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Title: Forecasting Dynamic Line Rating with Spatial Variation Considerations

Abstract

Dynamic line rating (DLR) is a technology that allows the ampacity of an electrical conductor to be calculated using real-time or forecasted weather conditions. Historically, the ampacity of a conductor has been determined using a static line rating method which assumes conservative weather assumptions. Therefore, not only can DLR give a more accurate measurement of the true ampacity of a conductor, but it can also increase its ampacity during weather conditions with greater thermal mitigations. The two primary cooling factors in the ampacity calculations are wind speed and direction. In complex terrain, wind speed and direction can have large variations over short distances. Therefore, accurately identifying the limiting span of a transmission line requires high spatial resolution of the wind along its path. One solution is to install dense weather stations along their path, though this can become costly over long distances. Therefore, researchers have investigated the use of Computation Fluid Dynamic (CFD) simulations to accurately compute the wind field along the path of a transmission line and use these results to identify the limiting section of the conductor. This work presents a case study that evaluates the coupling of CFD simulations and forecasted weather simulations using the High-Resolution Rapidmore » Refresh (HRRR) model points over a 2-year span within a region in south eastern Idaho. The primary goal of the work is the evaluation of the number of HRRR model points used, i.e., weather stations, along the path of the line and the accuracy of the resulting DLR ampacity. This was done using 4, 10, 17, 26, and 35 HRRR model points along two transmission line paths. The results indicate that as the number of model points are increased, the DLR ampacity of the lines decrease, yet converge as more points are added and demonstrate little change with additional HRRR points. It is expected that these results can help transmission line operators identify the number of weather stations that must be installed when coupled with CFD simulations and DLR ampacity to ensure accurate ratings and safe operations.« less

Authors:
ORCiD logo [1]; ORCiD logo [1];  [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Idaho National Laboratory
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:
1895360
Report Number(s):
INL/CON-21-64862-Rev000
DOE Contract Number:  
DE-AC07-05ID14517
Resource Type:
Conference
Resource Relation:
Conference: Grid of the Future, Providence, RI, 10/17/2021 - 10/20/2021
Country of Publication:
United States
Language:
English
Subject:
24 - POWER TRANSMISSION AND DISTRIBUTION; 17 - WIND ENERGY; Dynamic Line Rating; General Line Ampacity State Solver

Citation Formats

Phillips, Tyler Bennett, Abboud, Alexander W, Starks, Brandon Edward, Lehmer, Jacob P, and Gentle, Jake P. Forecasting Dynamic Line Rating with Spatial Variation Considerations. United States: N. p., 2021. Web.
Phillips, Tyler Bennett, Abboud, Alexander W, Starks, Brandon Edward, Lehmer, Jacob P, & Gentle, Jake P. Forecasting Dynamic Line Rating with Spatial Variation Considerations. United States.
Phillips, Tyler Bennett, Abboud, Alexander W, Starks, Brandon Edward, Lehmer, Jacob P, and Gentle, Jake P. 2021. "Forecasting Dynamic Line Rating with Spatial Variation Considerations". United States. https://www.osti.gov/servlets/purl/1895360.
@article{osti_1895360,
title = {Forecasting Dynamic Line Rating with Spatial Variation Considerations},
author = {Phillips, Tyler Bennett and Abboud, Alexander W and Starks, Brandon Edward and Lehmer, Jacob P and Gentle, Jake P},
abstractNote = {Dynamic line rating (DLR) is a technology that allows the ampacity of an electrical conductor to be calculated using real-time or forecasted weather conditions. Historically, the ampacity of a conductor has been determined using a static line rating method which assumes conservative weather assumptions. Therefore, not only can DLR give a more accurate measurement of the true ampacity of a conductor, but it can also increase its ampacity during weather conditions with greater thermal mitigations. The two primary cooling factors in the ampacity calculations are wind speed and direction. In complex terrain, wind speed and direction can have large variations over short distances. Therefore, accurately identifying the limiting span of a transmission line requires high spatial resolution of the wind along its path. One solution is to install dense weather stations along their path, though this can become costly over long distances. Therefore, researchers have investigated the use of Computation Fluid Dynamic (CFD) simulations to accurately compute the wind field along the path of a transmission line and use these results to identify the limiting section of the conductor. This work presents a case study that evaluates the coupling of CFD simulations and forecasted weather simulations using the High-Resolution Rapid Refresh (HRRR) model points over a 2-year span within a region in south eastern Idaho. The primary goal of the work is the evaluation of the number of HRRR model points used, i.e., weather stations, along the path of the line and the accuracy of the resulting DLR ampacity. This was done using 4, 10, 17, 26, and 35 HRRR model points along two transmission line paths. The results indicate that as the number of model points are increased, the DLR ampacity of the lines decrease, yet converge as more points are added and demonstrate little change with additional HRRR points. It is expected that these results can help transmission line operators identify the number of weather stations that must be installed when coupled with CFD simulations and DLR ampacity to ensure accurate ratings and safe operations.},
doi = {},
url = {https://www.osti.gov/biblio/1895360}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Dec 01 00:00:00 EST 2021},
month = {Wed Dec 01 00:00:00 EST 2021}
}

Conference:
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