CHEN She, WANG Juan, ZENG Zeyu, et al. Research on High Voltage Cable Core Temperature Prediction Based on Data Driven Model[J]. 2022, 42(2): 59-63+67.
CHEN She, WANG Juan, ZENG Zeyu, et al. Research on High Voltage Cable Core Temperature Prediction Based on Data Driven Model[J]. 2022, 42(2): 59-63+67.DOI:
Temperature is one of the important physical quantities to determine the operating status of the cable
but usually only the temperature of the outer sheath can be monitored
while the temperature of the cable core cannot be directly obtained. In this study
a temperature field model of tunnel laying 110 kV cable is built
incorporating the real-time monitoring temperature of the cable outer sheath. The cable temperature distribution is thus obtained by optimizing and correcting the physical quantities such as material parameters of the cable to make the model more consistent with the real operation state. The influences of parameters such as dielectric loss factor
dielectric constant and thermal conductivity of XLPE on the physical model of cable temperature prediction are further discussed. The temperature distribution of low resistance grounding fault in cable is simulated. It was found that the difference between the fault phase cable core temperature and its outer sheath temperature was 47 ℃
and this cable core temperature can reach 250 ℃
and meanwhile
the temperature of the same circuit non-fault phase cable core also rose to more than 120 ℃
which was in severe overload state. The data-driven high voltage cable model in this paper can effectively calculate the cable core temperature
which helps to grasp the core data and working status of cable operation
so that it can lay the foundation for the final construction of the cable digital twin model.