Introduction
The dataset captures yearly load profiles for different demand types, used by UK Power Networks to run import curtailment assessment studies.
The import curtailment assessment tool has gone live across all three licence areas in September 2024, and uses the standard demand profiles in this data publication to model accepted not-yet-connected demand customers for import curtailment studies.
Demand specific profile include the following demand types: commercial, industrial, domestic, EV charging stations, bus charging depots, network rail and data centres.
The profiles have been developed using actual demand data from connected sites within UK Power Networks licence areas falling into each of the demand categories. The output is a yearly profile with half hourly granularity.
The values are expressed as load factors (percentages) i.e., at each half hour the value can range from 0% to 100% of the maximum import capacity.
Methodological Approach
This section outlines the methodology for generating annual half-hourly demand profiles.
A minimum of ten connected demand sites for each of the demand types have been used to create the representative profiles.
Historical data from each of these connected demand sites are either retrieved from UK Power Networks’ Remote Terminal Unit (RTU) or through smart meter data. The historical data collected consist of annual half-hourly meter readings in the last calendar year.
A Python script was used to process the half-hourly MW data from each of the sites, which have been normalize by the peak MW values from the same site, for each timestamp, as follows:
P
t (p.u) = P
1, tPmax
1 + P
2, tPmax
2 + … + P
n, tPmax
n
where
- P,t(p.u) is normalised power
- P is the import in MW from sites 1, 2, ..., n
- Pmax is max import in the last calendar year, from site 1, 2, ..., n
- t is time, 30 minutes resolution for one year
The final profile has been created by selecting a percentile ranging from 95 to 98%.
Quality Control Statement
The dataset is primarily built upon RTU data sourced from connected customer sites within the UK Power Networks' licence areas as well as data collected from customers smart meters.
For the RTU data, UK Power Networks' Ops Telecoms team continuously monitors the performance of RTUs to ensure that the data they provide is both accurate and reliable. RTUs are equipped to store data during communication outages and transmit it once the connection is restored, minimizing the risk of data gaps. An alarm system alerts the team to any issues with RTUs, ensuring rapid response and repair to maintain data integrity.
The smart meter data that is used to support certain demand profiles, such as domestic and smaller commercial profiles, is sourced from external providers. While UK Power Networks does not control the quality of this data directly, these data have been incorporated to our models with careful validation and alignment.
Where MW was not available, data conversions were performed to standardize all units to MW. Any missing or bad data has been addressed though robust data cleaning methods, such as forward filling.
The final profiles have been validated by ensuring that the profile aligned with expected operational patterns.
Assurance Statement
The dataset is generated using a script developed by the Network Access team, allowing an automated conversion from historical half hourly data to a yearly profile. The profiles will be reviewed annually to assess any changes in demand patterns and determine if updates of demand specific profiles are necessary. This process ensures that the profiles remain relevant and reflective of real-world demand dynamics over time.
Other
Download dataset information: Metadata (JSON)
Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: https://ukpowernetworks.opendatasoft.com/pages/glossary/