Impacts of Dynamic Line Ratings on the ERCOT Transmission System

TL;DR

The work addresses transmission bottlenecks by evaluating Dynamic Line Ratings (DLR) alongside Ambient Adjusted Ratings (AAR) and Static Line Ratings (SLR) on a synthetic ERCOT grid. It develops a multiplicative DLR framework, $\eta(v,T) \approx \eta_v \eta_T$, that incorporates wind speed, wind direction via $K_{angle}$, and ambient temperature, and couples this with a contingency-screened security-constrained DCOPF solved in parallel across hours. The study demonstrates that DLR can offer roughly double the benefits of AAR in terms of system costs, renewable curtailment, and emissions reductions, with substantial improvements in wind/solar utilization and congestion relief at the network level. These results underscore the practical potential of DLR to enhance transmission usage without new line construction, informing policy and utility practice while highlighting areas for validation and implementation challenges.

Abstract

Grid regulators and participants are paying increasing attention to Dynamic Line Ratings (DLR) as a new approach to address transmission system bottlenecks. In this paper, a thorough comparison of DLR, Ambient Adjusted Ratings (AAR), and the traditional Static Line Ratings (SLR) are conducted on a synthetic ERCOT grid. Estimates of DLR and AAR are calculated using an equation based on heat balance physics, along with high-resolution weather data of temperature and wind velocities. A constraint generation method for contingency screening is developed for solving security-constrained optimal power flow. Numerical results suggest that employing DLR could double the benefits compared to those of AAR relative to SLR, in terms of system costs, renewable curtailment, and emissions.

Figures (8)

• Figure 1: Weather data for 1AM on January 1, 2016. Temperature (in K). Wind speed (m/s) and direction.
• Figure 2: Overall work flow for DLR estimation and dispatch.
• Figure 3: Summary of DLR results.
• Figure 4: Branch-averaged DLR capacity factor increase values $\eta$ over time, under different parameter values.
• Figure 5: Hourly wind curtailment versus available wind resources: The slope of the positive association diminishes when switching from SLR to AAR to DLR. The 2nd-order polynomial best-fit lines are shown for clarity. Color of scatter plot points correspond to system load levels. The darker green points towards the top right illustrate the contribution of low-load, high-wind hours toward wind curtailment.