[Paper Review] Impact of Dynamic Line Rating on Dispatch Decisions and Integration of Variable RES Energy

Bolun Xu, Andreas Ulbig+1 more|arXiv (Cornell University)|Dec 2, 2016

Thermal Analysis in Power Transmission7 references3 citations

TL;DR

This paper proposes a dynamic line rating (DLR) model that leverages real-time weather data and conductor thermal balance to increase transmission capacity beyond traditional nominal line ratings (NLR). Using high-resolution DC optimal power flow simulations on a German power system benchmark, it demonstrates that DLR reduces wind curtailment by up to 800 GWh annually and significantly decreases load shedding under high renewable energy penetration, especially in congested corridors like Bremen–Frankfurt–Stuttgart.

ABSTRACT

Dynamic line rating (DLR) models the transmission capacity of overhead lines as a function of ambient conditions. It takes advantage of the physical thermal property of overhead line conductors, thus making DLR less conservative compared to the traditional worst-case oriented nominal line rating (NLR). Employing DLR brings potential benefits for grid integration of variable Renewable Energy Sources (RES), such as wind and solar energy. In this paper, we reproduce weather conditions from renewable feed-ins and local temperature records, and calculate DLR in accordance with the RES feed-in and load demand data step. Simulations with high time resolution, using a predictive dispatch optimization and the Power Node modeling framework, of a six-node benchmark power system loosely based on the German power system are performed for the current situation, using actual wind and PV feed-in data. The integration capability of DLR under high RES production shares is inspected through simulations with scaled-up RES profiles and reduced dispatchable generation capacity. The simulation result demonstrates a comparison between DLR and NLR in terms of reductions in RES generation curtailments and load shedding, while discussions on the practicality of adopting DLR in the current power system is given in the end.

Motivation & Objective

• To assess the impact of dynamic line rating (DLR) on transmission congestion and renewable energy integration in power systems with high variable RES shares.
• To develop a weather-based DLR model that calculates real-time line capacity using ambient conditions such as temperature, wind speed, and solar radiation.
• To simulate and compare dispatch outcomes under DLR versus traditional nominal line ratings (NLR) using high-resolution real-world data from 2011.
• To evaluate the practical feasibility and limitations of implementing DLR in existing transmission systems, including equipment constraints and spatial weather variability.
• To quantify the reduction in renewable energy curtailment and load shedding when DLR is applied under scaled-up future RES scenarios.

Proposed method

• Developed a DLR model based on the conductor thermal balance equation, incorporating Joule heating, solar heating, convective cooling, and radiative cooling.
• Calculated line ratings using ambient weather data (air temperature, wind speed, wind angle, solar radiation) instead of relying on conductor temperature measurements.
• Reconstructed historical weather conditions from local temperature records and renewable energy feed-in data to enable consistent DLR estimation over time.
• Applied a DC optimal power flow (DC OPF) dispatch model with a cost function penalizing load curtailment and generation curtailment to simulate economic dispatch under DLR and NLR.
• Simulated a six-bus benchmark power system modeled after the German grid, using actual 2011 wind and PV feed-in data and scaled-up RES profiles to represent future scenarios.
• Evaluated line loading and congestion on the Bremen–Frankfurt–Stuttgart corridor using time-series DLR and NLR ratings, comparing curtailment and transmission performance.

Experimental results

Research questions

• RQ1 To what extent can DLR reduce wind generation curtailment and load shedding in a high-RES power system compared to NLR?
• RQ2 How do variations in ambient weather conditions (e.g., wind speed, solar radiation) affect the dynamic rating of overhead transmission lines?
• RQ3 What is the impact of spatial weather variability along transmission lines on the accuracy of DLR estimation when using simplified node-based models?
• RQ4 How does DLR affect the overall transmission capability of a congested transmission corridor under high renewable generation?
• RQ5 What are the practical limitations of implementing DLR in real-world power systems, including equipment ratings and measurement uncertainties?

Key findings

• DLR reduces wind curtailment by approximately 800 GWh annually in the Bremen–Frankfurt–Stuttgart transmission corridor under a scaled-up future RES scenario.
• Load curtailment in the Frankfurt and Stuttgart zones is reduced by nearly half when using DLR compared to NLR, particularly during high-wind winter periods.
• The DLR model increases transmission capacity by up to 200% under high wind speeds (e.g., 6 m/s), significantly improving power transfer capability in congested corridors.
• The simulation results show that DLR effectively mitigates congestion in the north-south transmission path, enabling more efficient transfer of wind power from northern to southern Germany.
• Despite the benefits, DLR’s effectiveness is limited by spatial weather variability and the need to cap ratings based on worst-case scenarios and equipment thermal limits.
• The study concludes that DLR is a cost-effective alternative to building new transmission lines for integrating high shares of variable RES, especially in transmission-constrained networks.