The Industrial Energy Intelligence project will develop and test a repeatable methodology for translating industrial decarbonisation intelligence into planning-ready regional assumptions for RESP and future COMIT modelling. The project will produce sector mapping, decarbonisation playbooks, modelling requirements, data architecture, implementation guidance, stakeholder validation processes and industrial intelligence gathering guidance. These outputs will improve the evidence base for industrial demand assumptions, support more robust regional planning, clarify COMIT input requirements and establish a repeatable process for gathering and validating industrial intelligence. Key risks include limited or commercially sensitive data, insufficient evidence to support sector assumptions, challenges in translating technology pathways into time-resolved network demand profiles, and the potential complexity of maintaining the methodology within BAU processes.
Benefits
Project benefits
The project will deliver a reusable industrial intelligence methodology, sector playbooks and COMIT requirements that improve NESO’s ability to translate industrial decarbonisation evidence into credible regional planning assumptions.
Who will benefit from this project and in what way?
NESO RESP modelling teams, RESP regional teams and the wider NESO organisation and network planning stakeholders will benefit from clearer, more consistent and better-evidenced industrial demand assumptions. The project will improve understanding of where industrial demand is located, which processes drive energy consumption, how different sectors may decarbonise, and how this could affect future electricity, gas, hydrogen-volumes, peak demand and flexibility requirements/potential.
The direct benefit is primarily Knowledge, because the project will create new learning on whether industrial demand can be characterised at a sector, site-type and end-use level, and whether sector decarbonisation pathways can be translated into planning-ready assumptions. It also supports Environmental benefits by improving the evidence base for industrial decarbonisation planning, Financial benefits by reducing the risk of inefficient network investment, and Social benefits by supporting more robust whole-system planning for consumers.
Confidence level
Medium to High. The project is designed to deliver useful learning even if some industrial sectors or activities cannot be represented robustly. If the evidence is sufficient, the project will produce a repeatable methodology and practical outputs for future RESP use. If the evidence is not sufficient, the project will still define the limits of current knowledge, identify data gaps and prevent NESO from prematurely embedding an unproven approach into BAU processes.
Can this benefit be quantified?
Partially. The direct project benefit can be quantified through the outputs delivered and improvements in modelling consistency, rather than through full consumer benefits at this stage. Expected measurable outputs include: mapping CaRB3 industrial activity classifications to Standard Industrial Classification (SIC) codes and identifying priority sectors that together account for around 80% of UK industrial thermal demand; producing at least 10 additional sector-level thermal end-use breakdowns; developing grouped sector decarbonisation playbooks covering technology options, adoption timings, energy-demand impacts, flexibility potential and uncertainty; defining COMIT data inputs, spatial and temporal modelling requirements, data architecture and implementation guidance; and producing a validation framework and industrial-intelligence-gathering guidance tested with two RESP Regional teams.
Full consumer benefit quantification is not currently feasible because the project is a development activity focused on testing methodology, evidence availability and implementation requirements. Wider financial and environmental benefits will depend on future adoption within COMIT and RESP planning cycles.
Future Full-Scale Benefit
If implemented at full scale, the project could provide a consistent GB-wide industrial intelligence capability for future RESP cycles, improving the quality of regional energy planning assumptions and supporting more efficient whole-system network development.
Who will benefit from this project in the future and in what way?
Network companies, who currently do not incorporate future industrial demand from decarbonisation at a granular enough level in their future network planning activities, will benefit from more credible regional assumptions on industrial electrification, biomethane / hydrogen conversion, gas demand change, peak demand and flexibility potential, supporting more efficient network reinforcement and investment decisions. Industrial customers will benefit from regional plans that better reflect future industrial decarbonisation needs, reducing the risk that network constraints delay or limit decarbonisation options, providing them the confidence that network infrastructure will be ready to support the execution of their decarbonisation strategies. Consumers will benefit through better-informed investment decisions that reduce the risk of both under-investment and inefficient over-investment. Policy and planning stakeholders will benefit from a stronger evidence base for understanding how industrial decarbonisation may affect regional energy systems, infrastructure needs and whole-system pathways.
What needs to happen for this future benefit to be realised?
The project outputs would need to be integrated into COMIT and RESP modelling processes through future BAU delivery. This would include developing or updating relevant COMIT workflows, data pipelines and interfaces; agreeing data governance, ownership, quality controls and refresh cycles; embedding the sector playbooks and demand assumptions into RESP planning processes; training regional teams to use the validation framework and intelligence templates; and assigning ongoing ownership for maintaining sector playbooks, assumptions and COMIT inputs. Broader validation with regional and industrial stakeholders may also be required before full-scale adoption.
Confidence level
Medium. The project should provide a strong basis for future implementation by defining the methodology, data requirements, playbooks, validation framework and COMIT requirements. However, the full-scale benefit depends on future delivery decisions, BAU implementation, data availability, regional adoption and ongoing governance.
Can this benefit be quantified?
Partially. The full-scale benefit can be estimated indicatively but cannot be fully quantified until the methodology is tested and integrated into future RESP cycles. The current evidence suggests the approach could help avoid underestimation of industrial peak, reduce underestimation of network peaks, reduce modelling rework, accelerate future industrial demand assumption updates and improve consistency of industrial decarbonisation assumptions across regions.
These estimates are indicative because the project is intended to test whether the methodology is feasible, scalable and sufficiently robust. Full quantified consumer benefits would require future implementation, comparison against baseline RESP modelling processes, and assessment of how improved industrial assumptions affect network planning and investment decisions.
