Loadscape aims to enhance UK Power Networks’ understanding of how non-domestic customers use electricity across different times of day and seasons. Non-domestic customers include all users outside of households, such as supermarkets, schools and businesses.
What is the project about?
UK Power Networks is building its understanding of how different types of non-domestic customers use electricity, using improved analysis to capture how demand varies over time. This includes both short-term changes (e.g. throughout the day) and longer-term patterns (e.g. across different seasons).
This enhanced insight will support Network Planning teams when assessing new connection requests, helping them determine whether a customer can connect to the nearest substation or if network reinforcement (i.e. infrastructure upgrades) is required.
The project aims to deliver several key benefits:
Lower connection costs for new customers
Faster decision-making during the connection process
More efficient use of the network by avoiding unnecessary reinforcement
Improved identification of Business Priority Services Register (PSR) customers – businesses that may need additional support during a power outage
The project will group non-domestic customers into types, such as “large supermarkets” and “schools.” For each type, it will create a typical pattern of how they use electricity and estimate how much they are likely to need at peak times.
This clearer understanding will help Network Planning teams make faster and better decisions when reviewing new connection requests.
How we’re doing it
The project is a partnership between UK Power Networks and Environmental Insight Partners (EIP), part of the University of Reading. It will be carried out as a desk-based research project.
First, UK Power Networks will share detailed electricity usage data for non-domestic customers with EIP. This data shows how much electricity is used every half hour, over several years. The data will be checked and cleaned to fix any problems, such as missing information. Other useful data, like weather conditions, will also be gathered.
Next, customers will be grouped into types, such as schools. Each group will be given a confidence level to show how accurate the grouping is. Business customers on the Priority Services Register (PSR) will also be identified.
These groupings will be reviewed with teams at UK Power Networks and updated based on their feedback. Once agreed, the project will create typical usage patterns and estimate peak electricity demand for each customer type.
Finally, UK Power Networks will review the results and, if they are accurate, use them to support the existing connections process.
What makes it innovative
Loadscape is innovative because of its scale, the level of detail and the way the data will be analysed — none of which have been used together in past studies. The project will look at several years of data, making it possible to spot patterns across different seasons and over time. Working with such large amounts of data will also require new and improved ways of analysing it.
Key findings will be shared throughout the project, including how the analysis was carried out. This will help other network operators carry out similar work for their own customers.
Overall, the project will use a large and detailed dataset to tackle an important challenge for network operators like UK Power Networks, reducing connection costs and delivering real benefits for both current and future customers.
What we’re learning
Loadscape will carry out new, first-of-its-kind analysis to help make the connections process more efficient for network operators.
The project will analyse electricity usage data for non-domestic customers to provide the following insights:
A clear method for grouping customers and identifying patterns in how they use energy, helping to create more accurate and efficient connection quotes
A proposed set of customer types, each with a confidence level to support better decision-making
Typical estimates of how each customer type uses electricity, to better inform connection requests
Checks on how accurate these usage patterns are
A practical approach for building these insights into the existing connections process used by Network Planning teams
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