Green Energy Tool is developing a solution to help customers more accurately estimate their electricity needs when requesting a new connection for low-carbon technologies (LCTs). By improving demand forecasts, the tool will also give the industry a better understanding of how these technologies interact with the electricity network.
What is the project about?
When applying for new electricity connections, customers often provide inaccurate load estimates, particularly when low-carbon technologies (LCTs) are involved. This can lead to a poor customer experience, as applicants must rely on third-party tools to estimate their capacity requirements.
Most existing tools use an approach known as After Diversity Maximum Demand (ADMD), which was developed before the widespread adoption of LCTs. As a result, these tools can produce inconsistent and often overestimated capacity forecasts, limiting their usefulness for modern technologies.
Green Energy Tool is exploring a new approach that uses LCT profiles to calculate load requirements. These profiles reflect how the electricity demand of technologies such as heat pumps, EV chargers and batteries changes over time, including by time of day and season. The project will assess whether this method provides more accurate estimates than the traditional ADMD approach. If successful, the findings will be used to develop an easy-to-use online tool that helps customers more accurately determine their electricity requirements when applying for a new connection.
How we’re doing it
Greener Energy Tool researching whether low-carbon technology (LCT) profiles can provide more accurate load estimates than the traditional ADMD approach. As part of this work, we will explore:
Insights from industry and innovation projects on how LCTs affect daily and seasonal energy demand patterns.
The impact of specialist electrical equipment used by medically dependent or vulnerable customers on household energy demand.
How participation in flexibility services influences the energy profiles of different customer groups.
Whether using load profiles instead of ADMD is a practical way to estimate customer capacity requirements and improve forecast accuracy.
Other factors that influence electricity consumption and LCT performance, such as a property’s energy efficiency rating and the effectiveness of technologies such as heat pumps.
Alongside this research, we will develop a tool to help customers estimate their load requirements. The first stage will be a clickable prototype, enabling us to test the concept and gather feedback from customers.
By combining research, tool development and customer testing, we will assess whether LCT profiles offer a more accurate way to estimate electricity demand, identify the features customers find most valuable, and determine which customer groups are most likely to benefit from and use the service.
What makes it innovative
By using LCT profiles rather than ADMD, Green Energy Tool is exploring a new way to help customers estimate their electricity requirements. This could lead to the development of the UK’s first tool of its kind, supporting the transition to low-carbon technologies through more accurate demand forecasting.
What we’re learning
We expect the project to generate valuable insights for both UK Power Networks and the wider industry, including:
Whether annual and daily load profiles that account for the interactions between different low-carbon technologies (LCTs) can provide more accurate capacity estimates than the traditional ADMD approach.
Whether this new estimation method could unlock capacity savings across the network.
How LCT demand affects higher-voltage network levels and whether these insights could deliver wider whole-system benefits.
Which customer groups would benefit most from more accurate demand forecasting tools and the features they find most valuable.
The business, technological and operational changes required to develop, integrate and deploy such a tool.
Together, these findings will help determine whether a profile-based approach can improve demand forecasting, enhance the customer experience and support a more efficient transition to a low-carbon energy system.
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