The project will look to overcome an initial barrier to Low Carbon Technology (LCT) uptake by producing Connection Readiness Indicators so customers can easily understand how ready a property is to connect an LCT, and give them the ability to request a Distribution Network Operator (DNO) proactively carry out works to upgrade fuses/cut-outs/looped services and remove the potential for delays when they eventually look to install an LCT. This will help customers avoid facing a “distress purchase” scenario where their existing heating system fails and only then are they made aware of the timescales involved in upgrading fuses/cut-outs or removing looped services. The project also aims to demonstrate how having access to data on incumbent heating systems can help DNOs improve network investment activities.
Benefits
Using a project cost of £555,575 to deliver the LCT Connection Readiness Indicator, we can expect a benefit of approximately 5 times the investment made to deliver the solution in SSEN-D network areas.
In addition, we should highlight the expected additional benefits which are harder to quantify but no less important – any delays in replacing a failed heating system can result in customers taking days off work to hurriedly research possible solutions and get checks carried out, possibly face financial burden from finding alternative accommodation or temporary heating/hot water solutions if they were determined to wait for the required works to get a HP, and experience the stress of the overall situation. Ultimately customers may simply opt for another fossil fuel heating system, which delays their and GB’s transition to low carbon heating.
Learnings
Outcomes
The project has carried out extensive customer research around the concept and the messaging strategy, and this Customer Research Findings report is now live in documents sections NIA SSEN 0077 LCT Connections Readiness Indicator | SSEN Innovation and LCT Connections Readiness Indicator | ENA Innovation Portal
The project has modelled 85% of missing service cable data and 82% of missing cut-out rating data in SHEPD, and 96% of missing service cable data and 98% of missing cut-out rating data in SEPD.
The project has produced LCT Connections Readiness Indicator data for 98% of properties in SSEN’s licence areas.
Initial accuracy checks against known data reveal that the service cable prediction model was able to correctly model looped services in 95% of cases, and single services in 79% of cases. The project will continue to assess the accuracy of the models via the data gathered in the field trials.
Full comprehensive details of the Project’s outcomes will be reported at the end of the Project.
Lessons Learnt
The field trials planned for the latter half of 2025 should enable further improvements to both the machine learning model for service cable prediction, and the logical decision model for cut-out rating prediction. With initial accuracy checks against known data showing the service cable prediction model was able to correctly model looped services in 95% of cases, and single services in 79% of cases. The project will continue to assess the accuracy of the models via the data gathered in the field trials. As it has been deemed valuable to continue to support initial customer and installer engagement and indicate the potential for requiring a looped service or cut-out upgrade, that SSEN is proceeding to upload the results of the modelled data into core systems which will enable it to support call handlers, SSEN’s Self-Serve minor connections tool, and Local Authorities using the LENZA tool.
