TY - JOUR
T1 - Modeling of high-temperature superconducting cable via time domain reflectometry and general regression neural network
AU - Kwon, Gu Young
AU - Bang, Su Sik
AU - Lee, Yeong Ho
AU - Lee, Geon Seok
AU - Shin, Yong June
N1 - Publisher Copyright:
© 2002-2011 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - When a fault occurs in the high-temperature superconducting (HTS) cable, a fault current consisting of extremely high frequency components is generated and propagated based on the transient response of the HTS cable. Therefore, a simulation model based on high frequency characteristic of the HTS cable is essential to obtain accurate simulation results in the transient fault analysis. In this paper, the result of time domain reflectometry is used to design the model of the HTS cable. To determine model parameters, a general regression neural network based on the kernel density estimation is utilized. After the modeling procedure, the accuracy of the model is evaluated by time-frequency domain reflectometry, whose response depends on the high frequency characteristic of the cable. It is expected that the proposed modeling method can be applied to various application area of HTS cable, such as fault analysis, protection, and diagnostics in the future.
AB - When a fault occurs in the high-temperature superconducting (HTS) cable, a fault current consisting of extremely high frequency components is generated and propagated based on the transient response of the HTS cable. Therefore, a simulation model based on high frequency characteristic of the HTS cable is essential to obtain accurate simulation results in the transient fault analysis. In this paper, the result of time domain reflectometry is used to design the model of the HTS cable. To determine model parameters, a general regression neural network based on the kernel density estimation is utilized. After the modeling procedure, the accuracy of the model is evaluated by time-frequency domain reflectometry, whose response depends on the high frequency characteristic of the cable. It is expected that the proposed modeling method can be applied to various application area of HTS cable, such as fault analysis, protection, and diagnostics in the future.
KW - Cable modeling
KW - general regression neural network (GRNN)
KW - high-temperature superconducting (HTS) cable
KW - time domain reflectometry
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U2 - 10.1109/TASC.2019.2898885
DO - 10.1109/TASC.2019.2898885
M3 - Article
AN - SCOPUS:85063216672
SN - 1051-8223
VL - 29
JO - IEEE Transactions on Applied Superconductivity
JF - IEEE Transactions on Applied Superconductivity
IS - 5
M1 - 8641370
ER -