Summary

When energy systems fail, the cause is often not just technical — it's human.

The UK's energy supply chain is vast. It connects power generators, grid operators, fuel suppliers, regulators, and millions of end users. When something goes wrong — a cyberattack, an equipment failure, a policy shock — the effects don't stay contained [1]. They cascade. And the damage is often made worse not by the original threat, but by the fact that the different organisations involved in the response have different priorities, risk thresholds, and ideas about who should act and how [2].

This is the problem ResChain set out to tackle. Current tools for managing energy risk are good at cataloguing technical threats, but they don't capture the tensions that exist between the organisations sharing the same infrastructure. A grid operator, a renewable energy supplier, and a regulator may all recognise the same risk, yet disagree fundamentally on how serious it is, who is responsible for it, and what to do about it [3 ,4]. Those disagreements don't just slow down decision-making, they create hidden vulnerabilities that traditional risk assessments never see.

Over four months, the ResChain team worked with stakeholders from across the UK energy sector to map these tensions. Through two structured workshops bringing together industry, academia, and policy voices, the team gathered data on how different organisations perceive and prioritise risks — and where their views diverge most sharply. The findings fed into a new analytical tool called the Tension Map framework, which makes these organisational fault lines visible and links them directly to resilience planning.

The result is a practical resource for energy operators, policymakers, and regulators: a structured way to identify not just what the risks are, but whose risks they are, and where misaligned priorities are quietly undermining the system's ability to respond. A white paper summarising the findings and setting out recommendations.

Objectives

Phase 1 of ResChain was structured around four objectives:

1. Scoping and stakeholder mapping. To identify key stakeholders and risk types in the energy supply chain, and to review existing risk assessment frameworks to establish where socio-organisational factors are underrepresented.

2. Stakeholder engagement and data collection. To design and run two structured impact workshops capturing how energy sector stakeholders perceive and prioritise risks, collecting quantitative data on their interests, concerns, confidence, and interdependencies across key risk domains.

3. Analysis of stakeholder tensions and dependencies. To translate divergences in stakeholder risk perception into measurable tension scores, map these scores against stakeholder dependencies, and identify latent vulnerabilities that are invisible to conventional risk assessment methods.

4. Framework development and recommendations. To develop the Tension Map framework, integrating stakeholder Interest Level (IL) and Concern Level (CL) into probabilistic risk assessment , and to produce a white paper setting out the findings and recommendations for future research and practice.

Activities

We conducted the following activities:

1. Reviewed existing resilience frameworks and case studies and identified key stakeholders and types of risks in the energy supply chain.

2. Designed and ran two structured impact workshops to identify stakeholder risk perceptions, priorities, and key tensions, one in-person (February 2026) and one online (March 2026).

3. Analysed stakeholder data collected during the impact workshops, including tension scores, dependency mappings, and responses to a crisis scenario exercise.

4. Developed the Tension Map framework, integrating stakeholder Interest Level (IL) and Concern Level (CL) into probabilistic risk assessment to produce tension-adjusted vulnerability scores.

5. Produced a white paper summarising the project findings, the Tension Map framework, and recommendations for future research and practice.

Outputs

1. Impact workshop design, which reflects a novel methodology to capture different levels of interest and concern, identify key tensions in risk perception among energy supply chain stakeholders, and map tensions to vulnerabilities.

2. Running two impact workshops on 11/02/2026 (in-person), and 24/03/2026 (online), where data in relation to stakeholders’ risk perception alongside key tensions were collected.

3. A stakeholder-centric resilience framework: Novel Tension Map framework, which integrates socio-organisational tension into probabilistic risk assessment.

4. White paper which summarises the main project findings, including the Tension Map framework, Impact workshop data analysis, Recommendations and next steps.

5. Seminar talk at ECR NetZero Conference on 09/03/2026. The seminar discussed the findings collected from the first impact workshop.

Impact

Phase 1 of ResChain generates new insights into how stakeholders across the energy sector perceive and prioritise supply chain risks. The project findings not only inform future phases of ResChain but also provide an evidence base that can support better-informed decision-making within the energy sector. By making the white paper publicly available and disseminating findings through the SPRITE+ website and relevant industry events, we ensure our insights reach a wide audience of practitioners, policymakers, and researchers. Additionally, the tension map framework, which is clearly articulated in our white paper, enables stakeholders in adjacent sectors, such as water, transport, and digital infrastructure, to adapt our approach, thereby catalysing similar assessments and improvements in risk awareness and resilience beyond the energy domain.

Broader Impact of ResChain Programme:

We break down the wider ResChain impact of our project findings into the following areas:

1. Policy and Governance Impact: Phase 1 findings have a great impact on ResChain phase 2, in which we will provide policymakers and regulators with a transparent, evidence-based tool for understanding how risk propagates across socio-technical boundaries. Our risk representation modelling approach also supports equitable risk governance by aligning resilience strategies with stakeholder-specific priorities and tolerances. ResChain is aligned with the Royal Academy of Engineering’s review of risk governance in government, which emphasised the joined-up approach to managing risk across government departments and stakeholders. Our approach could ultimately be integrated into the UK Government's risk assessment, as adjacent sectors are indeed a core area from which to transfer lessons. 

2. Operational Impact: ResChain findings, especially the tension map framework, help energy operators and vendors anticipate how their decisions affect broader system resilience, reducing the likelihood of siloed or conflicting mitigation actions. Certain workstreams beyond Phase 1 improves incident response coordination by making risk trade-offs and impacts visible in near real time across the supply chain.

3. Societal Impact: By embedding stakeholder concern,including transparency, compliance, and sustainability, into resilience planning, ResChain supports more equitable and publicly accountable risk governance across the energy sector.

4. Scientific & Technical Impact: The Tension Map framework formally integrates stakeholder Interest Level (IL) and Concern Level (CL) into probabilistic risk assessment, producing tension-adjusted likelihood estimates that augment existing methods such as MAGERIT. The white paper is deposited in the University's research repository for open access.

Future work

1. Subsequent work which will refine data-collection instruments by incorporating calibration techniques and triangulating survey responses with documentary evidence and expert validation.

2. Pilot case studies that compare calculated tension scores with real or historical incidents, enabling empirical validation of the model.

3. The framework’s static nature will be extended through longitudinal data collection, enabling the tracking of tensions over time and supporting early identification of emerging risks.

4. Visualisation techniques will be refined through user testing to ensure clarity and consistency in interpretation. Collectively, these activities will strengthen the framework’s robustness, usability, and practical relevance.

References:

1. Holm, T. B., Daloz, A. S., Ma, L., Van Maanen, N., Tamang, R., & Aall, C. (2025). From climatic hazards to systemic vulnerabilities: Evolving perceptions of climate risk in Norway’s renewable energy sector. Energy Research & Social Science, 130, 104456. DOI: https://doi.org/10.1016/j.erss.2025.104456

2. Song, Y., Wang, Z., Song, C., Wang, J., & Liu, R. (2024). Impact of artificial intelligence on renewable energy supply chain vulnerability: Evidence from 61 countries. Energy Economics, 131, 107357. DOI: https://doi.org/10.1016/j.eneco.2024.107357

3. Xexakis, G., Hansmann, R., Volken, S. P., & Trutnevyte, E. (2020). Models on the wrong track: model-based electricity supply scenarios in Switzerland are not aligned with the perspectives of energy experts and the public. Renewable and Sustainable Energy Reviews, 134, 110297. DOI: https://doi.org/10.1016/j.rser.2020.110297

4. Axon, C. J., & Darton, R. C. (2024). A systematic evaluation of risk in bioenergy supply chains. Sustainable Production and Consumption, 47, 128-144. DOI: https://doi.org/10.1016/j.spc.2024.03.028