Project Summary

WARN aims to address Challenge 3: Improving energy system resilience and robustness. Over the past few years extreme weather events have become more common and this has a direct impact on customers and the network given the direct relationship to faults and failures. WARN will provide better decision making and planning to mitigate against and reduce the impacts from these events. The WARN project will develop and test an integrated digital solution that monitors weather and climate-related asset vulnerabilities. This will enable DNOs to make decisions that will improve the robustness and resilience of their networks and operations in the face of weather shocks and future climate change.

WARN will require UK Power Networks to delve deep into the data they have and understand how they can use the innovation to improve their processes and decision making. Understanding how - and if - the weather impacts different aspects of the network is still unproven using real time data. The project will therefore focus first on using advanced statistical methods to identify relationships in past weather and UK Power Networks' network data. These will establish how weather variables combine to cause faults and induce slow onset performance risks, and the thresholds at which these emerge. This insight will then provide the basis for improved monitoring and alerting over three time periods:

1. Short-term (up to seven days)
2. Seasonal (e.g., upcoming winter)
3. Long-term (climate impacts on problematic weather conditions)

WARN has two key project partners:

1. The Institute for Environmental Analytics: an applied R&D centre specialising in modelling the impacts of weather and climate on the energy sector. WARN will build on an existing IEA proof-of-concept already demonstrated in the energy context in Columbia and on pre-existing software libraries and weather data pipelines used within a commercial weather monitoring platform.
2. UK Power Networks: distribution network operator and the end user of the innovation. They will utilise the integrated solution developed by the IEA to better understand how the weather and climate will impact their assets and operations.

If the project moves to Alpha Phase, SSEN have shown interest to be involved. DNOs and stakeholders involved in the planning of network operations and assets are the primary users of WARN and they are actively involved in the Discovery Phase to ensure the solution meets their needs.

Innovation Justification

UK government has made it a priority for all DNOs to improve capabilities for managing disruption caused by severe weather events (Ofgem Storm Arwen Report, June 2022). WARN will support this by developing a comprehensive new digital system to monitor weather and climate-related risks and enable more effective decision making.

DNOs have experimented with solutions to extreme weather and long-term climate change to some degree. Examples include Storm Resilience, MIVOR, Predict4Resilience, ERA, Ice Project and ACCELERATED. To date, no project has developed an operational system for the distribution infrastructure that is comprehensive across all relevant time horizons and types of risk. Predict4Resilience, for example, focuses on the transmission infrastructure and does not consider long-term climate projections, impacts to contact centres from increased call volumes or use of machine learning for continuous improvement, all of which are considered in WARN. Our aim is to provide a seamless approach for the DNOs, covering the near-term, medium-term, and long-term. Whilst UK Power Networks does undertake some high-level forecasting of weather impacts, it is not well understood at an asset level, does not include real-time weather data, and does not yet form part of day-to-day operational decision making.

WARN will enable step-change improvements in key metrics such as Customer Interruptions and Customer Minutes Lost. More intelligence on the impacts of extreme weather events will improve and reduce these metrics as UK Power Networks are better able to prepare the resourcing of their staff and equipment. In turn this will reduce total staff costs per annum as resourcing levels are better matched with operational requirements. If WARN is not deployed, we will continue to see the impacts of weather and climate on the cost of operating the network and on customers.

We will use relevant network data from recent weather disruptions as our counterfactual and benchmark against which we will evaluate our success.

Significant investment is required to develop WARN which would not typically be achievable as part of BaU or elsewhere within the price control as the approach, analysis, scope, and systems are new, unproven and carry a degree of risk. The initiative is highly strategic and will be developed in an agile way that is well suited to SIF as the feasibility must be proven before it can proceed. Given WARN's complementarity with CReDo+, it may be possible to include the WARN system as a module plugged into the CReDo digital twin.

Project Benefits

Financial -- future reductions in the cost of operating the network

1. WARN improves efficiency of field and contact operations:
   a)Metrics: i)Reductions to CML; ii)Improved utilisation of on-call staff (less redundancy); iii)Improved customer satisfactioniv)Improved utilisation of contact centre staff
2. Network-wide analysis informs evidence-based approach to network planning.
   a)Metrics: i)Reductions in CI and CML ii)Improved RoS.
3. Weather inputs to inform vegetation growth models improve vegetation management practices
   a)Metrics: i)Reductions in CI and CML ii)Reduced # of flying hours iii)Reduced #/distance of vehicle patrols

Financial -- cost savings per annum on energy bills for consumers

Directly related to reduced costs for network operations, flowing through to consumers as reductions on energy bills.

Financial -- cost savings per annum for users of network services.

Cost reductions for operating the network drive related cost savings for other users of network services.

Environmental -- carbon reduction -- direct CO2 savings per annum

1.Efficiency in field operations includes more intelligent deployment of mobile back-up generation: Metrics: Reduction in litres of consumed fuel/conversion to CO2 equivalents

2.Efficiency in field operations improves deployment of on-call staff:
Metrics: Reduced journey times and distances save fuel/conversion to CO2 equivalents

3.Improved targeting of vegetation management practices:
Metrics:
i.Reduced # (number) of flying hours reduces fuel consumption/conversion to CO2 equivalent
ii.Reduced #/distance of vehicle patrols reduces fuel consumption/conversion to CO2 equivalent

All benefits are linked to deployment into operations of WARN. Timeline to achieve is Discovery + Alpha + Beta = 24 to 36 months.