Learnings

Outcomes

The project delivered several tangible outputs that contribute to improved industrial decarbonisation planning: 
A Data Sharing Agreement enabling compliant exchange of site-level industrial data. 
A structured methodology for cleansing and integrating electricity and gas datasets. 
Sector-specific decarbonisation playbooks providing consistent assumptions for future technology adoption. 
Forecasts of future industrial energy demand across electricity, hydrogen and biomethane. 
Spatial and temporal analysis of network impacts associated with industrial electrification. 
These outcomes collectively demonstrate how coordinated, data-led approaches can improve forecasting accuracy and reduce the risk of inefficient or duplicative network investment. The following insights are a result of this work:  
Publicly available data does not capture the range of industrial sectors or the scale of emissions located within the overlapping area studied in Indus 2.0 – smaller non-point source emissions are not captured in other datasets such as the NAEI dataset which is commonly used. 
There are 65 industrial sites from the nine sectors studied in the overlapping SGN/UK Power Networks licence areas. These sites represent 80% of the gas demand in the overlapping area (exclusive of power plants/sites which are solely used for power generation).  
Across scenarios, 131-771 MW of additional electrical load is expected from industrial decarbonisation in the overlapping SGN/UK Power Networks licence areas. This suggests that dispersed sites are still a meaningful source of load which may come online because of industrial decarbonisation.  
In hydrogen-focused pathways, there is up to 2.5 TWh of hydrogen demand by 2050 which is predominantly concentrated in three clusters. This demand is driven by sectors with high-temperature or direct-fire processes which are difficult to electrify (paper, bricks, building materials/gypsum).  
Across the sectors assessed, technology choices vary significantly depending on the underlying process‑heat requirements and the wider assumptions embedded in the FES pathways.

Lessons Learnt

Consistent with learning captured in similar NIA projects, the key insights relate to the practical application of the project’s innovative approach to data sharing and engagement. 
 
Data Sharing 
Legal and regulatory barriers to cross-network data sharing were more complex than initially anticipated.  
Involvement of NESO as an independent system operator was critical to enabling compliant data sharing within an innovation context. Along these lines, NESO’s new responsibilities under the Energy Act 2023 may unlock access to wider data sharing across the sector. 
Similar future data exchange may be best facilitated by Xoserve/Electralink rather than through bilateral agreements between network operators. 
Further work is required to establish how similar data sharing can be delivered outside an innovation funding framework. 
Stakeholder Engagement 
Industrial stakeholders are experiencing “engagement fatigue” due to uncoordinated outreach across the sector. 
Engagement is more effective when coordinated through recognised regulatory or system-wide bodies. 
Future projects should prioritise utilisation of existing stakeholder insights and minimise duplicated engagement activity.