National Grid recently developed Consumer Building Blocks under NIA2_NGESO026 in conjunction with ERM (Element Energy), leading to publication at LSOA-level of domestic and non-domestic archetypes. These offer opportunities to DNOs to bring greater commonality across the transmission and distribution load models and to incorporate modelling improvements related to domestic and non-domestic responses to flexibility, efficiency, and LCTs. However, to adapt the non-domestic archetypes for DNO use requires incorporation of DNO specific services and considerations, and of the constraints faced by businesses in rural and urban settings. Work is also needed to develop methodologies that add regionality into the domestic archetypes by considering (for example) disposable household incomes, as the NG archetypes include uncontextualised data on household incomes.
Benefits
The guidance produced by this project could facilitate improved regional understandings of future low carbon technology deployment, which becomes increasingly important as DNOs become DSOs, and the way in which individuals and businesses engage with energy use shifts.
Learnings
Outcomes
The CBB archetypes usefully augment current DFES processes by bringing new information to the task of quantifying the effect of LCT uptake on the power system. They do not incorporate the depth of understanding that has been developed over many years of DFES development, but do provide a powerful, nationally consistent basis for disaggregating domestic low carbon technology (LCT) uptake projections produced as part of DFES to high spatial resolution, such as LSOA level.
Similar demographics in different areas of GB generate different levels of engagement with the net zero transition, and application of the archetypes to disaggregation of LCT uptake is improved by using regionally specific weights. This highlights the need for accurate reflection of regional specifics in the future planning of the energy system.
The non-domestic CBB archetypes do not as predict LCT uptake as well as their domestic counterparts. This likely has multiple causes:
- non-domestic LCT uptake is in its early stages, with less than 10% of the expected 2050 LCT uptake currently installed
- the installation data are not as high-quality as in the domestic case
- data on non-domestic businesses and premises is much sparser than data on household energy usage and demographics given the commercial sensitivity of some business data
However, there are regional patterns in the LCT uptake data which regression models do not systematically explain; both temporally – with domestic and non-domestic uptake following similar trends – and spatially. Again, this suggests the role of local expertise is likely to be important in planning for the impact of non-domestic LCT uptake in the net zero transition.
A linear model trained on the CBB archetypes can improve the geospatial LCT allocation that forms part of each GB DNOs DFES processes. In implementation, each DNO will need to assess how to integrate the post-processing step with their current DFES processes, and to validate and quantify the benefit.
Future strategic energy system modelling should incorporate as much local understanding and specificity as possible. QC of the non-domestic LCT uptake data is needed. Difficulties in fitting uptake data to the CBB archetypes in the non-domestic – relative to the domestic – case are partially explained by data quality, and the MCS and RHI/FiT datasets do not agree on HP and PV uptake respectively.
A quantitative validation and model fitting of the non-domestic CBB archetypes should be carried out on high quality non-domestic installation data once LCT uptake moves into the early-adopters phase. The non-domestic archetypes may better predict LCT uptake were the analysis re-run when uptake levels are higher, using a quality-controlled dataset of non-domestic LCT uptake.
Lessons Learnt
A steering group was set up for the project, which affirmed that we were on the right track and that other DNOs saw the potential for this learning. Setting this up ahead of time would have been more beneficial and shall be considered for future projects.
