ENTSO-EDynamic Line Rating (DLR)
Overview
Dynamic Line Rating (DLR) for overhead lines (OHLs) is enabled by the variability of their current carrying capacity based on ambient conditions. While OHLs are constructed to endure the peak summer conditions, they frequently operate under less severe weather for the majority of the year, allowing for potential increases in line capacity by up to 200%. [1] The primary challenge is to accurately determine current and predict future environmental conditions, compute the enhanced capacity, and effectively incorporate this data into dispatch centre operations with appropriate safety margins.
Benefits
DLR technology addresses several key challenges in the management of OHL transmission systems:
- Increase of Transmission Capacity: traditional static ratings of OHLs are based on conservative estimates and worst-case scenarios, primarily peak summer conditions. This frequently leads to the underutilisation of infrastructure for most of the year when the weather conditions are milder. DLR solves this by adjusting the capacity ratings based on real-time ambient conditions such as temperature, wind speed and solar radiation.
- Cost Efficiency and Infrastructure Optimisation: by increasing the ampacity of existing lines under favourable conditions, DLR can reduce the need for building new transmission lines, thereby saving costs on infrastructure development and minimising environmental impact.
- Enhanced Grid Reliability: with accurate, real-time line capacity data, operators can make better-informed decisions about power dispatch. This improves the overall reliability of the grid, especially during varying demand cycles.
- Climate Resilience: with changing climate patterns, DLR provides a tool for adapting the transmission system to new weather models, thereby supporting policies aimed at making infrastructure more resilient to climate change.
Current Enablers
The adoption and utilisation of DLR technology is supported by various factors within the market, as well as regulatory and technological aspects. Existing enablers include market-driven incentives, established standards and advanced technologies that facilitate the implementation and scaling of this technology. In addition, the application of DLR necessitates the inspection and possibly upgrading of all components in switchgear to accommodate the increased operational current. This need arises from the enhanced line capacity under optimal conditions enabled by DLR. Regulatory clarity and the development of standards specifically tailored to the technical and safety requirements of DLR are crucial to ensure the widespread adoption and effective implementation of this technology.
R&D Needs
To enhance the reliability and scalability of electrical systems, focusing on mid-term and long-term forecast adequacy of ampacity is essential. Ampacity, the maximum electrical current a conductor can carry, is crucial for system design and stability:
- Integration into Long-term Forecast Processes: accurately integrating ampacity forecasts into long-term planning ensures that electrical systems can handle expected loads and maintain stability under varying conditions.
- Accuracy of Derived Values: the precision of ampacity forecasts can be improved by using advanced analytics and real-time data, ensuring forecasts are dynamic and reliable.
- Enhanced Combination with Weather Forecasts: because weather significantly impacts ampacity, integrating weather data more closely with ampacity models will make forecasts more responsive to environmental changes, enhancing system resilience and efficiency.
Moreover, a standardised approach for integration into the operating centres can be beneficial for TSOs that presently use only a part of the technology capabilities.
The technology is in line with milestones “Integration of dynamic ratings and AI-based renewable power forecasts” and “Demonstration of innovative technologies for power flow control and increasing grid efficiency” under Mission 1 and milestone “Demonstrator of tools for compliance validation” under Mission 3 of the ENTSO-E RDI Roadmap 2024-2034.
TSO Applications
DLR systems have been successfully implemented in various European countries, enhancing the operational efficiency and capacity of power transmission lines. These systems utilise real-time data and advanced forecasting to optimise the power capacity of transmission lines under varying environmental conditions. This adoption showcases a clear trend towards leveraging technology to meet growing energy demands while addressing operational challenges.
Examples
| Location: Belgium, France | Year: 2008 – 2020 |
|---|---|
| Description: DLR systems are installed on 27 lines including all High Voltage Alternating Current (HVAC) interconnection lines, and both real-time and forecast DLR data are used in intraday and day-ahead operation planning and market capacity allocation processes. The recent development of the system and its validation through surveyor measurements of sag demonstrated that up to 200% of rated capacity was available in certain circumstances. | |
| Design: Commercially available sensors were used to measure real-time sag directly on 70 kV, 150 kV, 245 kV and 400 kV lines. An up to 60 h-ahead forecast module has been developed. | |
| Results: Intraday rated capacity is raised up to 130%, whereas for CORESO processes it is raised up to 110% based on statistical risk assessment. | |
| Location: Spain [2] | Year: 2017 |
|---|---|
| Description: The research for BEST PATHS is focused on repowering existing power lines and enhancing the technological knowledge and application of conductor technologies through different innovations. DEMO 4 has addressed the following objective through the development of a prototype DLR system based on low cost sensors, allowing for higher temperature operations of current line technologies. Part of the BEST PATHS project is the implementation of the DLR sensors on a transmission line in Spain | |
| Design: Using 7 DLR sensors on existing 220 kV live line variations in a catenary angle of 0.005 º or 10 cm in sag will be measured and communicated for optimal line loading. | |
| Results: Using data from DLR sensors, existing corridors were optimised to carry more power. A transmission capacity increase of 15 – 30% was measured over the duration of the experiment, which lasted 3 months. | |
| Location: Slovenia | Year: 2013-2017 |
|---|---|
| Description: The DLR system covers 29 lines (6 × 400 kV, 4 × 220 kV and 17 × 110 kV). The system is fully functional and integrated into the daily operation. The main applications that support real-time operation and operation planning are the mitigation of N and N-1 overloading operational situations and calculations of transmission capacities for up to two days ahead. The system also features an inverse DLR algorithm for icing prevention and alarms for extreme weather conditions along the lines. | |
| Design: An indirect (non-contact) DLR system based on macro and micro-scale meteorological models supported by weather measurements. Calculations are performed for each line span. The system enables the definition of maximal operating temperature per tension field. A comprehensive modular IT system with data quality monitoring and uncertainties modules is integrated with the SCADA / EMS. | |
| Results: On average, 92 – 96% of the time the DLR system offers a higher transmission capacity with a median increase of 15 – 20 % of the nominal capacity. Over 20 events in N and over 500 in N-1 topologies are mitigated annually by the DLR system. | |
| Location: Germany | Year: 2015 |
|---|---|
| Description: DLR is used on many heavily loaded OHLs. The system is integrated into most of the German TSOs’ dispatching centres that exchange the ratings online. | |
| Design: There are different approaches for weather forecasts based on local and regional measurements as well as seasonal settings. The maximal derived ampacity differs depending on the region. | |
| Results: Rated capacity was raised up to 200%. | |
| Location: Italy | Year: 2012 |
|---|---|
| Description: Terna followed a mixed approach to guarantee the high accuracy of the system and contain costs. DLR systems have been installed on several OHLs (380 kV, 220 kV, 150/132 kV) and are currently employed in the Control Rooms. A plan to increase the number of lines monitored with the DLR system is already in place. | |
| Design: Terna developed a thermo-mechanical model based on the CIGRE dynamic model which estimates the main conductor parameters (sag, temperature, stress) for each span of the line using detailed meteorological short-term forecasts. In particular, the mechanical model considers the mechanical balance of the conductors on the pylon and can also be employed for High Temperature Low Sag Conductors (HTLS). Real-time monitoring systems have been installed as feedback to the model results in the most critical spans to respect the clearance from obstacles according to Italian law. | |
| Results: In operation | |
Technology Readiness Level The TRL has been assigned to reflect the European state of the art for TSOs, following the guidelines available here.
- TRL 8 for DLR.
References and further reading
K. Moroyovska and P. Hilber “Study of the monitoring systems for dynamic line rating,”, Energy Procedia, vol. 105, pp. 2557–2562, May 2017.
Kladar Dalibor. “Dynamic Line Rating in the world – Overview.” , researchgate.net
Best paths. “DEMO 4, Innovative Repowering of AC Corridors.”, Bestpaths-project.eu
Navigant Research. “T&D Sensing and Measurement Market Overview.”, electricity-today.com
US Department of Energy. “Dynamic Line Rating Systems for Transmission Lines.”, energy.gov
ENTSOE, “Dynamic Line Rating for overhead lines – V6,”, Mar. 30, 2015.
E. Cloet and J. Santos “TSOs Advance Dynamic Rating,”, ampacimon.com
D. A. Douglass et al., “A Review of Dynamic Thermal Line Rating Methods With Forecasting,” IEEE Transactions, Jul. 2019, doi:10.1109/TPWRD.2019.2932054.
CIGRE-TB-498: “Guide for Application of Direct RealTime Monitoring Systems.”
CIGRE-TB-425: “Increasing capacity of power transmission lines – needs and solutions.”
J. Kosmač, A. Matko, F. Kropec and A. Deželak. Use of Dynamic Line Rating System in System Operation and Planning, CIGRE Paris, session 48, C2-143, 2020.