Diversifying Transmission Planning of Wind-Heavy Systems by Incorporating Dynamic Line Rating

Expanding electric transmission capacity for renewable energy sources such as wind and solar is essential for decarbonization efforts and meeting increased load demand. This typically requires significant investments in new transmission lines or upgrades to existing ones. However, enhancing the efficiency of current infrastructure can also be highly beneficial. Recently, the use of Dynamic Line Ratings (DLR) has gained significant attention from utilities. DLR allows operators to use lines at their true capacities by considering weather conditions, which can be much higher than the conservative static line ratings. This paper presents a methodology for identifying and implementing DLR on selected lines to enhance capacity and reduce upgrade costs. Line identification is performed using power flow tracing algorithms, where lines carrying more wind power are chosen as candidates for DLR implementation. A criticality score, which is a function of the average wind power flow in the line and the worst-case loading level, is then defined to prioritize the lines that need DLR implementation. The proposed method is tested on a modified system based on the Western Kansas area, with estimated cost savings evaluated. The criticality of these transmission lines during <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(n-1)$</tex> contingencies is also evaluated. Additionally, alternative reinvestment strategies for these savings are explored, which show their potential benefits for system security and reliability.

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Published
2024-10-13
DOI
https://doi.org/10.1109/naps61145.2024.10741620
Citations
2
Primary Topic
Thermal Analysis in Power Transmission
Type
article
Field-Weighted Citation Impact
0.66

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article

Diversifying Transmission Planning of Wind-Heavy Systems by Incorporating Dynamic Line Rating

Visvakumar Aravinthan, Charles R. Yokley, Satoshi Endo, Meng Yue et al.
2 citations
Thermal Analysis in Power Transmission
0.66
article

Diversifying Transmission Planning of Wind-Heavy Systems by Incorporating Dynamic Line Rating

Visvakumar Aravinthan, Charles R. Yokley, Satoshi Endo, Meng Yue, Al Tamimi, Tianqiao Zhao, Amirthagunaraj Yogarathnam, Sarangan Rajendrane
article en
2 citations

Abstract

Expanding electric transmission capacity for renewable energy sources such as wind and solar is essential for decarbonization efforts and meeting increased load demand. This typically requires significant investments in new transmission lines or upgrades to existing ones. However, enhancing the efficiency of current infrastructure can also be highly beneficial. Recently, the use of Dynamic Line Ratings (DLR) has gained significant attention from utilities. DLR allows operators to use lines at their true capacities by considering weather conditions, which can be much higher than the conservative static line ratings. This paper presents a methodology for identifying and implementing DLR on selected lines to enhance capacity and reduce upgrade costs. Line identification is performed using power flow tracing algorithms, where lines carrying more wind power are chosen as candidates for DLR implementation. A criticality score, which is a function of the average wind power flow in the line and the worst-case loading level, is then defined to prioritize the lines that need DLR implementation. The proposed method is tested on a modified system based on the Western Kansas area, with estimated cost savings evaluated. The criticality of these transmission lines during <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(n-1)$</tex> contingencies is also evaluated. Additionally, alternative reinvestment strategies for these savings are explored, which show their potential benefits for system security and reliability.

Brookhaven National Laboratory (US), Wichita State University (US)
Laboratory Directed Research and Development, Brookhaven National Laboratory
Affordable and clean energy
Openalex Percentile: Top 29%
Thermal Analysis in Power Transmission
0.66
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