Historical Data Analysis for Extending Dynamic Line Ratings Across Power Transmission Systems

Nicola Viafora; Jakob Glarbo Møller; Rasmus A. Olsen; Anders S. Kristensen; Joachim Holbøll

doi:10.1109/PMAPS.2018.8440449

Historical Data Analysis for Extending Dynamic Line Ratings Across Power Transmission Systems

Nicola Viafora, Jakob Glarbo Møller, Rasmus A. Olsen, Anders S. Kristensen, Joachim Holbøll

Energinet.dk

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

Dynamic Line Rating (DLR) consists in an innovative way to operate power systems, which allows for higher power flows on transmission lines depending on weather conditions. Extending the application of DLR technology from one to numerous lines across a larger transmission power system presents challenges with respect to the scalability due to the large amount of data required. Firstly, a modified overhead line thermal model and the use of historical weather data are considered in this paper to preliminary assess the margin for increased rating of transmission lines. Secondly, spatial correlation of line ratings are analyzed and a comparison of various rating approaches, which rely on different combinations of weather variables, is presented. The resulting probability distributions of line ratings are compared with constant seasonal ratings highlighting the trade-off between those solutions that yield a large increase in rating at a cost of high volatility, against simpler approaches which are more conservative and require less information. The results reported are based on actual data of the western section of the Danish power transmission system.

Original language	English
Title of host publication	2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)
Number of pages	6
Publisher	IEEE
Publication date	2018
Pages	1-6
ISBN (Electronic)	978-1-5386-3596-4
DOIs	https://doi.org/10.1109/PMAPS.2018.8440449
Publication status	Published - 2018
Event	2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems - Boise, United States Duration: 24 Jun 2018 → 28 Jun 2018 https://ieeexplore.ieee.org/xpl/conhome/8422007/proceeding

Conference

Conference	2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems
Country/Territory	United States
City	Boise
Period	24/06/2018 → 28/06/2018
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8422007/proceeding

Keywords

Dynamic line rating
Historical weather data
Correlation
Overhead lines
Thermal model

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10.1109/PMAPS.2018.8440449

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Cite this

@inproceedings{ccfd2b8b3dc74af093af6fe9a5bf5ed0,

title = "Historical Data Analysis for Extending Dynamic Line Ratings Across Power Transmission Systems",

abstract = "Dynamic Line Rating (DLR) consists in an innovative way to operate power systems, which allows for higher power flows on transmission lines depending on weather conditions. Extending the application of DLR technology from one to numerous lines across a larger transmission power system presents challenges with respect to the scalability due to the large amount of data required. Firstly, a modified overhead line thermal model and the use of historical weather data are considered in this paper to preliminary assess the margin for increased rating of transmission lines. Secondly, spatial correlation of line ratings are analyzed and a comparison of various rating approaches, which rely on different combinations of weather variables, is presented. The resulting probability distributions of line ratings are compared with constant seasonal ratings highlighting the trade-off between those solutions that yield a large increase in rating at a cost of high volatility, against simpler approaches which are more conservative and require less information. The results reported are based on actual data of the western section of the Danish power transmission system.",

keywords = "Dynamic line rating, Historical weather data, Correlation, Overhead lines, Thermal model",

author = "Nicola Viafora and M{\o}ller, {Jakob Glarbo} and Olsen, {Rasmus A.} and Kristensen, {Anders S.} and Joachim Holb{\o}ll",

year = "2018",

doi = "10.1109/PMAPS.2018.8440449",

language = "English",

pages = "1--6",

booktitle = "2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)",

publisher = "IEEE",

address = "United States",

note = "2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018 ; Conference date: 24-06-2018 Through 28-06-2018",

url = "https://ieeexplore.ieee.org/xpl/conhome/8422007/proceeding",

}

Viafora, N, Møller, JG, Olsen, RA, Kristensen, AS & Holbøll, J 2018, Historical Data Analysis for Extending Dynamic Line Ratings Across Power Transmission Systems. in 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, pp. 1-6, 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems, Boise, Indiana, United States, 24/06/2018. https://doi.org/10.1109/PMAPS.2018.8440449

Historical Data Analysis for Extending Dynamic Line Ratings Across Power Transmission Systems. / Viafora, Nicola; Møller, Jakob Glarbo; Olsen, Rasmus A. et al.
2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, 2018. p. 1-6.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

TY - GEN

T1 - Historical Data Analysis for Extending Dynamic Line Ratings Across Power Transmission Systems

AU - Viafora, Nicola

AU - Møller, Jakob Glarbo

AU - Olsen, Rasmus A.

AU - Kristensen, Anders S.

AU - Holbøll, Joachim

PY - 2018

Y1 - 2018

N2 - Dynamic Line Rating (DLR) consists in an innovative way to operate power systems, which allows for higher power flows on transmission lines depending on weather conditions. Extending the application of DLR technology from one to numerous lines across a larger transmission power system presents challenges with respect to the scalability due to the large amount of data required. Firstly, a modified overhead line thermal model and the use of historical weather data are considered in this paper to preliminary assess the margin for increased rating of transmission lines. Secondly, spatial correlation of line ratings are analyzed and a comparison of various rating approaches, which rely on different combinations of weather variables, is presented. The resulting probability distributions of line ratings are compared with constant seasonal ratings highlighting the trade-off between those solutions that yield a large increase in rating at a cost of high volatility, against simpler approaches which are more conservative and require less information. The results reported are based on actual data of the western section of the Danish power transmission system.

AB - Dynamic Line Rating (DLR) consists in an innovative way to operate power systems, which allows for higher power flows on transmission lines depending on weather conditions. Extending the application of DLR technology from one to numerous lines across a larger transmission power system presents challenges with respect to the scalability due to the large amount of data required. Firstly, a modified overhead line thermal model and the use of historical weather data are considered in this paper to preliminary assess the margin for increased rating of transmission lines. Secondly, spatial correlation of line ratings are analyzed and a comparison of various rating approaches, which rely on different combinations of weather variables, is presented. The resulting probability distributions of line ratings are compared with constant seasonal ratings highlighting the trade-off between those solutions that yield a large increase in rating at a cost of high volatility, against simpler approaches which are more conservative and require less information. The results reported are based on actual data of the western section of the Danish power transmission system.

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KW - Historical weather data

KW - Correlation

KW - Overhead lines

KW - Thermal model

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T2 - 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems

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ER -

Historical Data Analysis for Extending Dynamic Line Ratings Across Power Transmission Systems

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Keywords

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