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Title: Operational and Strategic Implementation of Dynamic Line Rating for Optimized Wind Energy Generation Integration

Abstract

One primary goal of rendering today’s transmission grid “smarter” is to optimize and better manage its power transfer capacity in real time. Power transfer capacity is affected by three main elements: stability, voltage limits, and thermal ratings. All three are critical, but thermal ratings represent the greatest opportunity to quickly, reliably and economically utilize the grid’s true capacity. With the “Smarter Grid”, new solutions have been sought to give operators a better grasp on real time conditions, allowing them to manage and extend the usefulness of existing transmission infrastructure in a safe and reliable manner. The objective of the INL Wind Program is to provide industry a Dynamic Line Rating (DLR) solution that is state of the art as measured by cost, accuracy and dependability, to enable human operators to make informed decisions and take appropriate actions without human or system overloading and impacting the reliability of the grid. In addition to mitigating transmission line congestion to better integrate wind, DLR also offers the opportunity to improve the grid with optimized utilization of transmission lines to relieve congestion in general. As wind-generated energy has become a bigger part of the nation’s energy portfolio, researchers have learned that wind not onlymore » turns turbine blades to generate electricity, but can cool transmission lines and increase transfer capabilities significantly, sometimes up to 60 percent. INL’s DLR development supports EERE and The Wind Energy Technology Office’s goals by informing system planners and grid operators of available transmission capacity, beyond typical Static Line Ratings (SLR). SLRs are based on a fixed set of conservative environmental conditions to establish a limit on the amount of current lines can safely carry without overheating. Using commercially available weather monitors mounted on industry informed custom brackets developed by INL in combination with Computational Fluid Dynamics (CFD) enhanced weather analysis and DLR software, INL’s project offers the potential of safely providing line ampacities up to 40 percent or more above existing SLRs, by using real time information rather than overly conservative SLR.« less

Authors:
 [1]
  1. Idaho National Lab. (INL), Idaho Falls, ID (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:
1364098
Report Number(s):
INL/EXT-16-40751
TRN: US1702282
DOE Contract Number:  
AC07-05ID14517
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; 17 WIND ENERGY; WIND; POWER TRANSMISSION LINES; TURBINES; SMART GRIDS; WEATHER; MONITORS; TURBINE BLADES; ELECTRICITY; WIND POWER; Dynamic Line Rating; EERE Peer Review

Citation Formats

Gentle, Jake Paul. Operational and Strategic Implementation of Dynamic Line Rating for Optimized Wind Energy Generation Integration. United States: N. p., 2016. Web. doi:10.2172/1364098.
Gentle, Jake Paul. Operational and Strategic Implementation of Dynamic Line Rating for Optimized Wind Energy Generation Integration. United States. https://doi.org/10.2172/1364098
Gentle, Jake Paul. Thu . "Operational and Strategic Implementation of Dynamic Line Rating for Optimized Wind Energy Generation Integration". United States. https://doi.org/10.2172/1364098. https://www.osti.gov/servlets/purl/1364098.
@article{osti_1364098,
title = {Operational and Strategic Implementation of Dynamic Line Rating for Optimized Wind Energy Generation Integration},
author = {Gentle, Jake Paul},
abstractNote = {One primary goal of rendering today’s transmission grid “smarter” is to optimize and better manage its power transfer capacity in real time. Power transfer capacity is affected by three main elements: stability, voltage limits, and thermal ratings. All three are critical, but thermal ratings represent the greatest opportunity to quickly, reliably and economically utilize the grid’s true capacity. With the “Smarter Grid”, new solutions have been sought to give operators a better grasp on real time conditions, allowing them to manage and extend the usefulness of existing transmission infrastructure in a safe and reliable manner. The objective of the INL Wind Program is to provide industry a Dynamic Line Rating (DLR) solution that is state of the art as measured by cost, accuracy and dependability, to enable human operators to make informed decisions and take appropriate actions without human or system overloading and impacting the reliability of the grid. In addition to mitigating transmission line congestion to better integrate wind, DLR also offers the opportunity to improve the grid with optimized utilization of transmission lines to relieve congestion in general. As wind-generated energy has become a bigger part of the nation’s energy portfolio, researchers have learned that wind not only turns turbine blades to generate electricity, but can cool transmission lines and increase transfer capabilities significantly, sometimes up to 60 percent. INL’s DLR development supports EERE and The Wind Energy Technology Office’s goals by informing system planners and grid operators of available transmission capacity, beyond typical Static Line Ratings (SLR). SLRs are based on a fixed set of conservative environmental conditions to establish a limit on the amount of current lines can safely carry without overheating. Using commercially available weather monitors mounted on industry informed custom brackets developed by INL in combination with Computational Fluid Dynamics (CFD) enhanced weather analysis and DLR software, INL’s project offers the potential of safely providing line ampacities up to 40 percent or more above existing SLRs, by using real time information rather than overly conservative SLR.},
doi = {10.2172/1364098},
url = {https://www.osti.gov/biblio/1364098}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {12}
}