Unlocking Transmission Flexibility under Uncertainty: Getting Dynamic Line Ratings into Electricity Markets
Zhiyi Zhou, Christoph Graf, Yury Dvorkin

TL;DR
This paper introduces a novel operational framework for dynamic line ratings (DLRs) in electricity markets, modeling their uncertainty and impact on dispatch and pricing to enhance transmission utilization.
Contribution
It develops a convex optimization approach integrating DLRs with uncertainty modeling into multi-period power flow, enabling more accurate dispatch and pricing strategies.
Findings
DLRs increase transmission capacity utilization.
The model improves dispatch efficiency and pricing accuracy.
Impact on marginal carbon emissions is demonstrated.
Abstract
Static transmission line ratings may lead to underutilization of line capacity due to overly conservative assumptions. Grid-enhancing technologies (GETs) such as dynamic line ratings (DLRs), which adjust line capacity based on real-time conditions, are a techno-economically viable alternative to increase the utilization of existing power lines. Nonetheless, their adoption has been slow, partly due to the absence of operational tools that effectively account for simultaneous impacts on dispatch and pricing. In this paper, we represent transmission capacity with DLRs as a stock-like resource with time-variant interdependency, which is modeled via an approximation of line temperature evolution process, decoupling the impacts of ambient weather conditions and power flow on transmission line temperature and thus capacity. We integrate DLRs into a multi-period DC optimal power flow problem,…
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