW - THDi
KW - and Artificial Neural Network
UR - http://www.scopus.com/inward/record.url?scp=85114633397&partnerID=8YFLogxK
U2 - 10.1109/ISITIA52817.2021.9502236
DO - 10.1109/ISITIA52817.2021.9502236
M3 - Conference contribution
AN - SCOPUS:85114633397
T3 - Proceedings - 2021 International Seminar on Intelligent Technology and Its Application: Intelligent Systems for the New Normal Era, ISITIA 2021
SP - 293
EP - 298
BT - Proceedings - 2021 International Seminar on Intelligent Technology and Its Application
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 International Seminar on Intelligent Technology and Its Application, ISITIA 2021
Y2 - 21 July 2021 through 22 July 2021
ER -