The distribution connections queue is c.180GW and growing, driven by electrification of demand and growth in low-carbon generation and storage. Assessing overall network impacts from this ever-evolving connections stack is challenging. This complexity makes it difficult for networks to evaluate available headroom and plan future investments.
FastTrack, an Artificial Intelligence solution, simulates the impact of connection requests from primary substations to the Grid Supply Point. By analysing network capacity, existing load, connection data, and external drivers, it provides a consolidated view of future demand. This supports system planners in making informed decisions on investments, access products, and interventions to accelerate delivery and optimise capacity use.
By the end of Alpha, our goal is to build and validate a robust Proof-of-Concept (PoC) AI solution for the core feature: Probabilistic Load Forecast with Attrition (SE1). This will demonstrate both clear business value and technical feasibility, proving that the most technically complex feature can be successfully built using available data. Success at this stage will lay the foundation for Beta to successfully build other solution elements and eventual Business-As-Usual (BAU) integration.
Pre-Innovation Baseline and Metrics: Currently, DNOs are unable to assess the real-time effects of the expanding connections queue on the network, from primary substations to the Grid Supply Point. Planning typically relies on slow, manual processes that cannot keep up with the rapid growth in connection requests driven by electrification.
Key baseline metrics include planned reinforcement expenditure at HV and above (from SSEN’s ED2 business plans to 2038).Time to Quote (TTQ) and Time to Connect (TTC) by voltage and asset type, and the anticipated growth in system planning FTEs needed to keep pace with interventions—under current methods. Annual improvements of around 2% in TTQ/TTC are forecast under BAU, owing to ongoing reforms.
Forecast Net Benefits to Consumers: Should FastTrack be adopted as business-as-usual at SSEN, an NPV of roughly £35 million by 2038 is anticipated, based on operational deployment from 2028. The benefits fall into three main channels:
Financial – Reduced Network Operation Costs: FastTrack enables more efficient planning and intervention delivery, giving planners a real-time view of load impacts and allowing interventions to be prioritised and adjusted as the queue changes. This results in a 2% efficiency saving on relevant reinforcement, with ‘in-scope’ targeted at HV and above, and 70% of this being addressable by FastTrack.
Operational Efficiency – Avoided Headcount Growth: FastTrack automates forecasting tasks, reducing the need for additional FTEs (c.10 fewer by 2035), with avoided costs estimated at £6–8 million.
Revenues – Expedited Access for Network Users: Faster and better planning shortens TTQ and TTC (by c.5% and 2.5% respectively), expediting revenues for demand-side and distribution-connected storage users.
Benefits Realised to Date: Early successes include demonstrating the value of AI for system planning, integrating diverse data sources, and user engagement to validate prototypes and guide design, thereby reducing technical risks and establishing a solid foundation for the Alpha proof-of-concept.
FastTrack has completed the Discovery phase, and has moved into the Alpha proof of concept, which will conclude mid-April 2026.
Total Discovery costs: £158,926
SIF Discovery funding requested: £143,033
1st February to 1st May 2025
Total Discovery costs: £554,998
SIF Discovery funding requested: £499,498
15th October 2025 to 15th April 2026
FastTrack SmarterNetwork Portal Link – Discovery
FastTrack SmarterNetwork Portal Link – Alpha
FastTrack Event Details – SIF Discovery Show and Tell
Gemma Ennis
