Adaptive soil model for real-time thermal rating of underground power cables

This study presents a validated adaptive method intended for real-time thermal rating (RTTR) of underground power cables. The accuracy of the RTTR algorithm, when producing emergency ratings or predictive calculations, strongly depends on the following parameters (which have large uncertainties): correct soil modelling, the proper determination of the soil properties and the accurate estimation of the ambient temperature. To remove the uncertainties, this study uses a novel approach to the modelling of the soil that allows the implementation of an extended Kalman filter to estimate robustly the properties of the soil and the ambient temperature in real-time with the data obtained from cable temperature sensors. These estimation techniques have been validated for several cable installations and the accuracy of emergency current calculations has been assessed by comparing the calculated results with finite element method simulations. In the context of smart grid applications, the possibility of adapting the estimation models in real time with the new obtained measurements is a key aspect to assure robustness and accuracy of the power system operation and control.