The expanding and interconnected electricity network poses challenges for National Grid Electricity Transmission (NGET) in monitoring and assessing network resilience. Currently, tracking resilience involves multiple metrics on separate Power BI pages, making it difficult to view overall resilience and hindering timely decision-making during storms or major events. This fragmented approach can lead to suboptimal maintenance and repair decisions. To address these challenges, the proposed project aims to incorporates probabilistic risk analysis to further improve resilience assessments, enhance decision-making accuracy using risk scores, and identify weak areas in the network. Additionally, simplify monitoring through a holistic map view. Ultimately, the project seeks to improve network resilience by streamlining risk identification and establishing minimum resilience levels for substations. FRAME II will be the full product release following the Minimum Viable Project phase in FRAME I.
Benefits
- Tool will highlight and quantify risk at network/site/asset level and provide enhanced justification for replacement, fix, reinforcement, new operating regime etc. The tool will show this in a way that is digestible for a person and help prioritise. This justifyies the reason to fix assets and ensures we are more intelligent about where we deploy defect repairs.
- Improving defect repairs improves network resilience and reduces constraints.
- Consolidates all topics onto one single page with a unified map view, improving trend identification across the whole network i.e., more than 350 sites with various asset types.
- Implementation of a scoring system for each issue will enable site resilience scoring, prioritising repairs and identifying high-risk locations for enhanced network resilience at a lower cost.
- Facilitates faster decision-making during network events and extreme weather conditions.
- Enables more accurate decision-making by utilizing holistic resilience information. Supports improved investment justification and asset management decisions.
- Enhances overall network resilience by identifying weak areas and establishing minimum resilience levels for substations.
- Centralising assets, manufacturers, technical limitations (TLs), and compliance information streamlines identification of recurring issues, justifying investment in critical assets in high-risk or neglected areas.
Learnings
Outcomes
- FRAME I provides NGET with a scalable and transparent foundation for risk-informed decision-making. It enhances business ability to anticipate and mitigate asset failures, complements existing frameworks and supports the transition toward a more adaptive, intelligence-led asset management strategy.
- The project developed a web based application that visualises complex resilience and risk data, providing a holistic network view and substation level detail, supported by a robust risk scoring methodology and two integrated engine models. These models combine machine learning with rule based weighting to generate composite substation risk scores, predicting TLs and asset level failure likelihood while incorporating Bayesian calibration.
- FRAME I fully achieved the weighted criteria requirement and the transformation of complex data into accessible and intuitive visual formats, with stakeholder testing confirming improved interpretability. Requirements relating to user tailored views, holistic map interaction, and rapid identification of high risk substations were partially achieved through delivery of the initial UI and ranking capabilities, with further refinement planned in FRAME II.
- Overall, the project met its registered Phase 1 objectives by elevating the technology readiness from TRL7 to TRL8, establishing a centralised resilience risk view, and creating a strong analytical and technical foundation for continued development in FRAME II, where asset coverage, usability testing and model expansion will be progressed.
Net Benefit Case
The total programme cost for FRAME (Phase 1 + Phase 2) is currently estimated at ~£1.284m (≈£1.3m rounded), comprising supplier costs of £556,000 (Phase 1) and £708,875 (Phase 2) (total supplier £1,264,875), plus £19k internal direct costs, with a 10% contingency included in the total. A commercial update has reduced Phase 2 supplier cost by ~£100k (from £708k to ~£614k), lowering the supplier total to ~£1,164,875 and reducing overall programme spend to ~£1.17m .This reduction strengthens the value for money case; however, since BAU adoption is now expected after 2026, the benefits profile is likely to shift later than originally assumed (i.e., early-year benefits will be reduced or deferred), even though the long run benefit mechanisms remain the same (worktime reduction, improved voltage control equipment & DAR availability). The revised benefit profile, updated NPV (Net Present Value) will be calculated and evidenced in the FRAME II report, including the full methodology, assumptions and supporting evidence.
Recommendations for further work
It is recommended to set up a follow up project (FRAME II) to develop a web application displaying key metrics for the Network Resilience Risk Tool based on the work of FRAME I. FRAME II should focus on the following activities:
- Enhancing the modelling methodology by refining the current approach.
- Investigating additional features to improve technical limitation prediction accuracy and identifying new datasets for potential inclusion.
- Adding consequences of failure as a quantifiable metric, to be used in conjunction with technical limitation predictions.
Lessons Learnt
- FRAME I focused on deriving asset risk scores from historical data, with technical limitations as a target, therefore good quality historical data and relevant technical limitation examples were essential for accurate modelling. The number of technical limitations being relatively limited adds complexity to the prediction of future events.
- During the development of the models, other datasets that may be beneficial in risk modelling came to light, such as alarms, dissolved gas analysis and faults and failure data. The next stage, FRAME II, is focused on exploring these datasets for further improvements to asset risk modelling. FRAME I was focused on ground assets, while FRAME II will also model risk of Overhead Line assets, combining them into circuits to better represent the entirety of the NGET network.
- Owing to existing technical constraints within the IT estate, the scope for Phase 2 was refined to prioritise the creation of a robust risk scoring methodology. Consequently, the project transitioned into a Proof of Concept focusing on delivering a more in-depth risk analysis instead of advancing directly to a Full Product implementation.
Dissemination
A final workshop has been conducted for the closure of FRAME I. NGET will disseminate FRAME I by collaboratively sharing the key outcomes and lessons learned across the wider industry. A dissemination workshop and conference presentation are expected in early 2026 after completion of both FRAME I and FRAME II.
