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

Marc Diaz-Aguiló, Francisco De Leon

Research output: Contribution to journalArticle

Abstract

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
Volume9
Issue number6
DOIs
StatePublished - Sep 1 2015

Fingerprint

ratings
cables
soils
Cables
Soils
emergencies
ambient temperature
Extended Kalman filters
Kalman filters
temperature sensors
Temperature sensors
installing
finite element method
grids
Finite element method
Temperature
Hot Temperature
estimates
simulation
Uncertainty

ASJC Scopus subject areas

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

Cite this

Adaptive soil model for real-time thermal rating of underground power cables. / Diaz-Aguiló, Marc; De Leon, Francisco.

In: IET Science, Measurement and Technology, Vol. 9, No. 6, 01.09.2015, p. 654-660.

Research output: Contribution to journalArticle

@article{2b97cafb43074edbb80ab721d1a84e48,
title = "Adaptive soil model for real-time thermal rating of underground power cables",
abstract = "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.",
author = "Marc Diaz-Aguil{\'o} and {De Leon}, Francisco",
year = "2015",
month = "9",
day = "1",
doi = "10.1049/iet-smt.2014.0269",
language = "English (US)",
volume = "9",
pages = "654--660",
journal = "IET Science, Measurement and Technology",
issn = "1751-8822",
publisher = "Institution of Engineering and Technology",
number = "6",

}

TY - JOUR

T1 - Adaptive soil model for real-time thermal rating of underground power cables

AU - Diaz-Aguiló, Marc

AU - De Leon, Francisco

PY - 2015/9/1

Y1 - 2015/9/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84940869294&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84940869294&partnerID=8YFLogxK

U2 - 10.1049/iet-smt.2014.0269

DO - 10.1049/iet-smt.2014.0269

M3 - Article

VL - 9

SP - 654

EP - 660

JO - IET Science, Measurement and Technology

JF - IET Science, Measurement and Technology

SN - 1751-8822

IS - 6

ER -