3D-AR: Dynamic, data driven asset rating (SIF Round 4)

Project Overview

Description

3DAR will develop a common framework for use within distribution networks, across a range of asset types (see appendix). By combining asset and demand forecast data with advanced weather forecasting we will develop a dynamic and flexible approach to asset rating and begin to identify areas of the network where DR may be beneficial. This automated approach can be used for both long term investment planning and for near real time optimisation of network flexibility requirements.

Asset ratings are usually based on an assumed ambient temperature and operating environment, with values remaining fixed for the season. Some transmission operators use in-situ monitoring systems to calculate the available circuit rating dynamically in real time. These are expensive and deployed only in specific circumstances. The challenge of this approach at distribution scale, is covering a higher volume of assets across a wider geographic area. A solution without sensors is required.

Key innovation areas:

  • Optimising locational weather data collection by integrating operational research.
  • Downscaling weather data to highly local forecasts, allowing for a more robust evaluation of assets suitable for DR.
  • Quantifying risk of applying DR at scale across distribution system.
  • Bridging planning and operations using aggregated data models to ensure well-informed and operationally aligned decisions.

Expected Benefits

3DAR will enable operators to choose the most cost-effective solutions for network constraints, defer costly reinforcements, and optimise flexibility investments at both procurement (long-term) and dispatch (short-term) levels.

Financial: operating the network.

Deferring network reinforcement: By having a holistic view of network load and capacity, 3DAR will provide insights into where additional headroom can be unlocked on the network, and where assets can be run for longer, at a higher capacity than current static operating levels. With tools currently available SSEN have already deferred over £44m in ED2, the use of 3DAR gives DNOs further options to defer investment.

Reduced expenditure in the procurement of flexibility services over ED2 as a result of increased capacities of network assets. 3DAR will reduce investment in flexibility services procurement by optimising the use of existing network capacity through real-time data-driven decisions, such as leveraging DR. This optimisation allows DNOs to defer costly network reinforcements and right-size flexibility procurement. Rather than relying heavily on procuring flexibility services to manage grid congestion or imbalances, DNOs can use the additional capacity unlocked through DLR to handle short-term peaks. The estimated CAPEX for procuring flexibility services in RIIO ED2 under Consumer Transformation was: £5.1-6.5m. The estimated financial savings from reduced expenditure in procuring flexibility services could be 5%-15%.

Environmental: carbon reduction, direct CO2 savings per annum. 3DAR supports a more efficient and low-carbon grid operation by enabling better integration of renewables, reducing reliance on fossil fuels, and cutting overall emissions. By enabling a more efficient use of existing grid capacity, 3DAR will ensure that the renewable energy generated during periods of high output can be more readily accommodated on the grid. This displaces the need for fossil fuel generation that would otherwise be required to meet demand. By maximising the use of renewable energy sources, it directly contributes to reducing the electricity system’s carbon footprint.

Creation of new market processes: The continuous evaluation provided by 3DAR ensures that the network is run at its most efficient level, minimising the need for expensive external interventions while maintaining reliability and supporting the integration of more renewable energy. This process leads to a more cost-effective and scalable approach to network management, reducing the reliance on flexibility services procurement.

Progress

This project is due to start in February 2025.

Funding

Total Cost – £120,391
SIF Funding – £120,391

Start/End Date

3rd February to 30th May 2025

Current Phase

Project Manager

Ross Bibby

Partnered with: