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Applying Wind Simulations for Planning and Operation of Real-Time Thermal Ratings

Greenwood, David; Ingram, Grant; Taylor, Philip

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David Greenwood

Philip Taylor


Real-time thermal ratings (RTTRs) are an emerging technology that allows the rating of electrical conductors to be estimated using real-time local weather observations. In many cases this leads to a very significant (typically 50%-100%) increase in rating with respect to conventional approaches. Conductor rating is heavily influenced by wind speed and direction. Consequently, in this paper, computational wind simulations commonly employed by the wind energy industry have been applied to inform rating estimation during network planning and operation. This provides an exciting opportunity to allow the identification of determining conductor spans to inform network designers of the rating potential of different conductor routes to estimate the additional wind energy that could be accommodated through the enhanced line rating and to allow intelligent placement of the monitoring equipment required to implement RTTR. The wind simulation data were also used to allow more accurate estimation of conductor ratings during operation. Two case studies taken from actual trial sites in the U.K. are presented to demonstrate that these techniques can provide a real world benefit.


Greenwood, D., Ingram, G., & Taylor, P. (2017). Applying Wind Simulations for Planning and Operation of Real-Time Thermal Ratings. IEEE Transactions on Smart Grid, 8(2), 537-547.

Journal Article Type Article
Acceptance Date Sep 30, 2015
Online Publication Date Oct 29, 2015
Publication Date Mar 1, 2017
Deposit Date Feb 3, 2016
Publicly Available Date Feb 4, 2016
Journal IEEE Transactions on Smart Grid
Print ISSN 1949-3053
Electronic ISSN 1949-3061
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 8
Issue 2
Pages 537-547
Keywords Computational fluid dynamics, Overhead power lines, Power system meteorological factors, Power system planning.


Accepted Journal Article (1.3 Mb)

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