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Title: Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings

Abstract

This study looks at forecasted dynamic line ratings in southern Idaho by using data from the High Resolution Rapid Refresh (HRRR) model for forecasted weather conditions. The HRRR model can provide accurate 18- hour forecasts with a 15-minute temporal resolution. Typical static ratings used for over head transmission lines use overly conservative assumptions for local weather conditions, such as using the maximum solar irradiance or temperature measured during the summer combined with low wind speed for an entire season. The HRRR forecast model used here has a high spatial resolution to provide local forecast conditions along the entire length of a transmission line. The area that is of interest in this study is in southern Idaho spanning a total of 15,000 square kilometers. The forecasted weather data is coupled with a computational fluid dynamics model of the wind in the region to improve the resolution to an even finer scale for resolving local convective cooling rates on each individual transmission line midpoint span. This high fidelity approach can be used to find the minimum ampacity limit across all given midpoints of a transmission line to determine the absolute minimum to be used for the line rating. The ability to increasemore » the line rating above the conservative static approach with the forecasted weather data provides a large potential to alleviate congestion and provide data for the utility market transactions. Furthermore, this study shows that for the region of interest, using forecasted weather data coupled with CFD modeling will calculate DLR ampacity rating above static about 90% of the time, with only a small relative error in the forecasted ampacity over time.« less

Authors:
 [1];  [2]; ORCiD logo [1];  [1]; ORCiD logo [1]; ORCiD logo [1];  [1];  [2];  [3]
  1. Idaho National Lab. (INL), Idaho Falls, ID (United States)
  2. National Oceanic and Atmospheric Administration – Cooperative Institute for Research in the Atmosphere, Boulder, CO (United States)
  3. National Oceanic and Atmospheric Administration – Cooperative Institute for Research in the Environmental Sciences, Boulder, CO (United States)
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1498106
Report Number(s):
INL/JOU-18-51685-Rev000
Journal ID: ISSN 0378-7796
Grant/Contract Number:  
AC07-05ID14517
Resource Type:
Accepted Manuscript
Journal Name:
Electric Power Systems Research
Additional Journal Information:
Journal Volume: 170; Journal Issue: C; Journal ID: ISSN 0378-7796
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; Dynamic line rating; Computational fluid dynamics; Weather forecasting; Overhead transmission lines; High resolution rapid refresh

Citation Formats

Abboud, Alexander W., Fenton, Kenneth R., Lehmer, Jacob P., Fehringer, Benjamin A., Gentle, Jake P., McJunkin, Timothy R., Le Blanc, Katya L., Petty, Melissa A., and Wandishin, Matthew S. Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings. United States: N. p., 2019. Web. doi:10.1016/j.epsr.2019.01.035.
Abboud, Alexander W., Fenton, Kenneth R., Lehmer, Jacob P., Fehringer, Benjamin A., Gentle, Jake P., McJunkin, Timothy R., Le Blanc, Katya L., Petty, Melissa A., & Wandishin, Matthew S. Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings. United States. doi:10.1016/j.epsr.2019.01.035.
Abboud, Alexander W., Fenton, Kenneth R., Lehmer, Jacob P., Fehringer, Benjamin A., Gentle, Jake P., McJunkin, Timothy R., Le Blanc, Katya L., Petty, Melissa A., and Wandishin, Matthew S. Fri . "Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings". United States. doi:10.1016/j.epsr.2019.01.035.
@article{osti_1498106,
title = {Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings},
author = {Abboud, Alexander W. and Fenton, Kenneth R. and Lehmer, Jacob P. and Fehringer, Benjamin A. and Gentle, Jake P. and McJunkin, Timothy R. and Le Blanc, Katya L. and Petty, Melissa A. and Wandishin, Matthew S.},
abstractNote = {This study looks at forecasted dynamic line ratings in southern Idaho by using data from the High Resolution Rapid Refresh (HRRR) model for forecasted weather conditions. The HRRR model can provide accurate 18- hour forecasts with a 15-minute temporal resolution. Typical static ratings used for over head transmission lines use overly conservative assumptions for local weather conditions, such as using the maximum solar irradiance or temperature measured during the summer combined with low wind speed for an entire season. The HRRR forecast model used here has a high spatial resolution to provide local forecast conditions along the entire length of a transmission line. The area that is of interest in this study is in southern Idaho spanning a total of 15,000 square kilometers. The forecasted weather data is coupled with a computational fluid dynamics model of the wind in the region to improve the resolution to an even finer scale for resolving local convective cooling rates on each individual transmission line midpoint span. This high fidelity approach can be used to find the minimum ampacity limit across all given midpoints of a transmission line to determine the absolute minimum to be used for the line rating. The ability to increase the line rating above the conservative static approach with the forecasted weather data provides a large potential to alleviate congestion and provide data for the utility market transactions. Furthermore, this study shows that for the region of interest, using forecasted weather data coupled with CFD modeling will calculate DLR ampacity rating above static about 90% of the time, with only a small relative error in the forecasted ampacity over time.},
doi = {10.1016/j.epsr.2019.01.035},
journal = {Electric Power Systems Research},
number = C,
volume = 170,
place = {United States},
year = {2019},
month = {2}
}

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