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

Marc Diaz-Aguiló, Francisco de León

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)654-660
Number of pages7
JournalIET Science, Measurement and Technology
Issue number6
StatePublished - Sep 1 2015

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering


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