Rethinking Static Line Rating for Economic and Efficient Power Operation in South Korea
Junseon Park, Junhyun Lee, Hyeongon Park
TL;DR
The paper tackles safety and efficiency gaps in South Korea's Static Line Rating by proposing monthly, seasonal, and six-monthly updates to weather-based line-rating criteria and evaluating them with an OPF framework. By incorporating DC power-flow constraints, generator costs, and load-shedding penalties, the study demonstrates that a monthly-update scheme can nearly match Dynamic Line Rating performance while avoiding its implementation costs. Key finding: $SLR_{1month}$ typically yields lower total operating costs than conventional SLR and outperforms selective DLR deployment, offering a practical balance between reliability and economics. The work provides a concrete path to improve grid utilization under climate change without capital-intensive infrastructure, with implications for reliability analysis and policy guidance in transmission operation.
Abstract
In South Korea, power grid is currently operated based on the static line rating (SLR) method, where the transmission line capacity is determined based on extreme weather conditions. However, with global warming, there is a concern that the temperatures during summer may exceed the SLR criteria, posing safety risks. On the other hand, the conservative estimates used for winter conditions limit the utilization of renewable energy. Proposals to install new lines face significant financial and environmental hurdles, complicating efforts to adapt to these changing conditions. Dynamic Line Rating (DLR) offers a real-time solution but requires extensive weather monitoring and complex integration. This paper proposes a novel method that improves on SLR by analyzing historical data to refine line rating criteria on a monthly, seasonal, and semi-annual basis. Through simulations, we show our approach significantly enhances cost effectiveness and reliability of the power system, achieving efficiencies close to DLR with existing infrastructure. This method offers a practical alternative to overcome the limitations of SLR and the implementation challenges of DLR.