Project Summary

With increasing demand for both electrification and renewables connections, many
areas of the distribution network are approaching their capacity and will need
intervention. Traditionally, DNOs can reinforce the network or procure flexibility
services to meet these peaks. These are costly solutions that can have long lead
times. By leveraging dynamic asset ratings at scale for the first time at distribution
level, this project enables the deployment of a data-driven solution that optimises
capacity through real-time, localised weather data and asset modelling. 3DAR will
enhance network investment planning, reducing costs and ensuring long-term
resilience for faster, more efficient connections. 

Innovation Justification

Core innovative aspects

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.

Innovation and state of the art

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.

Building on previous research

This Project will consolidate insights from academic research, SSEN Transmission's REVISE Discovery Phase, and SPEN's ongoing Beta Phase Project, P4R. These provide a firm foundation, but do not address the key challenge of cost-effective deployment at scale across the DNO network.

In addition, relating to the application of sensor-less DLR, there are several established vendors providing these services to Transmission Operators, the Project will seek input from them.

Splight: https://www.splight-ai.com/about
Heimdall Power: https://heimdallpower.com/

TRL

3DAR has a current TRL of 4, and CRL2. We aim to progress this to TRL 5 in Alpha and higher in Beta.

SIF funding

Given the Project risk and complexity, SIF provides the ideal funding mechanism. Additionally, the cross-industry collaboration required to integrate granular weather data into DR modelling supports the need for SIF, as no current market proposition exists to use this data effectively in distribution.

Counterfactual

Traditionally, DNOs have either reinforced networks or procured network flexibility services to provide additional capacity both requiring significant capital or operational costs.

Impacts and 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 optimizing 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.