UK Power Networks
L o a d i n g
UK Power Networks (UKPN) own and maintain electricity cables and lines across London, the South East and East of England, delivering power to approximately eight million customers.
Available DatasetsShowing 139 of 139 results
- Introduction Daily Demand Statistics (Minimum, Average, Maximum) for Grid Supply Point (GSP). It includes aggregated GSP Data for all the monitored GSPs, and it also includes SGT data if we have used those for the creation of aggregated data. Data includes Voltages, Current, Active Power, and Reactive Power, and is updated every half an hour. This dataset shows data from a sample of GSPs which account for 1/5th of the total GSPs in our area (we will add more sites across the network in the future). To streamline and enable faster data refresh, we have structured our data into a header file which is light. This data is refreshed every 30 minutes. Methodological Approach The power flow data is streamed from our PI server, into an FTP server before being published on the Open Data Portal. To streamline and enable faster data refresh, we have structured our data into a header file which is light. Quality Control Statement The data is published as is from the network. Assurance Statement The Open Data Team and DSO Data Science Team worked together to ensure data accuracy and consistency. Other Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal Glossary Download dataset information: Metadata (JSON)To view this data please register and login.22 days ago
- Introduction A monthly updated snapshot of the number of meters connected by local authority district and by meter category: smart; and not smart (analogue). Specifically, our smart meter definition is: Profile Class 0-4 meters only; and Meters in Measurement Class A,F and G only.Note 1: where UK Power Networks borders NGED and SSEN, and share coverage of common local authorities, only UK Power Networks customers connected to the UK Power Networks are shown.Note 2: the smart meters are mapped to LSOA using Office for National Statistics datasets which are updated annually. However, UK Power Networks smart meter installation counts are updated monthly so there is a natural but negligible discrepancy.Contains Local Authority district code and name data sourced from the Office for National Statistics licensed under the Open Government Licence v.3.0 Methodological Approach Data Extraction and Cleaning: Smart Meter installation data is extracted by post code, such that each post code has a count for smart meters; analogue; and advanced. Aggregation: Each post code is assigned to a local authority. Polygon Creation: Each local authority is then assigned to a local authority polygon. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations; Manual review and correct of data inconsistencies; and Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and Income Management Team worked together to ensure data accuracy and consistency. 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/42 days ago
- IntroductionShapefile showing operational boundaries in the UK Power Networks South Eastern Power Networks (SPN) area. Methodological Approach This dataset was extracted from UK Power Networks' internal geospatial mapping database - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/42 days ago
- Introduction Following the submission of evidence to NESO on the 10th of September 2025 of eligible Gate 2 to Whole Queue projects (G2tWQ), UK Power Networks seeks to provide further insight, at the Grid Supply Point (GSP) level, on the progress status of generation projects. These progress status categories are based on the National Energy System Operator's (NESO) queue formation criteria. This allows further visibility at a more granular level, while protecting individual information from projects. A project can be classed as one of five categories: Significantly progressed projects connecting by 2027 or earlier: Projects that have provided evidence they are meeting Protection Clause 2a, and have a firm or non-firm connection date of 2027 or earlier. Other significantly progressed projects: Projects that have provided evidence they are meeting Protection Clause 2a, with a connection date of 2028 or later. Other ready projects: Projects that have provided evidence they are meeting the readiness criteria (without any protection clause), via the land or planning route. Not ready / Gate 1 choice projects: Projects which have not provided any evidence or have opted for a Gate 1 offer. Outside of scope for Gate 2 to Whole Queue: Projects which were not part of an offer or an application to NESO by the 29th of January 2025, following Ofgem’s decision on pause of applications to NESO. Methodological Approach We follow a strict approach to ensure that, while we want to share as much useful data as possible, we are not providing specific information that can be linked to an individual project. The progress status of each project is obtained from our internal registers, which in turn has been obtained from our interactions with customers, our delivery pipeline and other requests for information. This is in turn grouped by GSPs and technologies, and classified as one of the seven categories used (aligning with NESO’s Gate 2 Readiness Criteria). From this dataset, we will apply two iterations to be certain no specific project is identifiable with a progress status stage. In the first place, all categories where the customer count is 1 (e.g. one solar project is Under Construction”) would be blanked out. By doing this, we avoid what we understand would allow that specific project to be identified, by looking at its capacity, and locating it in the queue of that GSP. In addition, if, after applying that initial check, there is a technology row with only a single non-blank, non-zero entry, we would blank the entire row . E.g. only three solar projects with Land rights only, those three projects could then be located in the queue as the only three solar schemes. The same blanking out correction is applied if the only non-blank, non-zero row entries are “Projects without readiness or not progress at all” and/or “Outside of scope for Gate 2 to Whole Queue”. Quality Control Statement This dataset has been peer reviewed, and sample checked. Assurance Statement The data provided above constitutes UK Power Networks’ provisional view of the status at this GSP at the date of publication and is for general information only. OtherDownload 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/To view this data please register and login.22 days ago
- IntroductionThis dataset contains the areas that are served by an Independent Distribution Network Operator, i.e. where the electricity distributor is not UK Power Networks. Users can use Line Search Before You Dig to target areas of interest. Methodological Approach This dataset was extracted from UK Power Networks' internal geospatial mapping database - NetMap.Please note, we are reliant on IDNOs informing and sharing their polygon areas with us, there are occasions where we do not receive them, as so the areas are not shown. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/To view this data please register and login.42 days ago
- Introduction 5 December 2024: The National Chargepoint Registry (NCR) was decommissioned on 28 November 2024 by the Department of Transport. All public EV chargepoint operators are now required to share open data free of charge on elements such as location, real-time availability, connector types, and payment methods. The archived NCR data will be available on request to users and researchers. For any enquiries contact consumerofferconsult@ozev.gov.uk. Methodological Approach This dataset was provided by the Office for Zero Emission Vehicles. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the code for the API pull against source to ensure data accuracy and consistency. For more information, please visit their website: Department for Transport The National Chargepoint Register (NCR) is a database of publicly available chargepoints for electric vehicles in the UK established in 2011. The underlying dataset from the Office of Zero Emission Vehicles (OZEV) is continually updated by chargepoint networks, owners and controllers.Note, we have restricted the coverage to overlap with UK Power Networks three licence areas of Eastern Power Networks, London Power Networks and South Eastern Power Networks.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/42 days ago
- IntroductionA special dataset that contains metadata for all the published datasets. Dataset profile fields conform to Dublin Core standard.Other You can download metadata for individual datasets, via the links provided in descriptions. Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: https://ukpowernetworks.opendatasoft.com/pages/glossary/22 days ago
- IntroductionThis dataset provides the locations of areas that restrict the suitability of land for solar PV developments; such as roads, residential areas, world heritage sites, agricultural land, and flood zones. In addition, it calculates the potential energy density of over 3.5 million individual areas for both solar and wind installations using windspeed and solar irradiance data.This results in an overall assessment of the suitability of a specific area for installing solar and wind generation. The assessment grades land as either YES – suitable, No – not suitable, or MAYBE – could be suitable. This dataset was developed for UK Power Networks licence area by UEA Consulting Limited. It is based on public domain sources and previous analysis that was carried out as part of the IRENES EU Interreg project which examined renewable energy sources in eastern England.Methodological ApproachTo view the methodology behind this data please click here.This dataset displays the solar PV data, click here for the wind data. Quality Control Statement This dataset is provided "as is". Assurance Statement The Open Data Team and Local Net Zero Team worked together to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- IntroductionThis list outlines the current plans for the development of UK Power Networks' three license areas over the next five years, as detailed in the latest Long Term Development Statement (LTDS) Development Proposals. The LTDS is updated twice a year, at the end of May and November. Please note that these plans may change in both content and timing. All listed projects aim to increase network capacity, while those focused solely on asset replacement are not included. For more information and full reports, visit the landing page below: Long Term Development Statement Landing Page Methodological Approach FLOC association: FLOCs are used to associate the LTDS infrastructure upgrade projects to grid and primary substations, to create geopoints. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. Other You can also download dataset information here: 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/To view this data please register and login.42 days ago
- Introduction The dataset provides detailed information about UK Power Networks' Grid Sites and Primary Sites. It includes key characteristics such as: Spatial coordinates of each site Year commissioned Asset counts against each site Power transformer count Local authority information Winter and summer demand Transformer (Tx) ratings This data is useful for understanding the infrastructure and capacity of the electricity network across its regions. Methodological Approach Source: Various internal data domains - geospatial, asset, long term development statement; as well as openly available data from the Ordnance Survey and Office of National Statistics Manipulation: Various data characteristics were combined together using Functional Locations (FLOCs) Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. Other Contains data from Office for National Statistics licensed under the Open Government Licence v.3.0. Local Authority District (2022) to Grouped Local Authority District (2022) Lookup for EW - data.gov.uk Contains Ordnance Survey data Crown copyright and database right [2019-]. Free OS OpenData Map Downloads | Free Vector & Raster Map Data | OS Data Hub 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/To view this data please register and login.42 days ago
- Introduction This beta dataset provides carbon intensity insights by Grid Supply Points (GSP) across UK Power Networks’ licence areas. It shows blended carbon intensity values for each half-hour period, helping users understand how the carbon intensity of energy varies over time and across different parts of our network. Methodological Approach Plant Information (PI) tags and values associated with generators are matched to the relevant GSP, across Eastern Power Networks (EPN) and South Eastern Power Networks (SPN), via the Embedded Capacity Register (ECR), (over 1MW only). Generator fuel types are classified using the ECR's Energy Source and Energy Conversion Technology fields, with fallback logic applied where ECR data is missing (e.g., inferring fuel type from customer name). Fuel types are then mapped to published carbon intensity factors (gCO₂/kWh) provided courtesy of NESO (National Energy System Operator). For the purposes of this beta methodology, Batteries/BESS are assigned a carbon intensity factor of 0gCO₂e/kWh. This is a simplifying assumption and may be reviewed in future iterations, as battery discharge may reflect electricity previously imported from or generated elsewhere on the system. Using the PI values, carbon intensity at the DNO (Distribution Network Operator) level (without transmission network data) is calculated using a modified equation of the original methodology provided by NESO: DCt = Σ G g=1 Eg,t × Cg Eg,t Where: DCt is the DNO-level carbon intensity, in grams of CO₂ per kilowatt hour (gCO₂e/kWh), G is total number of generators, g is the individual generator, Eg,t is the energy export of the distribution-connected generator onto the distribution network at time t in kilowatt hours (kWh) and Cg is the generator’s corresponding carbon intensity factor in gCO₂e/kWh. We divide by the sum of Eg,t because the calculation produces a GSP-level generation-weighted carbon intensity. This calculation is performed separately for each GSP and half-hour period. Each generator’s contribution is weighted according to its exported energy during the half-hour period. Transmission import/export is accounted for separately in Equation 2. Network losses and sensitivity factors are not applied in this beta methodology. PI values are recorded from the PI server in MW. Our data is half-hourly, and thus, these values are converted to kW by multiplying by 1000 and then multiplying by 0.5 for kWh. Where multiple PI readings exist within a half-hour period, the average MW value is calculated first, then converted to kWh. Super Grid Transformer (SGT) header data is then added to the dataset. The SGT active energy value represents the net energy flow at the transmission-distribution boundary: positive values indicate energy flowing from transmission into the distribution network (import), while negative values indicate energy flowing from distribution back to transmission (export). The blended carbon intensity formula extends the original NESO formula to incorporate the transmission contribution: BDCt = ((Eg,t × DCt) + (ESGT,t × Ct)) (Eg,t + ESGT,t) Where:Blended DNO carbon intensity, BDCt, at time t is calculated using the generation-weighted average carbon intensity of DNO generation, DCt, the SGT import/export energy, Esgt,t, and the NESO regional carbon intensity forecast, Ct. The SGT value represents the net energy flow at the transmission-distribution boundary during the half-hour period. Where SGT active power is recorded in kW, it is converted to kWh by multiplying by 0.5 hours. This formula is applied with the following assumptions: If sgt_energy_kwh is positive, the interval is treated as data available, and blended carbon intensity is calculated as a weighted average of local DNO generation intensity and the NESO regional carbon intensity forecast, weighted by their respective power contributions. This reflects the transmission network supplementing local generation to meet demand. If sgt_energy_kwh is negative but dno_generation_kwh + sgt_energy_kwh > 0, the interval is treated as data available, and the blended carbon intensity is set to the local weighted average carbon intensity only. The NESO forecast is disregarded because the DNO network is a net exporter - local generation exceeds demand and the surplus is flowing back to the transmission network, so no transmission network-sourced power is entering the distribution network. If sgt_energy_kwh is negative and dno_generation_kwh + sgt_energy_kwh <= 0, the interval is treated as no data available, and the blended carbon intensity is set to null. This occurs when the volume of power being exported to transmission network exceeds total visible DNO generation, suggesting either unmetered generation, data quality issues, or load flow conditions that cannot be reliably attributed to a carbon intensity value; and If sgt_energy_kwh is null, the interval is treated as no data available with no transmission network data available. Without SGT data, the transmission network contribution to demand cannot be quantified and a reliable blended carbon intensity cannot be calculated.Limitations and ConsiderationsDNO generation visibility is limited to generators registered in the ECR and matched via PI tags. Unregistered or unmetered embedded generation is not captured.The NESO regional carbon intensity forecast is used as a proxy for the carbon intensity of power imported from the transmission network. This is a regional average and may not precisely reflect the marginal generation mix at the specific GSP.Quality Control StatementQuality control measures include:Automated review to check PI tag status; andMonthly upload of new ECRAssurance StatementThe Open Data Team, DSO Data Science Team, and the DSO Regional Development Team worked together to ensure data accuracy and consistency.OtherDownload 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/To view this data please register and login.22 days ago
- IntroductionTo ensure we deliver a safe and reliable electricity supply or to invest in our network, we may need to carry out works on highways and footways.This dataset contains details of open street and roadworks permits and private activities taking place on the highway or on private land within the UK Power Networks footprint. See what work we are doing, where and when you can expect us to finish. This report is refreshed every two hours.For further information including contact details, please visit https://www.ukpowernetworks.co.uk/help-and-contact/roadworks-delayed-or-overrunning-works Methodological Approach Data Extraction: Data is extracted from Street Manager onto a server every two hours. Data Upload: Another script is run every two hours to upload onto an FTP server, before passing onto the Open Data Portal. Quality Control Statement Quality Control Measures include: Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodologyPlease note that multiple permits can exist for one job. This may be to store equipment such as a generator. Assurance Statement The Open Data Team and Streetworks Team worked together to ensure data accuracy and consistency. 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/42 days ago
- Introduction UK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is distributing this electricity across our regions through circuits. Electricity enters our network through Super Grid Transformers at substations shared with National Grid we call Grid Supply Points. It is then sent at across our 132 kV Circuits towards our grid substations and primary substations. From there, electricity is distributed along the 33 kV circuits to bring it closer to the home. These circuits can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables. This dataset provides half-hourly current and power flow data across these named circuits from 2021 through to the previous month across our Eastern Power Networks (EPN) license area. The data is aligned with the same naming convention as the LTDS for improved interoperability. Care is taken to protect the private affairs of companies connected to the 33 kV network, resulting in the redaction of certain circuits. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted. To find which circuit you are looking for, use the ‘ltds_line_name’ that can be cross referenced in the 33kV Circuits Monthly Data, which describes by month what circuits were triaged, if they could be made public, and what the monthly statistics are of that site. If you want to download all this data, it is perhaps more convenient from our public sharepoint: Sharepoint This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets. Methodological Approach The dataset is not derived, it is the measurements from our network stored in our historian. The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps. We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. This redaction process considers the correlation of all the data, of only corresponding periods where the customer is active, the first order difference of all the data, and the first order difference of only corresponding periods where the customer is active. Should any of these four tests have a high linear correlation, the data is deemed redacted. This process is not simply applied to only the circuit of the customer, but of the surrounding circuits that would also reveal the signal of that customer. The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation. Quality Control Statement The data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these measurements are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that. Assurance Statement Creating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS circuit from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same circuit in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing circuits, incorrectly labelled circuits, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible. Additional InformationDefinitions of key terms related to this dataset can be found in the Open Data Portal Glossary. Download dataset information: Metadata (JSON) We would be grateful if you find this dataset useful to submit a reuse case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. Click here for more information: Open Data Portal Reuses — UK Power Networks To view this data please register and login.22 days ago
- Introduction The GIS (Geographic Information System) vectorisation project will deliver the incremental digital conversion of our legacy geospatial network records. This dataset defines the sub-areas which will be incrementally delivered, detailing corresponding current status and planned completion dates. This allows users to understand the current and future coverage of digital geospatial network records as the project progresses. Methodological Approach Progress against a defined project plan is captured and updated throughout the day. A script is run to convert into a shapefile. This shapefile is then uploaded onto the Open Data Portal. Quality Control Statement This dataset is provided "as is". Assurance Statement The Open Data Team has checked outputs to validate. 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/42 days ago
- Introduction This dataset is a geospatial view of the areas fed by primary substations. The aim is to create an indicative map showing the extent to which individual primary substations feed areas based on MPAN data. Methodological Approach Data Extraction: MPAN data is downloaded from the geographical system. The system searches with a geographical window and assigns it to the nearest supply point. Connectivity: Data is taken from the connectivity model and mapped to the relevant MPAN. Data Filtering: Any coordinates that are more than 500m from the nearest secondary site are removed. Primary Assignment: Postcodes of the MPANs are assigned to a primary substation based on the number of MPANs fed. Polygon Creation: Primary Feed Polygons are created and cleaned up to remove holes and inclusions. Hierarchy Construction: Grid Supply Point polygons are produced from schematics and merged based on hierarchical relationships. FLOC Matching: Functional Location Codes (FLOC) are matched to the respective sites.Geospatial data was then layered using dataset Local Authorities and County Councils within UK Power Networks licence areas — UK Power Networks to determine which local authorities were fed by each primary substation. Quality Control Statement Quality control measures include: Verification steps to match features only with confirmed FLOCs. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Regular updates and reviews documented in the version history. Assurance Statement The Open Data team, worked with the Geospatial Data Engineering team ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- IntroductionThis dataset contains the geographical locations of High Voltage overhead lines that are in use in the Eastern Power Network (EPN) and South Eastern Power Network (SPN) licence areas. Locations are available as Geo Point (latitude and longitude) and Geo Shape. The dataset can be downloaded as a shapefile. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/To view this data please register and login.42 days ago
- Introduction Volume of Low Carbon Technologies (LCT) for both generation and demand (under 1MW) connected or accepted to connect to UK Power Networks Secondary Substations where: There are greater than 5 LCT connections (or accepted to connect) by Type; and The secondary site transformer serves more than 5 customers. This is done in the interest of protecting customer privacy. Methodological Approach LCT application data (which captures, amongst other things, the location, LCT type, and capacity) is taken from our Smart Connect portal at https://www.ukpowernetworks.co.uk/smart-connect; Using the MPAN (Meter Point Administration Number), we look up our connectivity model to ascertain the upstream connecting secondary and primary substations; and Data is then aggregated to the secondary site where there are greater than 5 connections. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations; Manual review and correction of data inconsistencies; and Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction When a generation customer requests a firm connection under a congested part of our network, there may be a requirement to reinforce the network to accommodate the connection. The reinforcement works take time to complete which increases the lead time to connect for the customer. Furthermore, the customer may need to contribute to the cost of the reinforcement works. UK Power Networks offers curtailable-connections as an alternative solution for our customers. It allows customers to connect to the distribution network as soon as possible rather than waiting, and potentially paying, for network reinforcement. This is possible because under a curtailable connection, the customer agrees that their access to the network can be controlled when congestion is high. These fast-tracked curtailable-connections can transition to firm connections once the reinforcement activity has taken place. Curtailable connections have enabled faster and cheaper connection of renewable energy generation to the distribution network owned and operated by UK Power Networks. The Distribution System Operator (DSO) team has developed the Distributed Energy Resource Management System (DERMS) that monitors curtailable-connection generators as well as associated constraints on the network. When a constraint reaches a critical threshold, an export access reduction signal may be sent to generators associated with that constraint so that the network can be kept safe, secure, and reliable. This dataset contains a record of curtailment events and the associated access reduction experienced by DERs with curtailable connections. Access reduction is calculated as the MW access reduction from maximum × duration of access reduction in hours (MW×h). The dataset categorises curtailment actions into two categories: Constraint-driven curtailment: when a constraint is breached, we aggregate the access reduction of all customers associated with that constraint. A constraint breach occurs when the network load exceeds the safe limit; and Non-constraint driven curtailment: this covers all curtailment which is not directly related to a constraint breach on the network. It includes customer comms failures, non-compliance trips (where the customer has not complied with a curtailment instruction), planned outages, and unplanned outages. Each row in the dataset is a curtailment event, meaning a continuous period of access reduction, with associated start and end times, volume of access reduction, estimated energy reduction, and likely curtailment driver. We also provide the associated grid supply point (GSP) and nominal voltage to provide greater aggregation capabilities. Estimated energy loss is calculated using the average generation of the specific asset from the five most recent non-curtailment weekdays or the two most recent non-curtailment weekend days, depending on whether the curtailment event occurred on a weekday or a weekend. The curtailment driver column represents UK Power Networks' best view of the likely driver of the curtailment. Future improvements may remap drivers and provide a more detailed breakdown of drivers. By virtue of being able to track curtailment across our network in granular detail, we have managed to significantly reduce curtailment of our curtailable-connections customers. Methodological Approach A Remote Terminal Unit (RTU) is installed at each curtailable-connection site providing live telemetry data into the DERMS. It measures communications status, generator output, and mode of operation. RTUs are also installed at constraint locations (physical parts of the network, e.g., transformers, cables which may become overloaded under certain conditions). These are identified through planning power load studies. These RTUs monitor current at the constraint and communications status. The DERMS design integrates network topology information. This maps constraints to associated curtailable connections under different network running conditions, including the sensitivity of the constraints to each curtailable connection. In general, a 1MW reduction in generation of a customer will cause <1MW reduction at the constraint. Each constraint is registered to a GSP. DERMS monitors constraints against the associated breach limit. When a constraint limit is breached, DERMS calculates the amount of access reduction required from curtailable connections linked to the constraint to alleviate the breach. This calculation factors in the real-time level of generation of each customer and the sensitivity of the constraint to each generator. Access reduction is issued to each curtailable-connection via the RTU until the constraint limit breach is mitigated. Multiple constraints can apply to a curtailable-connection and constraint breaches can occur simultaneously. Where multiple constraint breaches act upon a single curtailable-connection, we apportion the access reduction of that connection to the constraint breaches depending on the relative magnitude of the breaches. Where customer curtailment occurs without any associated constraint breach, we categorise the curtailment as non-constraint driven. Future developments will include the reason for non-constraint driven curtailment. Quality Control Statement The dataset is derived from data recorded by RTUs located at customer sites and constraint locations across our network. UKPN’s Ops Telecoms team monitors and maintains these RTUs to ensure they are providing accurate customer/network data. An alarms system notifies the team of communications failures which are attended to by our engineers as quickly as possible. RTUs can store telemetry data for prolonged periods during communications outages and then transmit data once communications are reinstated. These measures ensure we have a continuous stream of accurate data with minimal gaps. On the rare instances where there are issues with the raw data received from DERMS, we employ simple data cleaning algorithms such as forward filling. RTU measurements of access reduction update on change or every 30 minutes in the absence of change. We also minimise post-processing of RTU data (e.g., we do not time average data). Using the raw data allows us to ascertain event start and end times of curtailment actions exactly and accurately determine access reductions experienced by our customers. Assurance Statement The dataset is generated and updated by a script which is scheduled to run daily. The script was developed by the DSO Data Science team in conjunction with the DSO Network Access team, the DSO Operations team, and the UKPN Ops Telecoms team to ensure correct interpretation of the RTU data streams. The underlying script logic has been cross-referenced with the developers and maintainers of the DERMS scheme to ensure that the data reflects how DERMS operates. The outputs of the script were independently checked by the DSO Network Access team for accuracy of the curtailment event timings and access reduction prior to first publication on the Open Data Portal (ODP). The DSO Operations team conducts an ongoing review of the data as it is updated daily to verify that the operational expectations are reflected in the data. The Data Science team has implemented automated logging which notifies the team of any issues when the script runs. This allows the Data Science team to investigate and debug any errors/warnings as soon as they happen. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal Glossary To view this data please register and login.22 days ago
- IntroductionThis dataset shows our secondary sites and a number of attributes including oil natural air natural (ONAN) ratings, spatial coordinates, customer counts, whether a site is indoor/outdoor, the address, substation name, alias and its primary feeder. Note: as of 18 April 2024, we have included an additional column showing the utilisation band of the site. The utilisation bands do not indicate contractually committed capacity e.g. capacity on our network may be unused now but expected to be used by a connection in a future year, recent acceptances which will be covered in next year's data. There is a site classification as follows: GMT: Ground Mounted Transformer; andPMT: Pole Mounted Transformer. As per the attached triage document, we have redacted sites from this dataset where a transformer serves five or less customers. This is in the interest of protecting customer privacy. Further, we are aware that for a small number of records there are null values, this is primarily for the rare cases where sites have more than one transformer. There is an ongoing review into how this is recorded, which will be reflected in the data once resolved. If you notice any errors, please let us know by feedbacking against the record in the table tab. Methodological Approach Data Extraction: This dataset is extracted from Azure Databricks. Combination: Various data columns are joined in Azure Databricks based on the FLOC. This includes Grid Reference, connectivity and the number of customers. Processing: There are some processing, such as conversion of Grid Reference into longitude and latitude. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- This asset was linked to the following asset: Data Roadmap and Tracker - VisualizationIntroduction This dataset provides visibility on what datasets are under review and when they may be published on the Portal. The datasets are all triaged and have the following triage ratings: 1 - In review 2 - Published 3 - Published with restricted access 4 - Rejected Methodological Approach This dataset is fed by a static dataset via Sharepoint, and is updated as and when there is an update. Quality Control Statement Quality Control Measures include: Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal Glossary22 days ago
- IntroductionThis dataset contains the frequency and duration that EHV electricity assets are out of service for planned outages from UK Power Networks' Network Vision - an outage planning tracking tool. Which provides a customer facing web portal to provide information about generation customer curtailments and shutdowns to our customers, and provides an interface for our customers to engage with our Outage Planners. We have removed planned outages which are related to customer sites, i.e. this dataset is not the complete view of unplanned EHV network outages. Distributed generation customers should register and login via our Network Vision tool for full visibility. Methodological Approach Data Extraction and Cleaning: Data is extracted from Network Vision. Data Filtering: We have removed planned outages which are related to customer sites, i.e. this dataset is not the complete view of unplanned EHV network outages. Functional Location Codes (FLOC) Matching: FLOC codes are extracted and matched to Primaries, Grid Sites and Grid Supply Points. Confirmed FLOCs are used to ensure accuracy, with any unmatched sites reviewed by the Open Data Team. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correct of data inconsistencies Assurance Statement The Open Data Team and Outage Planning Team worked together to ensure data accuracy and consistency. 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/42 days ago
- Introduction UK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is the stepping down of voltage as it is moved towards the household; this is achieved using transformers. Transformers have a maximum rating for the utilisation of these assets based upon protection, overcurrent, switch gear, etc. This dataset contains the Primary Substation Transformers, that typically step-down voltage from 33kVto 11kV (occasionally from 132kV to 11kV). These transformers can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables. This dataset provides half-hourly current and power flow data across these named transformers, in our Eastern Power Networks region, from 2021 through to the previous month across our license areas. The data are aligned with the same naming convention as the LTDS for improved interoperability.Care is taken to protect the private affairs of companies connected to the 11kV network, resulting in the redaction of certain transformers. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted. To find which transformer you are looking for, use the ‘tx_id’ that can be cross referenced in the Primary Transformers Monthly Dataset, which describes by month what transformers were triaged, if they could be made public, and what the monthly statistics are of that site. If you want to download all this data, it is perhaps more convenient from our public sharepoint: Open Data Portal Library - Primary Transformers - All Documents (sharepoint.com)This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets. Methodological Approach The dataset is not derived, it is the measurements from our network stored in our historian.The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps.We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. Where the primary transformer has 5 or fewer customers, we redact the dataset.The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation. Quality Control Statement The data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these transformers are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that. Assurance Statement Creating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS transformer from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same transformer in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing transformers, incorrectly labelled transformers, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible. Additional information Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary. Download dataset information: Download dataset information: Metadata (JSON) We would be grateful if you find this dataset useful to submit a “reuse” case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. Click here for more information: Open Data Portal Reuses — UK Power NetworksTo view this data please register and login.22 days ago
- IntroductionShapefile showing the position of UK Power Networks' 33kV overhead lines for all licence areas. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/To view this data please register and login.42 days ago
- IntroductionUK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is the stepping down of voltage as it is moved towards the household; this is achieved using transformers. Transformers have a maximum rating for the utilisation of these assets based upon protection, overcurrent, switch gear, etc. This dataset contains the Grid Substation Transformers, also known as Bulk Supply Points, that typically step-down voltage from 132kV to 33kV (occasionally down to 66 or more rarely 20-25). These transformers can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables. This dataset provides half-hourly current and power flow data across these named transformers from 2023 through to the previous month across our licence areas. The data are aligned with the same naming convention as the LTDS for improved interoperability.Care is taken to protect the private affairs of companies connected to the 33kV network, resulting in the redaction of certain transformers. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted. To find which transformer you are looking for, use the ‘tx_id’ that can be cross referenced in the Grid Transformers Monthly Dataset, which describes by month what transformers were triaged, if they could be made public, and what the monthly statistics are of that site. If you want to download all this data, it is perhaps more convenient from our public sharepoint: Open Data Portal Library - Grid Transformers - All Documents (sharepoint.com)This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets.Methodological ApproachThe dataset is not derived, it is the measurements from our network stored in our historian.The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps.We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. This redaction process considers the correlation of all the data, of only corresponding periods where the customer is active, the first order difference of all the data, and the first order difference of only corresponding periods where the customer is active. Should any of these four tests have a high linear correlation, the data is deemed redacted. This process is not simply applied to only the circuit of the customer, but of the surrounding circuits that would also reveal the signal of that customer.The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation.Quality Control StatementThe data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these transformers are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that.Assurance StatementCreating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS transformer from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same transformer in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing transformers, incorrectly labelled transformers, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible.OtherDefinitions of key terms related to this dataset can be found in the Open Data Portal Glossary.Download dataset information: Download dataset information: Metadata (JSON)We would be grateful if you find this dataset useful to submit a “reuse” case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. Click here for more information: Open Data Portal Reuses — UK Power NetworksTo view this data please register and login.22 days ago
- Introduction Shapefile showing UK Power Networks' 132kV overhead lines. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap; and Quality Control Statement The data is provided "as is". Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- Introduction This dataset shows an anonymised list of live, committed, import-related projects within UK Power Networks' licence areas. This includes not-yet energised, demand-only projects that are 5,000 kilovolt-amperes (kVA) and above, as well as battery energy storage systems (BESS). This list has been determined using internal systems UK Power Networks uses to manage all committed projects in the process of connecting to our network. To protect the identity of the sites, entries have been anonymised and only the licence area, the grid supply point the project is connecting at (or under), rounded requested import capacity, and application date have been provided. Methodological Approach Live, committed demand projects are identified through desktop exercises using UK Power Networks' internal customer relationship management system and extracted. The projects are then filtered to only show projects where The required import capacity is more than or equal to 5,000kVAThe required export capacity is 0MVA. These project entries are then cross-referenced with other sources to verify its status. Any discrepancies are manually reviewed and kept/omitted as appropriate.To protect the identity of the demand projects the required import capacity is rounded, and the project names are anonymised by providing an arbitrary sequential number. Quality Control Statement The dataset is primarily built upon internal data, relating to live demand projects in UK Power Networks' licence areas. Information about battery energy storage systems are taken from existing datasets relating to Appendix G information UK Power Networks manages.Data have been checked with both automatic and manual validation methods. Assurance Statement The dataset is generated through a manual process, conducted by the Distribution System Operator's Regional Development Team. The dataset will be reviewed monthly to assess any changes, and to determine if any updates to the methodology are necessary. This process ensures that the dataset remains relevant and reflective of the live large demand projects UK Power Networks is working on. There are sufficient projects per licence area to assure anonymity of projects.While all reasonable efforts have been made to ensure the accuracy of the information provided in this dataset, neither the licensee nor any of its directors or employees is under any liability for any errors, or for any misstatement on which a user of the data seeks to rely. Please view our Terms and Conditions for more information.The data provided constitutes UK Power Networks’ provisional view of the status at this GSP at the date of publication and is for general information only. 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/For prospective customers considering a connection to our network, we provide pre-application support on our website to make the connection journey as smooth as possible: Pre-application support and advice | UK Power NetworksWe also offer an "Ask the Expert" service, designed for some of your more complex connection questions that go beyond our FAQs. You can request an "Ask the Expert" surgery session, where our specialists can provide more specific technical guidance: Ask the Expert | UK Power NetworksTo view this data please register and login.22 days ago
- IntroductionThe Distribution Future Energy Scenarios (DFES) are primarily a series of granular scenario-based forecasts for key drivers of demand and generation technologies whose deployment are essential to achieving Net Zero. This includes EVs, decarbonised heating such as heat pumps and district heat networks, and forms of renewable energy generation and storage. For each driver, a range of forecasts are produced under different assumptions.The 2026 DFES datasets, detailing the how many, by when, and where, for a number of low carbon technologies drivers at LAD level until 2050. Methodological Approach Adopted the new pathway framework published by the National Energy System Operator in their 2024 Future Energy Scenarios (FES) to update our scenarios.All of Great Britain’s Distribution Network Operators (DNOs) have used the new pathway framework published by the National Energy System Operator in their “Future Energy Scenarios 2024: Pathways to Net Zero” to update their Distribution Future Energy Scenarios (DFES).This framework includes three potential energy pathways to achieve Net Zero emissions by 2050, along with an additional counterfactual scenario.These pathways represent different positions with regards to their speed of decarbonisation and level of societal change. The move to pathways is an approach that enables long term planning.In alignment with this change, we have updated our 2026 DFES to reflect the pathways framework, incorporating locally-influenced, bottom-up insights to support robust network planning.We have developed bespoke scenarios for each driver of demand and generation and constructed four overarching scenario worlds that align with the narratives of the pathways from the National Energy System Operator.We have integrated the latest local area energy plans inputs into all three of our Net Zero scenarios - ensuring that our planning reflects the most current regional insights. Quality Control Statement Cross-year and cross-scenario consistency checks.Glossaries and metadata provided for transparency. Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON)Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction The dataset provides detailed information about UK Power Networks' unplanned fault reporting under the Ofgem Interruptions Incentive Scheme (IIS). It includes key characteristics such as: Date/time fault start/end Number of customers affected Restoration stages Cause and main equipment involved Status of fault in terms of its exclusion from the IIS scheme due to it being a one-off /severe weather faultThe upstream primary substation to the fault More information about the IIS can be found on Ofgem's website or this document: RIIO-ED2 Regulatory Instructions and Guidance – Interruptions Methodological Approach Source: IIS returns post application of Ofgem decision one status of fault in terms of its exclusion from the IIS scheme due to it being a one-off /severe weather fault Manipulation: Includes all rows from unplanned fault reporting IIS returns with calculation of CI/CML removed, leaving source data only i.e. no calculated fieldsAddition: Inclusion of the sitefunctional location of the upstream Primary substation and its geopoint. Quality Control Statement The data is provided "as is". Assurance Statement The Regulation Team checked to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- Introduction Active transformer characteristics from our Grid Sites. Methodological Approach Data stems from our data warehouse; and Site Functional Location (FLOC) is used to capture spatial coordinates from Key characteristics of active Grid and Primary sites — UK Power Networks. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction This dataset presents import aggregated consumption data from Smart Meter customers at the secondary substation level, along with the count of smart meters contributing to the aggregated half-hourly values. It includes both Active Energy Import and Reactive Energy Import readings.The sample comprises 10,000 records drawn from aggregated smart meter data across our three operational regions: Eastern Power Networks (EPN), London Power Networks (LPN), and South Eastern Power Networks (SPN). To access the historical data covering all sites, where there are more than 5 connected smart meters, please see the attached instructions or click here. Methodological ApproachPrimary consumption data for Active Energy Import is aggregated based on the number of active devices reporting during each half-hour period. If a device is unreachable during a given interval, its data is excluded from the aggregation to maintain accuracy. Quality Control Statement This dataset is being shared to provide an early preview of the type of data we intend to publish from all smart meters within our regions. We are conducting monthly validation checks to enhance data quality prior to releasing the full dataset. Users are advised to exercise caution when interpreting or utilizing this preliminary data. Assurance Statement The Smart Metering Team has reviewed the dataset to ensure consistency and accuracy in the presented data. Other Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal Glossary Download dataset information: Metadata (JSON)To view this data please register and login.42 days ago
- Introduction The Long Term Development Statement (LTDS) in Common Information Model (CIM) provides standardised network data that enables interoperability between electricity network analysis tools. It provides a common data format to represent electrical network components and their relationships. This allows consistent data exchange across different software tools, such as PowerFactory and IPSA. The LTDS in CIM comprises several profiles, each describing a specific characteristic of the distribution network. These profiles are defined in accordance with the Common Grid Model Exchange Standard (CGMES) and the IEC 61970 family of standards. For further details, please refer to Form of Long Term Development Statement (LTDS) with particular attention to LTDS Grid Modelling Annex 1 – Grid Modelling Guidelines and LTDS Grid Modelling Annex 2 – Data Exchange Specifications. The latest version of the appendix is available through BSI GB CIM Engagement Hub.Scope of Data Published The present iteration of the LTDS in CIM is limited to Equipment (EQ), Short Circuit (SC), Short Circuit Result (SCR), and System Capacity (SYSCAP) profiles, in line with the Stage 2 LTDS CIM publication structure. The scope of each published profile is summarised below: EQ profile defines the physical structure of the electricity distribution network, including substations, transformers, feeders, switches, and related connectivity. SC profile provides short-circuit characteristics required for fault level assessment. SCR profile contains the results of short-circuit studies. SYSCAP profile provides system capacity information, including firm capacity and non-coincident maximum loading data. UK Power Networks is responsible for operating within three distinct distribution licence areas: Eastern Power Networks plc (EPN), London Power Networks plc (LPN), and South Eastern Power Networks (SPN). The LTDS CIM publication provides profile data for each licence area, organised according to these operational boundaries. For a detailed understanding of the data scope published in the November 2025 LTDS cycle, users should refer to LTDS Stage 2 Publication Notes, which set out the specific content and limitations of the dataset. The supporting documentation can be found on our library using the following link: LTDS CIM Deliverables - May 2026 Shared Data Request Form This dataset has been triaged as 'Shared' (see attached data sharing risk assessment). To request access to this dataset, please register, login then complete the Shared Data Request Form Methodological Approach The models were developed by configuring all required LTDS CIM classes, attributes, and associations, while sensitive data was excluded to produce LTDS Stage 2 profiles. Conformity and Interoperability tests were performed iteratively to ensure usability, accuracy and alignment with the relevant standards. Quality Control Statement Quality control measures applied during the development of the LTDS CIM models include: Independent XML-based validation to confirm structural completeness and data exchange reliability. Application of the latest SHACL constraints to ensure compliance with current LTDS CIM schema requirements and guidance developed in coordination with Ofgem and the LTDS CIM Working Group, established under the ENA Data and Digitalisation Steering Group (DDSG) Work Programme. Assurance Statement The Network Insights Team collaborated closely with Data Interoperability Engineers and Modelling Engineers to ensure the LTDS CIM models meet the required standards of accuracy, consistency, and interoperability. This work was coordinated with Ofgem and the LTDS CIM Working Group, ensuring that all models published for the three licence areas reflect agreed methodologies and best practice. Other The LTDS Data Exchange Definition artefacts were developed to support Stage 1.3 of the CIM LTDS grid modelling. Publication notes were also produced to provide guidance on Stage 2 Profiles. All artefacts and notes for this release are available on the BSI Engagement Hub at: LTDS Stage 2 Publication Notes. For any further inquiries, please contact us at via email to networkinsights@ukpowernetworks.co.uk The dataset is updated every May and November in line with regulatory requirements and is intended to improve transparency, interoperability, and stakeholder engagement across the energy sector. You can download metadata information here: Eastern Power Networks (EPN)London Power Networks (LPN)South Eastern Power Networks (SPN) Alternatively, you can 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/22 days ago
- Introduction This dataset records all curtailment events experienced by curtailable-connection customers. About Curtailment When a generation customer requests a firm connection under a congested part of our network, there may be a requirement to reinforce the network to accommodate the connection. The reinforcement works take time to complete which increases the lead time to connect for the customer. Furthermore, the customer may need to contribute to the cost of the reinforcement works.UK Power Networks offers curtailable-connections as an alternative solution for our customers. It allows customers to connect to the distribution network as soon as possible rather than waiting, and potentially paying, for network reinforcement. This is possible because under a curtailable connection, the customer agrees that their access to the network can be controlled when congestion is high. These fast-tracked curtailable-connections can transition to firm connections once the reinforcement activity has taken place. Curtailable connections have enabled faster and cheaper connection of renewable energy generation to the distribution network owned and operated by UK Power Networks.The Distribution System Operator (DSO) team has developed the Distributed Energy Resource Management System (DERMS) that monitors curtailable-connection generators as well as associated constraints on the network. When a constraint reaches a critical threshold, an export access reduction signal may be sent to generators associated with that constraint so that the network can be kept safe, secure, and reliable.This dataset contains a record of curtailment actions we have taken and the resultant access reduction experienced by our curtailment-connections customers. Access reduction is calculated as the MW access reduction from maximum × duration of access reduction in hours (MW×h). The dataset categorises curtailment actions into 2 categories: Constraint-driven curtailment: when a constraint is breached, we aggregate the access reduction of all customers associated with that constraint. A constraint breach occurs when the network load exceeds the safe limit. Non-constraint driven curtailment: this covers all curtailment which is not directly related to a constraint breach on the network. It includes customer comms failures, non-compliance trips (where the customer has not complied with a curtailment instruction), planned outages and unplanned outages Each row in the dataset details the start and end times, durations and customer access reduction associated with a curtailment actions. We also provide the associated grid supply point (GSP) and nominal voltage to provide greater aggregation capabilities. By virtue of being able to track curtailment across our network in granular detail, we have managed to significantly reduce curtailment of our curtailable-connections customers. Methodological Approach A Remote Terminal Unit (RTU) is installed at each curtailable-connection site providing live telemetry data into the DERMS. It measures communications status, generator output and mode of operation. RTUs are also installed at constraint locations (physical parts of the network, e.g., transformers, cables which may become overloaded under certain conditions). These are identified through planning power load studies. These RTUs monitor current at the constraint and communications status. The DERMS design integrates network topology information. This maps constraints to associated curtailable connections under different network running conditions, including the sensitivity of the constraints to each curtailable connection. In general, a 1MW reduction in generation of a customer will cause <1MW reduction at the constraint. Each constraint is registered to a GSP.DERMS monitors constraints against the associated breach limit. When a constraint limit is breached, DERMS calculates the amount of access reduction required from curtailable connections linked to the constraint to alleviate the breach. This calculation factors in the real-time level of generation of each customer and the sensitivity of the constraint to each generator. Access reduction is issued to each curtailable-connection via the RTU until the constraint limit breach is mitigated. Multiple constraints can apply to a curtailable-connection and constraint breaches can occur simultaneously. Where multiple constraint breaches act upon a single curtailable-connection, we apportion the access reduction of that connection to the constraint breaches depending on the relative magnitude of the breaches. Where customer curtailment occurs without any associated constraint breach, we categorise the curtailment as non-constraint driven. Future developments will include the reason for non-constraint driven curtailment. Quality Control Statement The dataset is derived from data recorded by RTUs located at customer sites and constraint locations across our network. UKPN’s Ops Telecoms team monitors and maintains these RTUs to ensure they are providing accurate customer/network data. An alarms system notifies the team of communications failures which are attended to by our engineers as quickly as possible. RTUs can store telemetry data for prolonged periods during communications outages and then transmit data once communications are reinstated. These measures ensure we have a continuous stream of accurate data with minimal gaps. On the rare instances where there are issues with the raw data received from DERMS, we employ simple data cleaning algorithms such as forward filling. RTU measurements of access reduction update on change or every 30-mins in absence of change. We also minimise postprocessing of RTU data (e.g. we do not time average data). Using the raw data allows us to ascertain event start and end times of curtailment actions exactly and accurately determine access reductions experienced by our customers. Assurance Statement The dataset is generated and updated by a script which is scheduled to run daily. The script was developed by the DSO Data Science team in conjunction with the DSO Network Access team, the DSO Operations team and the UKPN Ops Telecoms team to ensure correct interpretation of the RTU data streams. The underlying script logic has been cross-referenced with the developers and maintainers of the DERMS scheme to ensure that the data reflects how DERMS operates. The outputs of the script were independently checked by the DSO Network Access team for accuracy of the curtailment event timings and access reduction prior to first publication on the Open Data Portal (ODP). The DSO Operations team conduct an ongoing review of the data as it is updated daily to verify that the operational expectations are reflected in the data. The Data Science team have implemented automated logging which notifies the team of any issues when the script runs. This allows the Data Science to investigate and debug any errors/warnings as soon as they happen. 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/ To view this data please register and login.22 days ago
- IntroductionUK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is distributing this electricity across our regions through circuits. Electricity enters our network through Super Grid Transformers at substations shared with National Grid we call Grid Supply Points. It is then sent at across our 132 kV Circuits towards our grid substations and primary substations. These circuits can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables. This dataset provides half-hourly current and power flow data across these named circuits from 2021 through to the previous month across our license areas. The data are aligned with the same naming convention as the LTDS for improved interoperability. Care is taken to protect the private affairs of companies connected to the 132 kV network, resulting in the redaction of certain circuits. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted. To find which circuit you are looking for, use the ‘ltds_line_name’ that can be cross-referenced in the 132kV Circuits Monthly Data, which describes by month what circuits were triaged, if they could be made public, and what the monthly statistics are of that site. If you want to download all this data, it is perhaps more convenient from our public sharepoint: Sharepoint This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets. Methodological Approach The dataset is not derived, it is the measurements from our network stored in our historian. The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps. We developed a data redactions process to protect the privacy of companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. This redaction process considers the correlation of all the data, of only corresponding periods where the customer is active, the first order difference of all the data, and the first order difference of only corresponding periods where the customer is active. Should any of these four tests have a high linear correlation, the data is deemed redacted. This process is not simply applied to only the circuit of the customer, but of the surrounding circuits that would also reveal the signal of that customer. The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation. Quality Control Statement The data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these measurements are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that. Assurance Statement Creating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS circuit from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same circuit in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing circuits, incorrectly labelled circuits, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible. Additional Information Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary. Download dataset information: Metadata (JSON)To view this data please register and login.22 days ago
- Introduction This table provides an overview of the data in the Appendix G. This is an aggregation of the data in the detailed Appendix G table. The first row is broken out into the second and third rows, and the Max Lead Time is derived from the connection dates in the appendix G. Methodological Approach Data is compiled from existing datashare between UK Power Networks and the National Energy System Operator. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies; and Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and DSO Regional Development Team worked together ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- IntroductionThis dataset shows the utilisation band of our secondary sites across our three networks, over 1 April 2024 to 31 March 2025. This dataset is a redacted version of an annual regulatory submission to Ofgem. The data consists of a single utilisation value over a year for each of UK Power Networks secondary substation. This dataset is redacted in that any secondary sites with five or less customers will not be included to protect privacy. This dataset is a mixture of actual utilisation data and analytics based on transformer profile. The utilisation bands do not indicate contractually committed capacity e.g. capacity on our network may be unused now but expected to be used by a connection in a future year, recent acceptances which will be covered in next year's data.If you notice any errors, please let us know by feedbacking against the record in the table tab. Methodological Approach UK Power Networks worked with other DNOs and the Energy Networks Association (ENA), to agree a methodology to calculating transformer utilisation. It considered the following: Transformer rating; Current peak loading; Year demand growth; Year ahead peak demand; and Utilisation calculation. Quality Control Statement This dataset is provided "as is". Assurance Statement The Open Data Team and DSO Network Strategy Team worked to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- Introduction A dataset showing the location of UK Power Networks' LV (Low Voltage) poles. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- IntroductionA dataset showing the location of UK Power Networks' 33kV poles and towers. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- Introduction This dataset provides a geospatial view of High Voltage (HV) Flexibility Zones where long-term flexibility services have been tendered for by UK Power Networks. The dataset presents HV Flexibility Zones by tender round, showing whether UK Power Networks was procuring flexibility to manage constraints in a zone relating to high demand (e.g. reduced consumption or increased generation at times of peak demand) or excess generation (e.g. increased consumption or reduced generation at times of excess renewable generation). It is intended to help flexibility service providers understand where long-term HV flexibility requirements have been located over time. For information on the historic delivery of flexibility services, please refer to the Flexibility Dispatches dataset Methodological ApproachEach HV Flexibility Zone is shown as a geographic area representing the location of a network constraint. Zones are linked to a specific tender round and indicate whether flexibility was sought for Demand or Generation constraints. These requirements reflect the requirements at the time the flexibility tender was run and may not represent current network needs. As part of the flexibility procurement process, individual meter points (MPANs) are checked to confirm final eligibility. This dataset provides an indicative view of where flexibility has been required by UK Power Networks in the past and does not confirm eligibility to participate in future tenders. Quality Control StatementThe dataset is subject to a series of quality control checks prior to publication. These include: Verification of Flexibility Zone boundaries and spatial accuracy Checks that Flexibility Zone names align with those used in other datasets on the Open Data Portal Consistency with zone naming used on Localflex and within competition data files published on the Tender Hub Assurance StatementThe High Voltage Flexibility Zones by Tender Round spatial map is reviewed prior to publication by a member of the Flexibility Markets team. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal Glossary To view this data please register and login.42 days ago
- Introduction The Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. This is Table 3a from our current LTDS report (published 29th May 2026), showing the observed substation peak demands with no correction for demand served by generation. This data has been transposed to show years as rows. More information and full reports are available from the landing page below: Long Term Development Statement and Network Development Plan Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the HV or LV Substation to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Data is transposed to show year as a value rather than a field - this allows the data to be viewed graphically. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. 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/22 days ago
- Introduction This table summarises the status of export connections at each GSP, giving the key summarised information from the Appendix G at a glance. The Transmission Backlog is a subset of the Total Generation Pipeline Capacity, with the earliest connection date being derived from the last person in the queue. Methodological Approach Data is compiled from existing datashare between UK Power Networks and the National Energy System Operator. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and DSO Regional Development Team worked together ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- Introduction This dataset provides the locations of areas that restrict the suitability of land for onshore wind developments; such as roads, residential areas, world heritage sites, agricultural land, and flood zones. In addition, it calculates the potential energy density of over 3.5 million individual areas for both solar and wind installations using windspeed and solar irradiance data.This results in an overall assessment of the suitability of a specific area for installing solar and wind generation. The assessment grades land as either YES – suitable, No – not suitable, or MAYBE – could be suitable. Methodological Approach This dataset was developed for UK Power Networks licence area by UEA Consulting Limited. It is based on public domain sources and previous analysis that was carried out as part of the IRENES EU Interreg project which examined renewable energy sources in eastern England.To view the methodology behind this data please click here.This dataset displays the wind data, click here for the solar PV data Quality Control Statement This dataset is provided "as is". Assurance Statement The Open Data Team and Local Net Zero Team worked together to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- IntroductionDataset providing visibility of UK Power Network’s demand forecasts for its GSPs over the next eight years, across the four different demand scenarios. No tertiary connections or other transmission-connected parties have been considered in this forecast, which is based only on demand from our Distribution network. For GSPs shared with other DNOs, the data provides only UK Power Networks demand.Forecasts are submitted annually to NESO and NGET to support network planning efforts.Methodological ApproachThis dataset combines the demand forecast performed at 56 of our substations. As each forecast has been performed individually (but not in isolation), we collected the information of the different documents containing the forecasts and presented them under this dataset. This was a process carried out via a script.Assurance Statement We performed sample checks to ensure the script combining information from the different documents remained accurate. 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/ To view this data please register and login.22 days ago
- Introduction The soil dataset includes multi-layer soil resistivity values for geographic locations near Grid and Primary substations. This data can be used in substation earthing system design. For further information on earthing refer to UK Power Networks' earthing standard EDS 06-0001 available from our website https://g81.ukpowernetworks.co.uk/. Please send any enquiries related to the dataset to earthingenquiries@ukpowernetworks.co.uk. Methodological Approach Soil data is uploaded from UK Power Networks' data warehouse. Site Functional Locations (FLOCs) are used to associate soil data to UK Power Networks Grid and Primary Sites Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- IntroductionAnnex 1 contains the charges to Low Voltage (LV), High Voltage (HV) Designated Properties and Unmetered Supplies (UMS). Methodological Approach This dataset was extracted and compiled from UK Power Networks Distribution Use of System charges webpage, into a dataset. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/22 days ago
- Introduction UK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is the stepping down of voltage as it is moved towards the household; this is achieved using transformers. Transformers have a maximum rating for the utilisation of these assets based upon protection, overcurrent, switch gear, etc. This dataset contains the Primary Substation Transformers, that typically step-down voltage from 33kVto 11kV (occasionally from 132kV to 11kV). These transformers can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables. This dataset provides half-hourly current and power flow data across these named transformers, in our South Eastern region, from 2021 through to the previous month across our license areas. The data are aligned with the same naming convention as the LTDS for improved interoperability.Care is taken to protect the private affairs of companies connected to the 11kV network, resulting in the redaction of certain transformers. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted. To find which transformer you are looking for, use the ‘tx_id’ that can be cross referenced in the Primary Transformers Monthly Dataset, which describes by month what transformers were triaged, if they could be made public, and what the monthly statistics are of that site. If you want to download all this data, it is perhaps more convenient from our public sharepoint: Open Data Portal Library - Primary Transformers - All Documents (sharepoint.com)This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets. Methodological Approach The dataset is not derived, it is the measurements from our network stored in our historian.The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps.We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. Where the primary transformer has 5 or fewer customers, we redact the dataset.The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation. Quality Control Statement The data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these transformers are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that. Assurance Statement Creating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS transformer from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same transformer in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing transformers, incorrectly labelled transformers, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible. Additional information Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary. Download dataset information: Download dataset information: Metadata (JSON) We would be grateful if you find this dataset useful to submit a “reuse” case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. Click here for more information: Open Data Portal Reuses — UK Power NetworksTo view this data please register and login.22 days ago
- IntroductionThis dataset presents the outcome of Connections Reform, aggregated for each of the 133 local authorities within UK Power Networks licence areas. It provides visibility of the original export capacity that was eligible as part of Connections Reform, together with the capacity in the revised transmission queue. Overall connected capacity in the area is provided, in addition to the sum of connected and accepted to connect export capacity from renewable and storage sources in the revised queue. The latter is intended to provide insight into Local Authorities targets. Renewable sources are defined as Solar, Onshore and Offshore Wind and Low Carbon Dispatchable Power. Methodological Approach Connected and accepted projects across the UK Power Networks' licence area have been mapped, through their postcodes, to one of the 133 local authorities within our regions. For each local authority, the aggregated value of connected, eligible and customers now in the queue has been provided. Quality Control Statement The process has been peer reviewed by members of the team. In addition, to prevent individual project identification, local authorities with at least one project eligible for connections reform and with "Export capacity now in the transmission queue (MW)" values equal to 0 or "Eligible export capacity for Connections Reform (MW)" have been blanked. Assurance Statement The Open Data Team and DSO Regional Development Team worked together ensure data accuracy and consistency. OtherDownload 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/To view this data please register and login.42 days ago
- IntroductionThe Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. This is Table 3a from our current LTDS report (published 29th May 2026), showing the observed substation peak demands with no correction for demand served by generation. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the Substation to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. 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/ To view this data please register and login.22 days ago
- IntroductionFollowing an ESO (Electricity System Operator) and NGET (National Grid Electricity Transmission) assessment, some GSPs (Grid Supply Points) may be identified as having a need to place technical requirements or protection schemes on their generation. Methodological Approach Data is compiled from existing datashare between UK Power Networks and the National Energy System Operator. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and DSO Regional Development Team worked together ensure data accuracy and consistency. OtherDownload 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/To view this data please register and login.22 days ago
- The earthing fault level dataset includes the three-phase and single-phase to earth fault levels for all Grid (132kV, 66kV, 33kV) and Primary (33kV, 20kV, 11kV, 6.6kV) substations based on the UK Power Networks Long Term Development Statement (LTDS). This data can be used in substation earthing system design and assessment. For further information on earthing refer to UK Power Networks' earthing standard EDS 06-0001 available from our website https://g81.ukpowernetworks.co.uk/. Please send any enquiries related to the dataset to earthingenquiries@ukpowernetworks.co.uk Methodological Approach Fault level data is uploaded from UK Power Networks' data warehouse. Site Functional Locations (FLOCs) are used to associate fault level data to UK Power Networks Grid and Primary Sites Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- Introduction This dataset shows the capacity of operational and pipeline data centres in local authority districts that UK Power Networks has projects in. This list has been determined using internal systems UK Power Networks uses to manage all committed projects in the process of connecting to our network, and authoritative open data provided by the Office for National Statistics (ONS). To protect the identity of the sites, only capacities (in megavolt amperes, or MVA) have been disclosed and are aggregated at the local authority district level. Methodological Approach Operational and pipeline data centre projects are identified through desktop exercises using UK Power Networks' internal customer relationship management system and extracted. Operational data centres were identified using internal desktop exercises and corroboration with external sources. Pipeline data centre projects are projects that have accepted their connection offer, paid the application fee and have been committed to our delivery plans. Using the ONS' authoritative dataset named "ONS Postcode Directory (February 2025) for the UK", a local authority district is allocated to each data centre project based on its postcode provided to UK Power Networks in the application stage.Using the ONS' authoritative dataset named "Local Authority District to County and Unitary Authority (April 2025) Lookup in the UK (V2)", a county or unitary authority is allocated to each local authority district. Capacities for both connected and pipeline data centres (in MVA) are then summed up to local authority district level. The resultant capacity figures are then cross-checked to ensure all projects matched on to a local authority district. Any discrepancies are manually reviewed. Quality Control Statement Quality Control Measures include: The dataset is primarily built upon internal data, relating to data centre projects in UK Power Networks' licence areas. Data have been checked with both automatic and manual validation methods. Assurance Statement The dataset is generated through a manual process, conducted by the Distribution System Operator's Regional Development Team. The dataset will be reviewed quarterly to assess any changes, and to determine if any updates to the methodology are necessary. This process ensures that the dataset remains relevant and reflective of the data centre projects UK Power Networks is aware of. To protect the identity of the sites, only capacities (in megavolt amperes, or MVA) have been disclosed and are aggregated at the local authority district level so as not to disclose the identity of any one person or business. 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/To view this data please register and login.22 days ago
- Introduction The Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. Long Term Development Statement Table 8 indicates any Fault Level restrictions or mitigations in place at our Grid and Primary substations. Published 29th May 2026. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the Substation to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- Introduction National Grid sites (Transmission System) that feed UK Power Networks' Primary substations (Distribution System). Methodological Approach This was created internally by combining the primary feeding areas according to which Grid Supply Point is upstream. Quality Control Statement Quality Control Measures include: Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction This dataset presents import aggregated consumption data from Smart Meter customers at the secondary substation and LV Feeder level, along with the count of smart meters contributing to the aggregated half-hourly values. It includes both Active Energy Import and Reactive Energy Import readings.The sample comprises 10,000 records drawn from aggregated smart meter data across our three operational regions: Eastern Power Networks (EPN), London Power Networks (LPN), and South Eastern Power Networks (SPN).To access the historical data covering all sites, where there are more than 5 connected smart meters, please see the attached instructions or click here Methodological Approach Primary consumption data for Active Energy Import is aggregated based on the number of active devices reporting during each half-hour period. If a device is unreachable during a given interval, its data is excluded from the aggregation to maintain accuracy. Quality Control Statement This dataset is being shared to provide an early preview of the type of data we intend to publish from all smart meters within our regions. We are conducting monthly validation checks to enhance data quality prior to releasing the full dataset. Users are advised to exercise caution when interpreting or utilizing this preliminary data. Assurance Statement The Smart Metering Team has reviewed the dataset to ensure consistency and accuracy in the presented data. Other Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal Glossary Download dataset information: Metadata (JSON)To view this data please register and login.42 days ago
- Introduction The Embedded Capacity Register (ECR), formerly known as the System Wide Resource Register (SWRR), lists all generation, storage and flexible demand resources where the installed generation capacity, export capacity or the import capacity is greater than or equal to 1MW. The ECR dataset provides comprehensive information about generation, storage, and flexible demand resources connected to the electricity distribution network. This dataset is crucial for understanding the capacity and distribution of these resources across different licence areas. It includes key characteristics: Export MPAN/MSID: Unique identifier for the export meter point administration number or meter serial identifier. Import MPAN / MSID: Unique identifier for the import meter point administration number or meter serial identifier. Customer Name: Name of the customer associated with the resource. Location Coordinates: Eastings and Northings coordinates for the resource location. Primary: The primary substation associated with the resource. Energy Source and Conversion Technology: Details about the energy source (e.g., solar, wind) and the conversion technology used (e.g. photovoltaic, wind turbine). Transformer ratings Methodological Approach Data Collection: The data is sourced from various internal systems, including the data warehouse and other operational databases. This ensures comprehensive coverage of all relevant resources. Data Integration: The collected data is integrated and organized to provide a clear view of the capacity and distribution of these resources across different license areas. This includes details such as location coordinates, energy source, conversion technology, and associated substations. Quality Control Statement The data is provided "as is". Assurance Statement We are aware that not all cells are fully populated on the ECR, we are working hard to gather and check data so that we can provide the missing information as soon as possible. If you do notice any errors or omissions please email us at DG-Q&A@ukpowernetworks.co.uk. Other More information can be found here: https://ukpowernetworks.opendatasoft.com/pages/embedded_capacity_register/ 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/To view this data please register and login.42 days ago
- Introduction This is the detail in the Appendix G. The position has been derived from the point the customer accepted their connection, and the date of connection is based on the agreement with the customer and the ESO. The connection status highlights if the customer is able to connect, or if they are held back by transmission constraints. Methodological Approach Data is compiled from existing datashare between UK Power Networks and the National Energy System Operator. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies; and Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and DSO Regional Development Team worked together ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- Introduction Volume of Domestic Low Carbon Technologies (LCT) for both generation and demand (under 1MW) connected. Methodological ApproachLCT application data (which captures, amongst other things, the location, LCT type, and capacity) is taken from our Smart Connect portal at https://www.ukpowernetworks.co.uk/smart-connect; Using the Postcode of the MPAN (Meter Point Administration Number), we map the data to LSOA using Office for National Statistics datasets which are updated annuallyContains lower layer super output area (LSOA) codes and name data sourced from the Office for National Statistics licensed under the Open Government Licence v.3.0 Quality Control Statement Quality Control Measures include a manual review and correction of data inconsistencies. Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction The dataset captures yearly generation profiles for different generation technology types, used by UK Power Networks to run export curtailment assessment studies. UK Power Networks has been running curtailment studies since 2014 in the three licence areas and have been using standards technology specific profiles to model the accepted not yet connected generation capacity. Generation specific profile include the following generation types: solar photovoltaic, wind, battery and non-variable generation. The profiles have been developed using actual generation data from connected sites within UK Power Networks licence areas falling into each of the generation 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 export capacity. The profiles are revised on a regular basis to ensure that they represent as closely as possible the operational behaviour of unconnected sites. The following change have taken place since UK Power Networks has started issuing curtailment reports: The solar profile was updated in 2019/2020 and capacity factor was increased from 13.2% to 14.2%; The electricity storage profiles were updated in April 2024. new profiles available:“Storage_export_enhanced” and “Storage_import_enhanced”; Gas profiles were updated in September 2024 differentiating between small and large gas generators. Methodological Approach This section outlines the methodology for generating annual half-hourly demand profiles. Connected metered generators falling in each of the categories have been used to create the representative profiles. Historical data from each of these connected generation sites are retrieved from UK Power Networks’ Remote Terminal Unit (RTU) and consist of annual half-hourly meter readings. The profiles are averages of power/capacity at every time period i.e.: Paverage,t = average(P1,tc1 + P2,tc2 + … + Pn,tcn) where t is time, 30 minutes resolution for one year; P is the export in MW from sites 1, 2, ..., n; and c is capacity of site 1, 2, ..., n. If there was bad/missing data then PVSYST and local meteorological data were used. Electricity Storage profiles For export/generation studies, storage is modelled as constantly exporting with a varying profile throughout the day, whereas for demand/import studies, storage is modelled as constantly importing with a varying import profile throughout the day. This represent a conservative view, which is used due to the unpredictable pattern of Electricity Storage sites The solar and storage combined profile is calculated as the maximum of the storage and solar profiles during each 30-minute timestamp. Storage profiles are detailed in our design standard Engineering Design Standard (EDS 08-5010). Storage profiles were updated in April 2024 based following a piece of work delivered by Regen to UK Power Networks on the operational behaviour of battery storage, with the purpose to model reflect battery storage more realistically in curtailment studies . the revised profile are “Storage_export_enhanced” and “Storage_import_enhanced”. Curtailment reports issued prior to 22 April 2024 were produced using the legacy storage profiles (“Storage”). Gas Profiles Gas profiles were updated in September 2024 to provide a more representative view on how gas generator operate and to enable more representative curtailment results. The legacy profile used to model unconnected gas generators until September 2024 was the “non-variable” profiles. From September 2024, unconnected gas generators are modelled using new “Gas_large” and “Gas_small” profile. The two profiles are meant to capture the differences between smaller genset, quickly ramping up from 0 to maximum capacity, and larger gas generators that rather have a more stable behaviour. The profile have been created with the same equation described above, taking a percentile between 95 and 98, rather than the average. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and DSO Data Science worked together to ensure data accuracy and consistency. 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/22 days ago
- Introduction UK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is distributing this electricity across our regions through circuits. Electricity enters our network through Super Grid Transformers at substations shared with National Grid we call Grid Supply Points. It is then sent at across our 132 kV Circuits towards our grid substations and primary substations. These circuits can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables . Care is taken to protect the private affairs of companies connected to the 132 kV network, resulting in the redaction of certain circuits. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted. This dataset provides monthly statistics across these named circuits from 2021 through to the previous month across our license areas. The data is aligned with the same naming convention as the LTDS for improved interoperability. To find half-hourly current and power flow for the circuit you are looking for, use the ‘ltds_line_name’ that can be cross referenced in the 132kV Circuits Half Hourly Data. If you want to download all this data, it is perhaps more convenient from our public sharepoint: Sharepoint This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets. Methodological Approach The dataset is not derived, it is the measurements from our network stored in our historian. The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps. We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. This redaction process considers the correlation of all the data, of only corresponding periods where the customer is active, the first order difference of all the data, and the first order difference of only corresponding periods where the customer is active. Should any of these four tests have a high linear correlation, the data is deemed redacted. This process is not simply applied to only the circuit of the customer, but of the surrounding circuits that would also reveal the signal of that customer. The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation. Quality Control Statement The data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these measurements are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that. Assurance Statement Creating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS circuit from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same circuit in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing circuits, incorrectly labelled circuits, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible. Additional Information Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary. Download dataset information: Metadata (JSON) We would be grateful if you find this dataset useful to submit a “reuse” case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. For more information click here: Open Data Portal Reuses — UK Power NetworksTo view this data please register and login.22 days ago
- IntroductionLocal area energy planning (LAEP) is fundamental in achieving net zero objectives. Following direct engagement with key stakeholders, 30 use cases were identified within a set of defined data themes. This dataset details those use cases and contains links to the data and / or information required which can be found in the Net Zero Use Cases and Data Requirements dataset. Methodological Approach This dataset is manually updated as and when there is an update. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Local Net Zero Team worked together to ensure data accuracy and consistency. 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/22 days ago
- Introduction This dataset contains the terms and definitions included on the UKPN Open Data Portal Glossary Page. Methodological Approach This dataset is sourced from UK Power Networks internal business glossary. Quality Control Statement Quality Control Measures include: Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Data Governance Team worked together to ensure data accuracy and consistency. Other UKPN Open Data Portal Glossary helps ensure common understanding of terms, used or related to the datasets published on UKPN Open Data Portal. 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/22 days ago
- IntroductionPlease note, this dataset has now been archived. Our more granular Data Centre Demand Profiles dataset can still be found on our data catalogue.*** This dataset shows the maximum observed utilisations of operational data centres identified in UK Power Networks' region. The utilisations have been determined using actual demand data from connected sites within UK Power Networks licence areas, from 1 January 2023 onwards. Maximum utilisations are expressed proportionally, by comparing the maximum half-hourly observed import power seen across the site's meter point(s), against the meter's maximum import capacity. Units for both measures are apparent power, in kilovolt amperes (kVA). To protect the identity of the sites, data points have been anonymised and only the site's voltage level information has been provided - and our estimation of the data centre type - has been provided. Methodological Approach Over 100 operational data centre sites (and at least 10 per voltage level) were identified through internal desktop exercises and corroboration with external sources. After identifying these sites, their addresses and their MPAN(s) (Meter Point Administration Number(s)) were identified using internal systems. Half-hourly smart meter import data were retrieved using internal systems. This included both half-hourly meter data, and static data (such as the MPAN's maximum import capacity and voltage group, the latter through the MPAN's Line Loss Factor Class Description). Half-hourly meter import data came in the form of active and reactive power, and the apparent power was calculated using the power triangle. In cases where there are numerous meter points for a given data centre site, the observed import powers across all relevant meter points are summed, and compared against the sum total of maximum import capacity for the meters. The maximum utilisation for each site was determined via the following equation (where S = Apparent Power in kilovolt amperes (kVA)): % Maximum Observed Utilisation = MAX(SUM( SMPAN Maximum Observed Demand)) SUM( SMPAN Maximum Import Capacity) Quality Control Statement The dataset is primarily built upon customer smart meter data for connected customer sites within the UK Power Networks' licence areas. The smart meter data that is used is sourced from external providers. While UK Power Networks does not control the quality of this data directly, these data have been incorporated into our models with careful validation and alignment. Any missing or bad data has been addressed though robust data cleaning methods, such as omission. Assurance Statement The dataset is generated through a manual process, conducted by the Distribution System Operator's Regional Development Team. The dataset will be reviewed quarterly - both in terms of the operational data centre sites identified, their maximum observed demands and their maximum import capacities - to assess any changes and determine if updates of demand specific profiles are necessary. This process ensures that the dataset remains relevant and reflective of real-world data centre usage over time. There are sufficient data centre sites per voltage level to assure anonymity of data centre sites. Other Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: https://ukpowernetworks.opendatasoft.com/pages/glossary/Download dataset information: Metadata (JSON)To view this data please register and login.22 days ago
- Introduction The Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. Long Term Development Statement Table 6 indicates the level of new connections interest at each Primary substation. Published 29th May 2026. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the Site to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction This dataset provides Sensitivity Factors (SFs) for UK Power Networks' three licence areas. SFs represent the marginal impact of a power injection at a node on the network to branches (lines or transformers) elsewhere. They provide a simplified, linearised way of modelling the marginal impact of a MW generated in one part of the network on key constraints and are therefore widely used to model distributed energy resources (DERs) on the network. This analysis can be critical to developers assessing new projects.This dataset is calculated under an Export scenario of maximum generation and minimum demand. Please see the SFs (Import) dataset for sensitivity factors conducted under maximum demand, minimum generation conditions. Methodology SFs are calculated in PowerFactory based on an AC load flow. When calculating SFs for lines/cables/circuits, SFs are calculated between the node, which is where the import/export of power will take place, and the branch, which is where the change in power will be felt. For example, 1 MW injected at the node would have 0.8 MW decrease at the branch if the SF between the node and branch is -0.8. For transformers, we model between the HV node and the LV node. The SF values given are a fraction, dP/dP, that is, the increase or decrease in MW flow along the branch, resulting from a 1 MW active power injection at the node. The SFs are calculated under static network conditions and in intact running arrangements. They are a useful approximation of network suitable for modelling purposes, but do not reflect the real-time variability resulting from changing running arrangements and network loading. SFs are calculated on a per-Grid Supply Point basis: SFs are not provided between nodes and branches in different Grid Supply Points. Interoperability This dataset is interoperable with our Long Term Development Statement (LTDS) publications. Nodes can be matched with LV or HV node names in Tables 2a and 2b, while branches can be linked with the lines reported in Table 1 and transformers in Tables 2a and 2b. Using these datasets, users can retrieve asset ratings to assist curtailment studies. Quality Control Statement This dataset is subjected to algorithmic tests to ensure the data is clean. In addition, interoperability tests ensure that the dataset can be linked with tables from the Long Term Development Statement, also available on the Open Data Portal. Assurance Statement Sensitivity Factors are produced by UK Power Networks engineers, based on up-to-date PowerFactory models. The data is also reviewed by DSO data scientists before publication on the Open Data Portal. 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/To view this data please register and login.22 days ago
- Introduction Shapefile showing the areas within UK Power Networks' three licence areas which have flood warnings. This dataset will be updated quarterly, with the last refresh in 15 July 2025. Methodological Approach Data Extraction and Cleaning: Data is downloaded from DEFRA data portal. Data Filtering and Assignment: Only flood areas/warnings related to UK Power Networks service area are included. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team has checked this to ensure data accuracy and consistency. Other Contains public sector information licensed under the Open Government Licence v3.0. 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/42 days ago
- Introduction UK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is distributing this electricity across our regions through circuits. Electricity enters our network through Super Grid Transformers at substations shared with National Grid we call Grid Supply Points. It is then sent at across our 132 kV Circuits towards our grid substations and primary substations. From there, electricity is distributed along the 33 kV circuits to bring it closer to the home. These circuits can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables. This dataset provides half-hourly current and power flow data across these named circuits from 2021 through to the previous month in our South Eastern Power Networks (SPN) licence area. The data are aligned with the same naming convention as the LTDS for improved interoperability. Care is taken to protect the private affairs of companies connected to the 33 kV network, resulting in the redaction of certain circuits. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted. To find which circuit you are looking for, use the ‘ltds_line_name’ that can be cross referenced in the 33kV Circuits Monthly Data, which describes by month what circuits were triaged, if they could be made public, and what the monthly statistics are of that site. If you want to download all this data, it is perhaps more convenient from our public sharepoint: Sharepoint This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets. Methodological Approach The dataset is not derived, it is the measurements from our network stored in our historian. The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps. We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. This redaction process considers the correlation of all the data, of only corresponding periods where the customer is active, the first order difference of all the data, and the first order difference of only corresponding periods where the customer is active. Should any of these four tests have a high linear correlation, the data is deemed redacted. This process is not simply applied to only the circuit of the customer, but of the surrounding circuits that would also reveal the signal of that customer. The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation. Quality Control Statement The data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these measurements are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that. Assurance StatementCreating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS circuit from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same circuit in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing circuits, incorrectly labelled circuits, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible. Additional Information Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary. Download dataset information: Metadata (JSON)We would be grateful if you find this dataset useful to submit a “reuse” case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. Click here for more information: Open Data Portal Reuses — UK Power Networks To view this data please register and login.22 days ago
- IntroductionVolume of Low Carbon Technologies (LCT) for both generation and demand (under 1MW) connected to UK Power Networks by Primary Substation. Includes primary site spatial coordinates and covers LCT types: EV Charging Point; Heat Pump; Hydro; Combined Heat and Power; Solar, Wind; and Battery Storage among others.Please note that where the volume of LCT Connections by Type is 5 or less by primary site, these records have been removed. Methodological Approach LCT application data (which captures, amongst other things, the location, LCT type, and capacity) is taken from our Smart Connect portal at https://www.ukpowernetworks.co.uk/smart-connect. Using the MPAN (Meter Point Administration Number), we look up our connectivity model to ascertain the upstream connecting secondary and primary substations. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- IntroductionShapefile showing operational boundaries in the UK Power Networks Eastern Power Networks (EPN) area. Methodological Approach This dataset was extracted from UK Power Networks' internal geospatial mapping database - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/42 days ago
- Introduction The Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. This is Table 4b from our current LTDS report (published 29th May 2026), showing the earth fault level at each Grid and Primary substation. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the Substation to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and Network Insights Team together ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- ******** Please note, the vectorisation programme for Eastern Power Networks (EPN) has concluded. As such, this dataset has expired but the catalogue card will remain. Introduction The GIS (Geographic Information System) vectorisation project will deliver the incremental digital conversion of our legacy geospatial network records. This dataset defines the sub-areas which will be incrementally delivered, detailing corresponding current status and planned completion dates. This allows users to understand the current and future coverage of digital geospatial network records as the project progresses. Methodological Approach Progress against a defined project plan is captured and updated throughout the day. A script is run to convert into a shapefile. This shapefile is then uploaded onto the Open Data Portal. Quality Control Statement This dataset is provided "as is". Assurance Statement The Open Data Team has checked outputs to validate. 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/22 days ago
- IntroductionHigh level statistics for each Licence Area taken from the Regulatory Instructions and Guidance (RIGs) submission 2024 / 2025. Methodological Approach This dataset was compiled from UK Power Networks annual Regulatory Information and Guidance submissions to Ofgem. This is refreshed every year. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and the Asset Information Reporting team worked together to ensure data accuracy and consistency. 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/22 days ago
- Introduction The Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. This is Table 3b from our current LTDS report (published 29th May 2026), showing the true substation peak demands with correction added for demand served by generation. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the From Substation to Grid and Primary Sites ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.22 days ago
- Introduction The Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. This is Table 2a from our current LTDS report (published 29th May 2026), showing the Transformer information for two winding (1x High Voltage, 1x Low Voltage) transformers associated with each Grid and Primary substation where applicable. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the Substation where the transformer is located to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.22 days ago
- National Parks are run by National Park Authorities for the purpose of conserving and enhancing the natural beauty, wildlife and cultural heritage and to provide opportunities for the understanding and enjoyment of the Park by the public.This dataset is restricted to the UK Power Networks' three licence areas. Methodological approach Download and ingestions: That dataset was downloaded from the Department for Environment Food and Rural Affairs data portal, and ingested into this data portal. Quality Control Statement This dataset is provided "as is". Assurance Statement The Open Data Team has reviewed the dataset to ensure it is true to source. 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/42 days ago
- Introduction Generation above 100 MW connecting or contracted to connect to UK Power Networks distribution network. Please note that, due to the effect of some legacy generators, there are five schemes above 100MW which are contained in the Appendix G, which would not be included in this generation list. This has been done to keep consistency with the signed contracts with the National Energy System Operator (NESO). Methodological Approach Showing all connected generation above 100MW (which are not already quoted in the Appendix G), and including all contracted generation above 100MW, be it part of a contract with NESO or still awaiting an application. Quality Control Statement The data is provided "as is". Assurance Statement The data domain owners have checked their respective data aspects. 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/To view this data please register and login.22 days ago
- IntroductionShapefile showing the UK Power Networks boundary.Click here to see the areas we cover. Methodological Approach This dataset was extracted from UK Power Networks' geospatial system - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data Team reviewed this to ensure data accuracy and consistency. 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/42 days ago
- Introduction Daily Demand Statistics (Minimum, Average, Maximum) for Grid Supply Point (GSP). It includes aggregated GSP Data for all the monitored GSPs, and it also includes SGT data if we have used those for the creation of aggregated data. Data includes Voltages, Current, Active Power, and Reactive Power, and is populated from 2021 onwards to the current day. This dataset shows data from a sample of GSPs which account for 1/5th of the total GSPs in our area (we will add more sites across the network in the future). This data is refreshed every day at midnight. The data is published as is from the network. Methodological Approach The power flow data is streamed from our PI server into an FTP server before being published on the Open Data Portal. To streamline and enable faster data refresh, we have structured our data into a header file which is light. Quality Control Statement The data is published as is from the network. Assurance Statement The Open Data Team and DSO Data Science Team worked together to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.22 days ago
- Introduction This dataset provides Sensitivity Factors (SFs) for UK Power Networks' three licence areas. SFs represent the marginal impact of a power injection at a node on the network to branches (lines or transformers) elsewhere. They provide a simplified, linearised way of modelling the marginal impact of a MW generated in one part of the network on key constraints and are therefore widely used to model distributed energy resources (DERs) on the network. This analysis can be critical to developers assessing new projects. This dataset is calculated under an Import scenario of maximum demand and minimum generation. Please see the SFs (Export) dataset for sensitivity factors conducted under maximum generation, minimum demand conditions. Methodology: SFs are calculated in PowerFactory based on an AC load flow. When calculating SFs for lines/cables/circuits, SFs are calculated between the node, which is where the import/export of power will take place, and the branch, which is where the change in power will be felt. For example, 1 MW injected at the node would have 0.8 MW decrease at the branch if the SF between the node and branch is -0.8. For transformers, we model between the HV node and the LV node. The SF values given are a fraction, dP/dP, that is, the increase or decrease in MW flow along the branch, resulting from a 1 MW active power injection at the node. The SFs are calculated under static network conditions and in intact running arrangements. They are a useful approximation of network suitable for modelling purposes, but do not reflect the real-time variability resulting from changing running arrangements and network loading. SFs are calculated on a per-Grid Supply Point basis: SFs are not provided between nodes and branches in different Grid Supply Points. Interoperability: This dataset is interoperable with our Long Term Development Statement (LTDS) publications. Nodes can be matched with LV or HV node names in Tables 2a and 2b, while branches can be linked with the lines reported in Table 1 and transformers in Tables 2a and 2b. Using these datasets, users can retrieve asset ratings to assist curtailment studies. Quality Control Statement This dataset is subjected to algorithmic tests to ensure the data is clean. In addition, interoperability tests ensure that the dataset can be linked with tables from the Long Term Development Statement, also available on the Open Data Portal. Assurance StatementSensitivity Factors are produced by UK Power Networks engineers, based on up-to-date PowerFactory models. The data is also reviewed by DSO data scientists before publication on the Open Data Portal. 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/To view this data please register and login.22 days ago
- IntroductionAnnex 2 contains the charges to Designated Extra High Voltage (EHV) Properties and charges applied to Licensed Distribution Network Operators (LDNOs) with Designated EHV Properties/end-users embedded in networks within the UK Power Networks licence areas. Methodological Approach This dataset was extracted and compiled from UK Power Networks Distribution Use of System charges webpage, into a dataset. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/22 days ago
- Introduction Generation customers connected to UK Power Networks can be subjected to curtailment through our Distributed Energy Resource Management System (DERMS) if they accepted a curtailable-connection. During periods of network congestion, these DERS will have their access reduced to mitigate network constraint breaches. Their reduction is organised according to their connection application date in a last-in first-out (LIFO) arrangement. The Constraints Real Time Meter Readings dataset on the Open Data Portal (ODP) gives a near real time status of the constraints on our network that are used by DERMS to reduce access. This API accessible dataset can be used to see just how congested the network is, and for the specific DER operators themselves, they have access and visibility to the constraints of their specific site. The dataset contains a timestamp, the constraint identifier, the most recent current reading in amps, the trim and release limits (curtailment starts at the trim and ends at the release), whether the site is in breach, a description of the constraint, and (only if you have access) the name of the DER. The dataset updates as close to real time as is possible. Our scheduling is as follows: At 15s past the minute mark, we scrape the network data and push it to the ODP server On the minute mark, the ODP runs an update to refresh the dataset The dataset refresh is completed between 5-15s past the minute mark Only after this refresh has completed can you get the latest values from the ODP You can run this notebook to see the dataset in action: https://colab.research.google.com/drive/1Czx98U6zttlA3PC2OfI_0UzAbE48BvEq?usp=sharing Methodological Approach A Remote Terminal Unit (RTU) is installed at each curtailable-connection site providing live telemetry data into the DERMS. It measures communications status, generator output, and mode of operation. RTUs are also installed at constraint locations (physical parts of the network, e.g., transformers, cables which may become overloaded under certain conditions). These are identified through planning power load studies. These RTUs monitor current at the constraint and communications status. The DERMS design integrates network topology information. This maps constraints to associated curtailable connections under different network running conditions, including the sensitivity of the constraints to each curtailable connection. In general, a 1MW reduction in generation of a customer will cause <1MW reduction at the constraint. Each constraint is registered to a GSP. DERMS monitors constraints against the associated breach limit. When a constraint limit is breached, DERMS calculates the amount of access reduction required from curtailable connections linked to the constraint to alleviate the breach. This calculation factors in the real-time level of generation of each customer and the sensitivity of the constraint to each generator. Access reduction is issued to each curtailable-connection via the RTU until the constraint limit breach is mitigated. Multiple constraints can apply to a curtailable-connection and constraint breaches can occur simultaneously. Where multiple constraint breaches act upon a single curtailable-connection, we apportion the access reduction of that connection to the constraint breaches depending on the relative magnitude of the breaches. Where customer curtailment occurs without any associated constraint breach, we categorize the curtailment as non-constraint driven. Future developments will include the reason for non-constraint driven curtailment. Quality Control Statement Quality Control Measures include: Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The DSO Data Science Team checked to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- Introduction Narrative for each Grid Supply Point to be shown on the Network Operational Data Dashboard. Methodological Approach Manually pulled together by the DSO. Quality Control Statement Verified by the DSO prior to publication. Assurance Statement The Open Data Team and DSO Regional Development Team worked together ensure data accuracy and consistency. OtherDownload 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/To view this data please register and login.22 days ago
- Introduction This dataset is a feed from UK Power Networks' Distribution Network Management System - ADMS, showing near real time power cut (fault) data. It includes planned and unplanned power cuts. Users will be able to consume live fault data via API. Methodological Approach Data Extraction: Fault data is queried from our PowerOn system. Data Cleaning: Any fault which contains five or less customers, and can not be aggregated have been omitted. Geopoint Creation: These are created from aggregated post code data to protect individual customer privacy. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/42 days ago
- IntroductionUK Power Networks Network Scenario Headroom Report (NSHR) is part of the Network Development Plan (NDP). The full NDP is published every other year, and the NSHR is updated annually.The NSHR indicates the available headroom capacity in MW for demand and generation on UK Power Networks Grid and Primary substations up to 2050. It shows where reinforcement or procurement of flexibility services are needed. Since the report indicates unused substation capacity in each year, please note unused capacity may be contractually committed to customers. Those seeking connection should contact our connections gateway to understand the latest view of available capacity.The 1 May 2026 DFES NSHR dataset uses the network loading from our the Long Term Development Statement November 2025 as baseline, and our Distribution Future Energy Scenarios 2025 for the future scenarios of demand and generation. For further information on the NDP and the methodology to produce the DFES NSHR dataset please see Network Development Plan Landing PageThe headroom tables are based on firm capacity. However, more capacity may be available for customers on a non-firm, flexible or curtailable connection.The demand headroom tables reflect our latest firm capacity figures for demand, consistent with the May 2025 LTDS. The generation headroom tables reflect the equipment ratings in the November 2025 LTDS. . As noted in the methodology, unused substation capacity (headroom) is indicative and may be already contractually committed to specific customers.Methodological Approach• Data Collection: Gathering data from various sources, including historical usage patterns, projected growth in renewable energy, and changes in regulatory frameworks.• Forecasting: The process begins with forecasting future network loads and demands. This often involves scenario planning to predict how energy consumption and generation will evolve to 2050. The forecast methodology is reviewed periodically to incorporate new data, stakeholder feedback, and any changes in energy policy or technology. Stakeholder inputs including local authorities Energy Plans, developers, and energy providers are considered to ensure the plans align with community needs and regulatory requirements.• Distribution Network Options Assessment Assessing the identified network constraints and developing potential solutions to address these identified constraints. This may involve traditional reinforcement methods or exploring flexibility services.• Reporting: Compiling findings into a structured report that outlines the methodology, assumptions, and planned interventions. This report is typically made available to the public for transparency.• Review and Update: The methodology is reviewed periodically to incorporate new data, stakeholder feedback, and changes in energy policy or technology.Quality Control StatementQuality Control Measures include:• Verification steps to match features only with confirmed functional locations.• Manual review and correction of data inconsistencies.• Use of additional verification steps to ensure accuracy in the methodology.Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency.OtherDownload 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/If you have any questions or need clarification on any of the information shared as part of the Network Development Plan, please email our Network Insights team via NetworkInsights@ukpowernetworks.co.uk To view this data please register and login.42 days ago
- Introduction This dataset is a low voltage subset of the full DNOA dataset. The DNOA output shows future network constraints, the recommended solution, and the current status in the solution progress. It indicates when, where, and at what volume flexibility services will be required in the next few years. Note: Due to the differences in the publication date of databases such as the LTDS, DFES NSHR, and the DNOA, there can be differences in published data. You can find out more information about our methodology here: Distribution Network Options Assessment (DNOA) (ukpowernetworks.co.uk) Methodological Approach DNOA Methodology: Our methodology document can be found here. FLOC association: Using FLOCs, we associate the DNOA data to our grid and primary substation FLOCs, which allows us to generate geopoints. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Network Options Team worked together to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction Shapefile showing UK Power Networks' 66kV underground cables. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Vectorisation: Shapefiles will be regularly updated to account for vectorisation updates. Quality Control Statement The data is provided "as is". Please be aware that we have not published the dataset as we are currently vectorising LPN. Please keep an eye on our Data Roadmap for further updates on delivery. Refer to our LPN Vectorisation Delivery dataset. Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/ To request access to this dataset, please fill out the shared data request form. To view this data please register and login.22 days ago
- Introduction Active transformer characteristics from our Primary Sites. Methodological Approach Data stems from our data warehouse; and Site Functional Location (FLOC) is used to capture spatial coordinates from Key characteristics of active Grid and Primary sites — UK Power Networks. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction The Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. This is Table 2b from our current LTDS report (published 29th May 2026), showing the Transformer information for three winding (1x High Voltage, 2x Low Voltage) transformers associated to each Grid and Primary substation where applicable. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the Substation which the transformer is located to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- Introduction This dataset shows the half-hourly load profiles of identified data centres within UK Power Networks' licence areas. The loads have been determined using actual demand data from connected sites within UK Power Networks' licence areas, from 1 January 2023 onwards. Loads are expressed proportionally, by comparing the half-hourly observed import power seen across the site's meter point(s), against the meter's maximum import capacity. Units for both measures are apparent power, in kilovolt amperes (kVA). To protect the identity of the sites, data points have been anonymised and only the site's voltage level information - and our estimation of the data centre type - has been provided. Methodological Approach Nearly 100 operational data centre sites (and at least 10 per voltage level) were identified through internal desktop exercises and corroboration with external sources. After identifying these sites, their addresses, connection point, and MPAN(s) (Meter Point Administration Number(s)) were identified using internal systems. Half-hourly smart meter import data were retrieved using internal systems. This included both half-hourly meter data, and static data (such as the MPAN's maximum import capacity and voltage group, the latter through the MPAN's Line Loss Factor Class Description). Half-hourly meter import data came in the form of active and reactive power, and the apparent power was calculated using the power triangle. In cases where there are numerous meter points for a given data centre site, the observed import powers across all relevant meter points were summed, and compared against the sum total of maximum import capacity for the meters. The percentage utilisation for each half-hour for each data centre was determined via the following equation: % Utilisation_data centre site = SUM( S_MPAN half-hourly observed import) SUM( S_MPAN Maximum Import Capacity) Where S = Apparent Power in kilovolt amperes (kVA) To ensure the dataset includes only operational data centres, the dataset was then cleansed to exclude sites where utilisation was consistently at 0% across the year. Based on the MPAN's address and corroboration with other open data sources, a data centre type was derived: either enterprise (i.e. company-owned and operated), or co-located (i.e. one company owns the data centre, but other customers operate IT load in the premises as tenants). Each data centre site was then anonymised by removing any identifiers other than voltage level and UK Power Networks' view of the data centre type. Quality Control Statement The dataset is primarily built upon customer smart meter data for connected customer sites within the UK Power Networks' licence areas. The smart meter data that is used is sourced from external providers. While UK Power Networks does not control the quality of this data directly, these data have been incorporated into our models with careful validation and alignment. Any missing or bad data has been addressed though robust data cleaning methods, such as omission. Assurance Statement The dataset is generated through a manual process, conducted by the Distribution System Operator's Regional Development Team. The dataset will be reviewed quarterly - both in terms of the operational data centre sites identified, their maximum observed demands and their maximum import capacities - to assess any changes and determine if updates of demand specific profiles are necessary. Deriving the data centre type is a desktop-based process based on the MPAN's address and through corroboration with external, online sources. This process ensures that the dataset remains relevant and reflective of real-world data centre usage over time. There are sufficient data centre sites per voltage level to assure anonymity of data centre sites. Other Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: https://ukpowernetworks.opendatasoft.com/pages/glossary/Download dataset information: Metadata (JSON)To view this data please register and login.22 days ago
- IntroductionUK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is the stepping down of voltage as it is moved towards the household; this is achieved using transformers. Transformers have a maximum rating for the utilisation of these assets based upon protection, overcurrent, switch gear, etc. This dataset contains the Grid Substation Transformers, also known as Bulk Supply Points, that typically step-down voltage from 132kV to 33kV (occasionally down to 66 or more rarely 20-25). These transformers can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables.Care is taken to protect the private affairs of companies connected to the 33kV network, resulting in the redaction of certain transformers. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted.This dataset provides monthly statistics data across these named transformers from 2023 through to the previous month across our licence areas. The data are aligned with the same naming convention as the LTDS for improved interoperability.To find half-hourly current and power flow data for a transformer, use the ‘tx_id’ that can be cross referenced in the Grid Transformers Half Hourly Dataset.If you want to download all this data, it is perhaps more convenient from our public sharepoint: Open Data Portal Library - Grid Transformers - All Documents (sharepoint.com)This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets.Methodological ApproachThe dataset is not derived, it is the measurements from our network stored in our historian.The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps.We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. This redaction process considers the correlation of all the data, of only corresponding periods where the customer is active, the first order difference of all the data, and the first order difference of only corresponding periods where the customer is active. Should any of these four tests have a high linear correlation, the data is deemed redacted. This process is not simply applied to only the circuit of the customer, but of the surrounding circuits that would also reveal the signal of that customer.The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation.Quality Control StatementThe data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these transformers are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that.Assurance StatementCreating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS transformer from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same transformer in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing transformers, incorrectly labelled transformers, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible.Additional informationDefinitions of key terms related to this dataset can be found in the Open Data Portal Glossary.Download dataset information: Metadata (JSON)We would be grateful if you find this dataset useful to submit a “reuse” case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. Click here for more information: Open Data Portal Reuses — UK Power NetworksTo view this data please register and login.22 days ago
- IntroductionThis dataset contains data captured from remote Power Quality logging devices currently available across 450 UK Power Network sites*. A weekly 95th percentile value per harmonic is calculated and the highest value of each harmonic amongst all weeks, over a period of 12 months (also applicable to THD) is shown. Methodological Approach Power Quality data is collected from meters on a 10-minute basis and stored in a database. 95th percentile statistics are calculated on a weekly basis and used to generate the harmonics report.Year-week is the ISO 8601 year and week number. Quality Control Statement The data is provided "as is". Assurance Statement Harmonic data is periodically extracted and reviewed prior to publication. 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/To view this data please register and login.42 days ago
- Introduction List of transformers associated with UK Power Networks' Published Secondary SitesUK Power Networks Secondary Sites — UK Power Networks (opendatasoft.com)This datasets includes the site functional location, the DNO, Oil Natural Air Natural (ONAN) transformer rating and voltage of each secondary transformer. Methodological Approach Data Extraction: This dataset is extracted from Azure Databricks.Combination: Various data columns are joined in Azure Databricks based on the functional location. This includes Grid Reference, connectivity and the number of customers. Administrative Divisions are found using the Geo Point.Processing: There is some data processing, such as conversion of Grid Reference into longitude and latitude. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/To view this data please register and login.42 days ago
- IntroductionShapefile showing operational boundaries of the UK Power Networks London Power Networks (LPN) area Methodological Approach This dataset was extracted from UK Power Networks' internal geospatial mapping database - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. 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/42 days ago
- Introduction A Strategic Housing Land Availability Assessment (SHLAA) is a technical exercise to determine the quantity and suitability of land potentially available for housing development. It is not a site allocations exercise – the purpose is to provide a robust indication of aggregate housing capacity at local authority level. Please note this dataset is restricted, and if you would like to be considered for access, please contact: "opendata@ukpowernetworks.co.uk" This dataset is a collation of SHLAAs that UK Power Networks has access to, and is primarily for use in conjunction with the Noise Propagation dataset. Methodological Approach This dataset was compiled using different SHLAA files that UK Power Networks owned and received from local authorities. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Environment Team worked together to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- Introduction UK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is distributing this electricity across our regions through circuits. Electricity enters our network through Super Grid Transformers at substations shared with National Grid we call Grid Supply Points. It is then sent at across our 132 kV Circuits towards our grid substations and primary substations. From there, electricity is distributed along the 33 kV circuits to bring it closer to the home. These circuits can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables. Care is taken to protect the private affairs of companies connected to the 33 kV network, resulting in the redaction of certain circuits. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted. This dataset provides monthly statistics across these named circuits from 2021 through to the previous month across our license areas. The data is aligned with the same naming convention as the LTDS for improved interoperability.To find half-hourly current and power flow for the circuit you are looking for, use the ‘ltds_line_name’ that can be cross referenced in the 33kV Circuits Half Hourly Data.If you want to download all this data, it is perhaps more convenient from our public sharepoint: SharepointThis dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets. Methodological ApproachThe dataset is not derived, it is the measurements from our network stored in our historian. The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps. We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. This redaction process considers the correlation of all the data, of only corresponding periods where the customer is active, the first order difference of all the data, and the first order difference of only corresponding periods where the customer is active. Should any of these four tests have a high linear correlation, the data is deemed redacted. This process is not simply applied to only the circuit of the customer, but of the surrounding circuits that would also reveal the signal of that customer. The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation. Quality Control StatementThe data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these measurements are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that. Assurance StatementCreating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS circuit from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same circuit in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing circuits, incorrectly labelled circuits, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible.Additional InformationDefinitions of key terms related to this dataset can be found in the Open Data Portal Glossary. Download dataset information:Metadata (JSON) We would be grateful if you find this dataset useful to submit a “reuse” case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. Click here for more information: Open Data Portal Reuses — UK Power NetworksTo view this data please register and login.22 days ago
- Introduction This dataset reports on UK Power Networks' use of paid flexibility services. UK Power Networks uses flexibility (demand/generation turn up/down) in London, the South East, and the East of England to manage electricity flows on the local electricity distribution network. Flexibility dispatches data can be used to understand historical volumes, prices paid, geographic locations, providers, and technologies used. Using the Analyse tab, users can visualize and explore the growth of flexibility dispatches. These transparent insights can inform current and prospective flexibility services providers on how often flexibility is dispatched and at what price, including local authorities, electricity suppliers, industrial/commercial energy users, and generation operators. The data can also be used by wider stakeholders such as market analysts, advisers, regulators, and policymakers. A wide variety of energy resources and low carbon technologies already provide flexibility services to UK Power Networks, including grid-scale batteries, electric vehicle charge points, solar farms, wind farms, and residential energy users. These are grouped using the industry standard technology categorizations as used for regulatory reporting. To find out more about how to participate in flexibility tenders and become a flexibility provider, visit our webpage: Flexibility - UKPN DSO (ukpowernetworks.co.uk). Flexibility dispatches are currently reported from 1 April 2023, with new dispatches added daily. Each row includes the timing, location, product, capacity, technology, and provider for our growing volume of flexibility dispatches. The data is assessed for errors using algorithmic quality control as well as being evaluated manually by a flexibility engineer before publication. The dataset can be downloaded or incorporated into the user’s interface via API. Requested volumes may not match delivered volumes, depending on performance against the relevant baseline. You can find actual dispatch data in the yearly Procurement Statements and Reports at Tender Hub - UKPN DSO (ukpowernetworks.co.uk). This includes our annual Flexibility Statement (forecasts for the next regulatory year), Flexibility Report (outcomes from last regulatory year), and data appendices. Methodological Approach Dispatches are made by a control engineer in the DSO Operations team to manage local constraints. Dispatches of flexible units (FUs) may be made either by API or email, depending on the FU's technological capabilities and preference. This dataset reports on dispatches made under Secure, Dynamic, and Day-Ahead products. Flexibility provided through our Sustain product is not dispatched and hence is not included within this dataset. Requested volumes may not match delivered volumes, depending on performance against the relevant baseline. Historic data may be updated from time to time where data errors are identified. Quality Control Statement Dispatches are passed through a quality control algorithm to flag anomalies and erroneous data. Quality control checks include: Times are consistent with the contracted service window; Dispatches are matched to the correct flexibility zone; Dispatches are unique (no duplicates); Dispatches are issued at the contracted price and volume; Dispatches are matched with an active contract. Assurance Statement The flexibility dispatch report is reviewed by a flexibility engineer and a member of the Data Science team to ensure the data is accurate before publication on the Open Data Portal. Any data errors in previous reports are corrected on an ongoing basis and updated daily. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.22 days ago
- IntroductionThis dataset is a geospatial view of the areas fed by grid substations. The aim is to create an indicative map showing the extent to which individual grid substations feed areas based on MPAN data. Methodology Data Extraction and Cleaning: MPAN data is queried from SQL Server and saved as a CSV. Invalid values and incorrectly formatted postcodes are removed using a Test Filter in FME. Data Filtering and Assignment: MPAN data is categorized into EPN, LPN, and SPN based on the first two digits. Postcodes are assigned a Primary based on the highest number of MPANs fed from different Primary Sites. Polygon Creation and Cleaning: Primary Feed Polygons are created and cleaned to remove holes and inclusions. Donut Polygons (holes) are identified, assigned to the nearest Primary, and merged. Grid Supply Point Integration: Primaries are merged into larger polygons based on Grid Site relationships. ny Primaries not fed from a Grid Site are marked as NULL and labeled. Functional Location Codes (FLOC) Matching: FLOC codes are extracted and matched to Primaries, Grid Sites and Grid Supply Points. Confirmed FLOCs are used to ensure accuracy, with any unmatched sites reviewed by the Open Data Team. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Regular updates and reviews documented in the version history Assurance Statement The Open Data Team and Network Data Team worked with the Geospatial Data Engineering Team to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- IntroductionWhen a generator applies and accepts a connection offer issued by UK Power Networks, and it is connecting to a GSP with no available materiality headroom, UK Power Networks will submit a Transmission Impact Assessment application to vary the BCA (Bilateral Connection Agreement). Methodological Approach Data is compiled from existing datashare between UK Power Networks and the National Energy System Operator. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and DSO Regional Development Team worked together ensure data accuracy and consistency. OtherDownload 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/To view this data please register and login.22 days ago
- Introduction This dataset provides information on where UK Power Networks requires flexibility services. The dataset provides a mapping of postcodes to Flexibility Zones – for all existing and historic day-ahead and long-term flexibility requirements. This enables potential flexibility service providers to quickly understand their eligibility for revenue from flexibility, without sharing any sensitive personal or commercial information. This dataset provides an approximation of eligibility for our flexibility tenders. Please note that even if your asset is within a postcode listed in this dataset, as part of the flexibility procurement process we will need to validate that the individual meter point (MPAN) is electrically connected to the Flexibility Zone. Methodological Approach Postcodes are listed against a Flexibility Zone where at least one meter point within that postcode is electrically connected to the constrained network asset. For large Flexibility Zones, which cover multiple postcodes, this will be a very good indication of eligibility for flexibility services. For smaller Flexibility Zones, particularly those at Low Voltage, a significant proportion of properties within a listed postcode may ultimately not be eligible. As part of our flexibility procurement process, we will check the individual meter point (MPAN) to confirm its final eligibility. This dataset offers an approximation of eligibility, without requiring any sharing of household or business level data. Quality Control Statement Dispatches are passed through a quality control algorithm to flag anomalies and erroneous data. Quality control checks include: Checking the formatting of postcodes Checking the number of postcodes mapped to each Flexibility Zone Checking that Flexibility Zone names align with those in other datasets on the Open Data Portal and on UK Power Networks’ chosen flexibility market platform: www.localflex.co.uk Assurance Statement The Flex Zone to Postcode mapping is reviewed before publication by a member of Flexibility Markets team. 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/ To view this data please register and login.42 days ago
- IntroductionNewsfeed Dataset lists the news items shown the landing page preview window. 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/22 days ago
- Introduction A dataset showing the location of UK Power Networks' 132kV towers. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- Introduction Shapefile showing licence boundaries in the UK Power Networks area. Methodological Approach This dataset was extracted from UK Power Networks' geospatial system - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data Team reviewed this to ensure data accuracy and consistency. 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/42 days ago
- Introduction UK Power Network maintains the 132kV voltage level network and below. An important part of the distribution network is the stepping down of voltage as it is moved towards the household; this is achieved using transformers. Transformers have a maximum rating for the utilisation of these assets based upon protection, overcurrent, switch gear, etc. This dataset contains the Primary Substation Transformers, that typically step-down voltage from 33kV to 11kV (occasionally from 132kV to 11kV). These transformers can be viewed on the single line diagrams in our Long-Term Development Statements (LTDS) and the underlying data is then found in the LTDS tables.Care is taken to protect the private affairs of companies connected to the 11kV network, resulting in the redaction of certain transformers. Where redacted, we provide monthly statistics to continue to add value where possible. Where monthly statistics exist but half-hourly is absent, this data has been redacted.This dataset provides monthly statistics data across these named transformers from 2023 through to the previous month across our licence areas. The data are aligned with the same naming convention as the LTDS for improved interoperability.To find half-hourly current and power flow data for a transformer, use the ‘tx_id’ that can be cross referenced in the Primary Transformers Half Hourly Dataset.If you want to download all this data, it is perhaps more convenient from our public sharepoint: Open Data Portal Library - Primary Transformers - All Documents (sharepoint.com)This dataset is part of a larger endeavour to share more operational data on UK Power Networks assets. Please visit our Network Operational Data Dashboard for more operational datasets.Methodological ApproachThe dataset is not derived, it is the measurements from our network stored in our historian.The measurement devices are taken from current transformers attached to the cable at the circuit breaker, and power is derived combining this with the data from voltage transformers physically attached to the busbar. The historian stores datasets based on a report-by-exception process, such that a certain deviation from the present value must be reached before logging a point measurement to the historian. We extract the data following a 30-min time weighted averaging method to get half-hourly values. Where there are no measurements logged in the period, the data provided is blank; due to the report-by-exception process, it may be appropriate to forward fill this data for shorter gaps.We developed a data redactions process to protect the privacy or companies according to the Utilities Act 2000 section 105.1.b, which requires UK Power Networks to not disclose information relating to the affairs of a business. For this reason, where the demand of a private customer is derivable from our data and that data is not already public information (e.g., data provided via Elexon on the Balancing Mechanism), we redact the half-hourly time series, and provide only the monthly averages. This redaction process considers the correlation of all the data, of only corresponding periods where the customer is active, the first order difference of all the data, and the first order difference of only corresponding periods where the customer is active. Should any of these four tests have a high linear correlation, the data is deemed redacted. This process is not simply applied to only the circuit of the customer, but of the surrounding circuits that would also reveal the signal of that customer.The directionality of the data is not consistent within this dataset. Where directionality was ascertainable, we arrange the power data in the direction of the LTDS "from node" to the LTDS "to node". Measurements of current do not indicate directionality and are instead positive regardless of direction. In some circumstances, the polarity can be negative, and depends on the data commissioner's decision on what the operators in the control room might find most helpful in ensuring reliable and secure network operation. Quality Control StatementThe data is provided "as is". In the design and delivery process adopted by the DSO, customer feedback and guidance is considered at each phase of the project. One of the earliest steers was that raw data was preferable. This means that we do not perform prior quality control screening to our raw network data. The result of this decision is that network rearrangements and other periods of non-intact running of the network are present throughout the dataset, which has the potential to misconstrue the true utilisation of the network, which is determined regulatorily by considering only by in-tact running arrangements. Therefore, taking the maximum or minimum of these transformers are not a reliable method of correctly ascertaining the true utilisation. This does have the intended added benefit of giving a realistic view of how the network was operated. The critical feedback was that our customers have a desire to understand what would have been the impact to them under real operational conditions. As such, this dataset offers unique insight into that. Assurance StatementCreating this dataset involved a lot of human data imputation. At UK Power Networks, we have differing software to run the network operationally (ADMS) and to plan and study the network (PowerFactory). The measurement devices are intended to primarily inform the network operators of the real time condition of the network, and importantly, the network drawings visible in the LTDS are a planning approach, which differs to the operational. To compile this dataset, we made the union between the two modes of operating manually. A team of data scientists, data engineers, and power system engineers manually identified the LTDS transformer from the single line diagram, identified the line name from LTDS Table 2a/b, then identified the same transformer in ADMS to identify the measurement data tags. This was then manually inputted to a spreadsheet. Any influential customers to that circuit were noted using ADMS and the single line diagrams. From there, a python code is used to perform the triage and compilation of the datasets. There is potential for human error during the manual data processing. These issues can include missing transformers, incorrectly labelled transformers, incorrectly identified measurement data tags, incorrectly interpreted directionality. Whilst care has been taken to minimise the risk of these issues, they may persist in the provided dataset. Any uncertain behaviour observed by using this data should be reported to allow us to correct as fast as possible. Additional informationDefinitions of key terms related to this dataset can be found in the Open Data Portal Glossary.Download dataset information: Metadata (JSON)We would be grateful if you find this dataset useful to submit a “reuse” case study to tell us what you did and how you used it. This enables us to drive our direction and gain better understanding for how we improve our data offering in the future. Click here for more information: Open Data Portal Reuses — UK Power NetworksTo view this data please register and login.22 days ago
- 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: Pt (p.u) = P1, tPmax1 + P2, tPmax2 + … + Pn, tPmaxn 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/22 days ago
- Introduction A dataset showing the location of UK Power Networks' HV (High Voltage) poles. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction The Capacity Heatmap data is a requirement defined in Form of Long Term Development Statement (LTDS) and is being published for the first time as part of this LTDS cycle. As described in Section 6 of the Form of LTDS, the data provides a standardised view of available network capacity, constraints, and recent connection activity across the distribution network. It supports users in understanding where demand and generation connections may be possible, where network constraints may exist, and how recent connection activity may influence future network planning and connection decisions. Further details on the Capacity Heatmap data structure and requirements are provided in LTDS Capacity Heatmaps Appendix 1 – Information Model. The latest version of the appendix is available through BSI GB CIM Engagement Hub. The heatmap data is structured around a HeatmapDataSet, which represents a single published dataset and contains publication metadata such as the dataset title, description, publisher, issue date, validity period, coverage, format, and rights information. Within the HeatmapDataSet, Substation records provide the main operational view of the network, including location, voltage levels, licence area, demand and generation capacities, available capacity, constraint indicators, limiting factors, and references to related network hierarchy points such as Grid Supply Points (GSPs) and Bulk Supply Points (BSPs). The dataset also includes ConnectionActivity for substations where connection activity has occurred during the past year. This element summarises the number and total capacity of budget estimates provided, connection offers made, and connection offers accepted for both demand and generation connections. It provides useful context for interpreting available capacity, as it shows recent customer activity that may affect future network utilisation and planning decisions. For more information please see the UK Power Networks guide to Capacity Heatmaps: UK Power Networks LTDS Capacity Heatmaps Methodological Approach The source data for this release is drawn from the 2026 LTDS publication together with UK Power Networks Network Scenario Headroom Reports and additional in-house data where required. To support consistency across published datasets, the longitude and latitude values used in the Capacity Heatmap data have been aligned with relevant location data available through the UK Power Networks Open Data Portal. For a detailed understanding of the data scope published in the May 2026 LTDS cycle, users should refer to the LTDS Stage 2 Publication Notes, which set out the specific content and limitations of the LTDS data. Quality Control Statement Quality control checks were undertaken during the development of the Capacity Heatmap data to support consistency, completeness, and accurate representation of the published information. The heatmap data was checked against the relevant source datasets, including the LTDS publication data, Network Scenario Headroom Report outputs, and supporting in-house data. These checks confirmed that the values included in the heatmap publication are consistent with the available source data and are reflected correctly in the published outputs. The JSON export was validated through an import and review process to confirm that the file structure, attribute values, and licence-area outputs could be read and analysed as expected. This provided an additional assurance check on the integrity and usability of the published JSON format. Assurance Statement The DSO Network Insights Team checked to ensure data accuracy and consistency. Other Download the full JSON files from the Attachments section on this dataset. Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: https://ukpowernetworks.opendatasoft.com/pages/glossary/To view this data please register and login.42 days ago
- IntroductionThis table provides an overview of the physical and technical capacity at every Grid Supply Point (GSP). The Technical Limits fields provide a RAG status on whether this is available yet, and where available the limits as agreed with National Grid ESO which will not have a negative impact on the transmission network. This is an ongoing development and as they become available more GSPs will become part of this process, and values may change over time. The Import limit is provided for winter, summer and the access period. The Historical Maximum and Minimum Power Flow comes from UK Power Networks' own analysis of the power flow through that GSP in the previous year. The Asset Import Limit and Asset Export Limit is calculated based on the Supergrid transformer capacities available at the GSP, and are provided for indicative purposes only and may not reflect the actual capacity at the GSP. The Export and Import Capacity Utilisation is then calculated as a ratio of the maximum and minimum demand and the capacity at the GSP, which where possible is the technical limits and where not possible, the asset capacity. Combined with the previous table it provides a thorough view of headroom at all GSPs. Methodological Approach Data is compiled from existing datashare between UK Power Networks and the National Energy System Operator. UK Power Networks has included Functional Locations (FLOCs) to aid with referencing with other UK Power Networks datasets. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations; Manual review and correct of data inconsistencies; and Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and DSO Data Science team worked together to ensure data accuracy and consistency. 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/Supported by National Energy SO Open Data.To view this data please register and login.42 days ago
- Introduction Shapefile showing local authority boundaries within the UK Power Networks area (across all licence areas). District/Borough councils, Unitary Authorities, and County Councils are shown. Methodological Approach Data Extraction: Static shapefiles were exported from the Office of National Statistics' website. Source: Local Authorities, County Councils and Regions.Data Manipulation: Using our shapefile for our operational boundaries, the Open Data team has excluded any local authorities outside of our area. Local Authority boundaries are unclipped, meaning the entire boundary is shown - even if the majority of the boundary is outside our licence Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. Other Contains public sector information licensed under the Open Government Licence v3.0. 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/42 days ago
- Introduction The Embedded Capacity Register (ECR) lists all generation, storage, and flexible demand resources where the installed generation capacity, export capacity, or import capacity is 50kW to 1MW.Note: Please note, in the November 2025 publication, an additional 230 records were included. This data has been provided by MCS (Microgeneration Certification Scheme) where installers have not previously notified us of installations. In publishing the data we aim to provide greater visibility of the number of installations. More information can be found here: Embedded Capacity Register Methodological Approach Data Collection: The data is sourced from various internal systems, including the data warehouse and other operational databases. This ensures comprehensive coverage of all relevant resources; and Data Integration: The collected data is integrated and organized to provide a clear view of the capacity and distribution of these resources across different license areas. This includes details such as location coordinates, energy source, conversion technology, and associated substations. Quality Control Statement The data is provided "as is". Assurance Statement We are aware that not all cells are fully populated on the ECR. We are working hard to gather and check data so that we can provide the missing information as soon as possible. If you notice any errors or omissions, please email us at DG-Q&A@ukpowernetworks.co.uk. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal Glossary *Please note that fixes have been applied to this dataset (February 2024) including the connected records source of data for registered capacity which has resulted in some fallout.To view this data please register and login.42 days ago
- Introduction This dataset shows the longest lead time seen for prospective large demand sites to connect to UK Power Networks’ distribution network at or under each of the Grid Supply Points in our service area. This process is known as a "Modification Application" or "ModApp". Further information about this application is given in the "Other" section of this dataset. It happens as a result of UK Power Networks submitting an application to the National Energy System Operator (NESO) for National Grid Electricity Transmission (NGET) to consider the material impact the large demand site may have on their transmission network. UK Power Networks submits these applications for large demand sites (e.g. very large data centres), where its connection and envisaged load is deemed to have a material impact on the operation of both the distribution and transmission network. These dates reflect the quoted time it will take for NGET to carry out the necessary transmission network building or reinforcement, for it to accommodate the new electrical load (from both a thermal and fault level perspective). UK Power Networks does not submit these applications for smaller connection projects (e.g. housing developments), as they are deemed not to have a sufficiently material impact on the transmission network. This future load is incorporated into our wider distribution network load forecasting, which is shared with NGET via regulatory processes for their consideration (e.g. The "Week 24" submission process). This list has been determined using internal systems UK Power Networks uses to manage all committed projects in the process of connecting to our network. To protect the identity of the sites, no project information has been disclosed, and insights are aggregated at the Grid Supply Point level. As per Section 11 of the Connection and Use of System Code (CUSC) ("Interpretation and Definitions"), a Modification is "any actual or proposed replacement, renovation, modification, alteration, or construction by or on behalf of a User or The Company to either the User’s Plant or Apparatus or the manner of its operation or Transmission Plant or Transmission Apparatus or the manner of its operation which in either case has or may have a Material Effect on another CUSC Party at a particular Connection Site". Further information about Modifications, including Modification Applications, can be found in Section 6.9 of the CUSC ("General Provisions", "Modifications"). The format of a Modification Application is provided in Exhibit I of the CUSC. Methodological Approach Modification Applications linked to large demand sites are identified through desktop exercises using UK Power Networks' internal customer relationship management system and extracted Information for each application is extracted in a tabular format (e.g., lead times, status, Grid Supply Point) Subsequent analysis is done to extract the longest times for each Grid Supply Point and generate the resultant dataset. Quality Control Statement The data is provided "as is". Assurance Statement The dataset uses internal data, relating to large demand projects and Modification Applications in UK Power Networks' licence areas. Data have been checked with both automatic and manual validation methods. The dataset is generated through a manual process, conducted by the Distribution System Operator's Regional Development Team. The dataset will be reviewed quarterly to assess any changes, and to determine if any updates to the methodology are necessary. This process ensures that the dataset remains relevant and reflective of the data centre projects UK Power Networks is aware of. To protect the identity of the sites, no project information has been disclosed, and insights are aggregated at the Grid Supply Point level. 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/To view this data please register and login.42 days ago
- IntroductionShapefile showing UK Power Networks' 66kV overhead lines. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- Introduction This dataset contains the geographical locations of Low Voltage overhead lines that are in use in the UK Power Networks licence areas. Locations are available as Geo Point (latitude and longitude) and Geo Shape. The dataset can be downloaded as a shapefile. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Quality Control StatementThe data is provided "as is".Assurance StatementThe Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction The DNOA output shows future network constraints, the recommended solution, and the current status in the solution progress. It indicates when, where, and at what volume flexibility services will be required in the next few years. This dataset will be updated annually by the end of the first quarter each year. Due to the differences in the publication date of databases such as the LTDS, DFES NSHR, and the DNOA, there can be differences in published data. Methodological Approach DNOA Methodology: Our methodology document can be found here. FLOC association: Using FLOCs, we associate the DNOA data to our grid and primary substation FLOCs, which allows us to generate geopoints. Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Network Options Team worked together to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction This dataset is a geospatial view of the areas fed by primary substations. The aim is to create an indicative map showing the extent to which individual primary substations feed areas based on MPAN data. Methodological Approach Data Extraction: MPAN data is downloaded from the geographical system. The system searches with a geographical window and assigns it to the nearest supply point. Connectivity. Data is taken from the connectivity model and mapped to the relevant MPAN. Data Filtering: Any coordinates that are more than 500m from the nearest secondary site are removed. Primary Assignment: Postcodes of the MPANs are assigned to a primary substation based on the number of MPANs fed. Polygon Creation: Primary Feed Polygons are created and cleaned up to remove holes and inclusions. Hierarchy Construction: Grid Supply Point polygons are produced from schematics and merged based on hierarchical relationships. FLOC Matching: Functional Location Codes (FLOC) are matched to the respective sites.Based on the functional location (FLOC), firm capacity, season of constraint and % unutilised capacity data is taken from Long Term Development Statement (LTDS) Table 3a Observed Peak Demand Quality Control Statement Quality control measures include: Verification steps to match features only with confirmed FLOCs. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Regular updates and reviews documented in the version history. Assurance Statement The Open Data team, worked with the Geospatial Data Engineering team ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- IntroductionA shapefile containing the postcode areas supplied by secondary substations. Methodological approach The dataset is generalised using our GIS customer connectivity model. Each Secondary Substation's connected LV Network is traced out to its electrical extents, including all connected customers. Using the geographic position of customer connections and key network points of both the Substation being traced and surrounding Substation's network, a Voronoi diagram is created. Each Voronoi polygon that intersects with the traced network is joined together to produce a single polygon, depicting the Supply Zone. Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. The data domain owners have checked their respective data aspects. This dataset is redacted in that any secondary sites with less than five customers will not be included to protect privacy. 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/To view this data please register and login.42 days ago
- Introduction To ensure we deliver a safe and reliable electricity supply or to invest in our network, we may need to carry out works on highways and footways. This dataset contains details of our proposed street and roadwork permit applications taking place on the highway within UK Power Networks' footprint. This report is refreshed daily. For further information including contact details, please visit https://www.ukpowernetworks.co.uk/our-company/road-works Methodological Approach Data Extraction: Data is extracted from Street Manager onto a server every two hours. Data Upload: Another script is run every two hours to upload onto an FTP server, before passing onto the Open Data Portal. Quality Control Statement Quality Control Measures include: Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Streetworks Team worked together to ensure data accuracy and consistency. Other Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal Glossary Download dataset information: Metadata (JSON)42 days ago
- IntroductionThe earth potential rise (EPR) dataset includes the fault current, ground return current, EPR and site classification at various voltages (132kV, 66kV, 33kV, 25kV, 20kV, 11kV, 6.6kV) for all Grid and Primary substations. This data can be used in substation earthing system design and assessment. For further information on earthing refer to UK Power Networks' earthing standard EDS 06-0001 available from our website https://g81.ukpowernetworks.co.uk/. Please send any enquiries related to the dataset to earthingenquiries@ukpowernetworks.co.uk. Methodological Approach EPR data is uploaded from UK Power Networks' data warehouse. Site Functional Locations (FLOCs) are used to associate EPR data to UK Power Networks Grid and Primary Sites Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team has checked to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- IntroductionFollowing the identification of Local Area Energy Planning (LAEP) use cases, this dataset lists the data sources and/or information that could help facilitate this research. View our dedicated page to find out how we derived this list: Local Area Energy Plan — UK Power Networks (opendatasoft.com) Methodological Approach Data upload: a list of datasets and ancillary details are uploaded into a static Excel file before uploaded onto the Open Data Portal. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Local Net Zero Team worked together to ensure data accuracy and consistency. 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/ Please note that "number of records" in the top left corner is higher than the number of datasets available as many datasets are indexed against multiple use cases leading to them being counted as multiple records.22 days ago
- Introduction Shapefile showing UK Power Networks' 132kV underground cables. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Vectorisation: Shapefiles will be regularly updated to account for vectorisation updates. Quality Control Statement The data is provided "as is". Please be aware that not all locations are fully vectorised yet, so the dataset provides only partial coverage. Refer to our LPN Vectorisation Delivery dataset. Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/To request access to this dataset, please fill out the shared data request form. To view this data please register and login.42 days ago
- IntroductionAs part of our Enable project, we estimated the projected number of on-street disabled parking bays and Blue Badge holders in our licence areas by 2030. This data is available at the Lower Layer Super Output Area (LSOA) level. We hope that this data will help local authorities and charge point operators plan for accessible transport provision for customers.This project started in March 2021 and concluded in March 2022. More information on what we're doing for accessible transport can be found at UK Power Networks Accessible transport information hub and project-enable. Please note, the dataset contains estimations and are not true values. Methodological Approach Details on the methodology can be found in the project report - Project Enable. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Innovation Team worked together to ensure data accuracy and consistency. 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/42 days ago
- IntroductionThis dataset provides visibility of the status of the UK Power Networks pipeline from the opening of the window, in May 2025. The breakdown of key technologies and also of the overall UK Power Networks view offers insight into the capacity that received a Gate 2 offer against other projects that either failed initial checks or self-elected Gate 1, or failed detailed checks, or have cancelled or connected since then. Methodological Approach The May 2025 UK Power Networks pipeline has been used in this dataset as the base scenario, and the NESO queue outcome and current connections status aggregated to it to provide this retrospective view. Quality Control Statement This dataset has been peer reviewed and checked against other datasets. Assurance Statement The Open Data Team and DSO Regional Development Team worked together ensure data accuracy and consistency. OtherDownload 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/22 days ago
- Introduction Shapefile showing UK Power Networks' 33kV underground cables. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Vectorisation: Shapefiles will be regularly updated to account for vectorisation updates. Quality Control Statement The data is provided "as is". Please be aware that not all locations are fully vectorised yet, so the dataset provides only partial coverage. Refer to our LPN Vectorisation Delivery dataset. Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/ To request access to this dataset, please fill out the shared data request form. To view this data please register and login.42 days ago
- Introduction The Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. Long Term Development Statement Table 5 shows the capacity of existing distributed generation connected at each Primary substation. It also includes a snapshot of accepted connections at the time. Published 29th May 2026. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the Substation to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.42 days ago
- Introduction Shapefile showing UK Power Networks' low voltage underground cables. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Vectorisation: Shapefiles will be regularly updated to account for vectorisation updates. Quality Control Statement The data is provided "as is". Please be aware that not all locations are fully vectorised yet, so the dataset provides only partial coverage. For clarity, LPN is not published yet as we are currently vectorising this region. Refer to our LPN Vectorisation Delivery dataset.Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/ This dataset has been triaged as 'Shared' (see attached data sharing risk assessment). To request access to this dataset, please register, login then complete the shared data request form.42 days ago
- Introduction Shapefile showing UK Power Networks' high voltage (1kV - 33kV) underground cables. Methodological Approach Data Extraction: Shapefiles are extracted from our geospatial mapping system - NetMap. Vectorisation: Shapefiles will be regularly updated to account for vectorisation updates. Quality Control Statement The data is provided "as is". Please be aware that not all locations are fully vectorised yet, so the dataset provides only partial coverage. Refer to our LPN Vectorisation Delivery dataset.Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. 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/ This dataset has been triaged as 'Shared' (see attached data sharing risk assessment). To request access to this dataset, please register, login then complete the shared data request form.42 days ago
- Introduction This data shows an aggregated view of our Data Best Practice Maturity Ratings against Ofgem's Data Best Practice Principles. The details of which, can be found here: https://www.ofgem.gov.uk/decision/decision-updates-data-best-practice-guidance-and-digitalisation-strategy-and-action-plan-guidance This dataset feeds our Data Best Practice Maturity Framework page. Methodological Approach This is an aggregated snapshot of our Data Best Practice Maturity Ratings against Ofgem's Data Best Practice Principles Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. 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/22 days ago
- Introduction The Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. Long Term Development Statement Table 7 indicates Operational Restrictions in place at our Grid and Primary substations. Published 29th May 2026. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page Methodological Approach Site Functional Locations (FLOCs) are used to associate the Substation to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies. Use of additional verification steps to ensure accuracy in the methodology. Assurance Statement The Open Data Team and Network Insights Team together ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- Introduction The Long Term Development Statement (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. This is Table 1 from our current LTDS report (published 29th May 2026), showing the circuit associated with each Grid and Primary substation. More information and full reports are available from the landing page below: Long Term Development Statement Landing Page — UK Power Networks (opendatasoft.com) Methodological Approach Site Functional Locations (FLOCs) are used to associate the From Substation to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal GlossaryTo view this data please register and login.22 days ago
- Introduction These maps show the potential area affected by noise from Grid or Primary Substations. Acoustic mitigation strategies that have already been applied to some substations are not reflected in the maps.Please take this into account when looking at individual sites. Please note this dataset is restricted, and if you would like to be considered for access, please contact: "opendata @ukpowernetworks.co.uk" Developers and local authority planners should be aware that the responsibility to mitigate noise issues rests with the developer as the ‘agent of change’. Methodological Approach There are three contours:Distance (m)Predicted Noise Level (dBA)ComplaintsAction4044Likely from any new residential developmentPlease consult environment@ukpowernetworks.co.uk7539Possible from any new residential developmentPlease consult environment@ukpowernetworks.co.uk13534Not very likely Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Environment Team worked together to ensure data accuracy and consistency. 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/To view this data please register and login.42 days ago
- IntroductionThe Long Term Development Statements (LTDS) report on a 0-5 year period, describing a forecast of load on the network and envisioned network developments. The LTDS is published at the end of May and November each year. Long Term Development Statement Table 4a shows the 3 phase fault level at each Grid and Primary substation. Published 29th May 2026. More information and full reports are available from the landing page below: Long Term Development Statement Landing PageMethodological ApproachSite Functional Locations (FLOCs) are used to associate the Site to Key characteristics of active Grid and Primary sites — UK Power Networks ID field added to identify row number for reference purposes Quality Control Statement Quality Control Measures include: Verification steps to match features only with confirmed functional locations. Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team and Network Insights Team worked together to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- Introduction This dataset contains the total losses across the network. Distributing electricity across a large area inevitably leads to electrical 'losses'. In simple terms, the energy entering our network is higher than the energy received by our customers and this is what we call a 'loss'. Losses can occur in a number of ways, please refer to our losses site for more information. Methodological ApproachNetwork losses in this dataset are calculated as the difference between units of electricity entering the network and units exiting the network. Due to delays in the data required to calculate the losses, final losses are not determined until 14 months after the date, referred to in this dataset as 'RF', albeit these can still change for up to 6 years due to corrections to IDNO and half-hourly customers' data.Delayed data includes the consumption of domestic customers and generation of small generators due to infrequent meter readings. Initial estimates are made (for example, estimated domestic bills), and it takes 5 reconciliations over a 14 month period to approach an accurate figure for units exiting the network. Our reporting is often required at the start of this reconciliation cycle, so the most up to date data available at that time is used but this will become outdated as further reconciliations come in.In addition to the reconciliations, the values used for our reporting are displayed in columns labelled 'Regulatory Reporting'. In some areas the reported values are not an exact match for any previous iteration of the data. This is due to metering errors of half hourly metered customers which are later corrected by the customer. Consumption data is sourced from Elexon, the company that manage the Balancing and Settlement Code. The main purpose of this data is to provide the data for billing DUoS, hence it is not necessarily complete for unbilled consumption or generation. Quality Control Statement Data is provided "as is". Data has been checked against regulatory submissions for consistency Assurance Statement The Open Data Team and Net Zero & Network Development Team worked together to ensure data accuracy and consistency. 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/To view this data please register and login.22 days ago
- IntroductionOptimise Prime has gathered data from over 8,000 electric vehicles (EVs) driven for commercial purposes through three trials. The project also implemented a range of technical and commercial solutions aiming to accelerate the transition to EVs for commercial fleet operators, while helping GB’s distribution networks plan and prepare for the mass adoption of EVs. The project aimed to reduce the impact of EVs on distribution networks and ensure security of electricity supply while saving money for electricity customers, helping the UK meet its clean air and climate change objectives. Methodology This is provided in the project links below. Quality Control Statement This dataset is provided "as is". Assurance Statement The Open Data Team and Innovation Lead checked for data accuracy and consistency. OtherDownload 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/Methodological ApproachThe project consisted of three trial workstreams (WS): WS1, investigating the impact of commercial vehicles charging at homes WS2, monitoring and optimising commercial vehicles charging in depots WS3, which uses private hire vehicle (PHV) journey data to model the impact of these vehicles on the distribution network. The trial period for WS3 began in August 2020, with WS1 and WS2 trials commencing on 1 July 2021. All trials concluded at the end of June 2022. Optimise Prime is sharing the project datasets by making them publicly available to the wider electricity, fleet and PHV industry to optimise their vehicle electrification plans. Distribution Network Operators (DNOs), academics and interested parties will be able to utilise this anonymised data created by the project for further research, analysis and forecasting. Along with the datasets, an introductory document is available below. It provides information on the content of those datasets, guidance on how to interpret each data field and instructions on how to access the data. Over the course of the trials, the project has collected and analysed data from a wide range of sources in order to carry out a wide range of experiments. The key datasets collected and used in analysis are available here. These includes: WS1 – Return-to-Home Trials · Charge Point (CP) session data · Vehicle telematics journey data WS2 – Depot Trials · Details of the assets and asset types at each depot · Charging data gathered from the CPs at each depot · Building load measurement data from each depot · Details of the profiled connections, flexibility trials and smart charging profiles trialled at each depot WS3 – Mixed Trials · PHV charging demand overlaid onto substation available capacity data aggregated by borough The project is not able to release all data collected and used by the project, as some are commercially confidential to the project partners (such as precise volumes of Uber trips or substation capacities), contains potentially personally identifiable information (such as precise start and end locations of home charging journeys or Uber trips) or were purchased by the project under license (e.g. charge point (CP) locations, weather data and off-street parking data). The figure below shows how the datasets are built:To access the datasets, use the below Account name and Shared Access Signature (SAS) token (used due to the large size of these data sets - if you are not familiar with this method, please refer to the guide at the bottom of this page):Account Name or URLhttps://ukpnoppublicdata001.blob.core.windows.net/optimiseprimeShared Access Signature (SAS)sv=2024-11-04&ss=b&srt=co&sp=rl&se=2026-11-10T19:04:16Z&st=2025-11-10T10:49:16Z&spr=https&sig=l%2FLfJSWI0r378cSJcAPyufVnr1S%2BOKIg2Z1AQGqHT44%3DShared Access Signature URL (SAS)https://ukpnoppublicdata001.blob.core.windows.net/optimiseprime?sv=2024-11-04&ss=b&srt=co&sp=rl&se=2026-11-10T19:04:16Z&st=2025-11-10T10:49:16Z&spr=https&sig=l%2FLfJSWI0r378cSJcAPyufVnr1S%2BOKIg2Z1AQGqHT44%3D Refer to Section 5 in the Optimise Prime Dataset Guidance Document, in the Attachments section below, for more information on how to access the datasets. We'd love to hear how you have used our datasets. Please submit a use case below (click on Submit a reuse).Any questions, please refer to the FAQ document in the attachments section first, if your questions is not answered, please contact innovation@ukpowernetworks.co.uk.For further information about Optimise Prime and access the project reports, please visit: UK Power Networks Innovation - Optimise Prime22 days ago
- Introduction Shapefile showing the areas within UK Power Networks' three licence areas which have Areas of Outstanding Natural Beauty (AONB) Methodological Approach Data Extraction: A static shapefile was exported from Natural England's website. Source: View Dataset Quality Control Statement The data is provided "as is". Assurance Statement The Open Data team has checked the data against source to ensure data accuracy and consistency. Other Note: Areas of Outstanding Natural Beauty are now know as National Landscapes.Contains public sector information licensed under the Open Government Licence v3.0. See also a map of areas of natural beauty showing the areas we are working on removing overhead power lines, helping restore the British countryside to its beautiful best. 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/42 days ago
- ***Please note, this dataset has now been archived indefinitely. If you would like to know your block letter, please visit: Find my block letter | UK Power Cut? Call 105 For Free | Find Your Electricity Provider***This dataset shows the primary feeding areas with their assigned rota load disconnection codes. Under various circumstances, distribution network operators (DNOs) such as UK Power Networks could be instructed to implement a schedule of rota disconnections to reduce electrical demand.For more information, please visit the Energy Networks Association's dedicated page. 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/To view this data please register and login.22 days ago
- IntroductionThe data shown above constitutes UK Power Networks’ provisional view against the Clean Power 2030 technology breakdowns applicable to UK Power Networks – the information will continue to be updated as we confirm the evidence from our customers. This is for indicative purposes only.Here is a breakdown of the different categories:Connected: Connected capacity.Potentially Protected Schemes by 2030: Projects meeting any of the protections criteria against Strategic Alignment. In line with the Connections Network Design Methodology (CNDM) from NESO, if the 2030 permitted capacity is reached at this stage, all remaining potentially protected projects will be allocated to Phase 2 (2035 allocation), even if this results in 2035 permitted capacity being exceeded. Potentially Protected Schemes by 2035: Remaining projects meeting any of the protections criteria against Strategic Alignment, and which exceeded the 2030 permitted capacity.Projects with readiness connecting by 2030: Projects with land rights (and either application submitted, under appeal or only land), connecting by 2030 as per their contracted connection date.Projects with readiness connecting by 2035: Projects with land rights (and either application submitted, under appeal or only land), connecting by 2035 as per their contracted connection date.No readiness or progress recorded: Projects without land rights (despite having consents approved or application submitted), or no progress recorded at all.Outside of scope for Gate 2 to Whole Queue: Projects which fall outside of the upcoming Gate 2 application window (Gate 2 to Whole Queue) due to not being part of an application to NESO before “The Pause” .Clean Power Action Plan - 2030: Regional capacity breakdown per technologies for UK Power Networks’ distribution network region for 2030, as provided by the Clean Power 2030 Action Plan (Clean Power 2030 Action Plan: A new era of clean electricity: Connections reform annex)Clean Power Action Plan - 2035: Regional capacity breakdown per technologies for UK Power Networks’ distribution network region for 2035, as provided by the Clean Power 2030 Action Plan (Clean Power 2030 Action Plan: A new era of clean electricity: Connections reform annex) Methodological Approach The breakdown has been generated based on the progress status which aligns with NESO’s Gate 2 Readiness Criteria, compared against DESNZ allocation for UK Power Networks. This continues to be updated as more information is provided and validated. Quality Control Statement This dataset has been peer reviewed and is the outcome of an iterative process as the queue formation process has become clearer over the last months (and is still subject to change following Ofgem’s decision). Assurance Statement The Open Data Team and DSO Regional Development Team worked together ensure data accuracy and consistency. OtherDownload 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/22 days ago
- IntroductionList of UK Power Network's Visual Amenity Projects where overhead power lines have been removed from National Landscapes and National Parks, restoring the British countryside to its beautiful best.Click here to view geographically and find out more about our Projects. Methodological Approach The Property and Consents team provided this dataset from their source. Quality Control Statement This dataset is provided "as is". Assurance Statement The Open Data Team and Property and Consents Team worked together to ensure data accuracy and consistency. 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/42 days ago
- Introduction Shapefile showing the rivers within UK Power Networks' three licence areas. Methodological Approach Data Extraction and Cleaning: Data is downloaded from DEFRA data portal. Data Filtering and Assignment: Only rivers within the UK Power Networks service area are included. Quality Control Statement Quality Control Measures include: Manual review and correct of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team has checked this to ensure data accuracy and consistency. Other Contains public sector information licensed under the Open Government Licence v3.0. 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/42 days ago
- Introduction Map layer featuring parliamentary constituency boundaries that are within the UK Power Networks service areas. This shapefile comes from the Boundary Review Commission for England in 2024. Note: there are some constituencies which are predominately served by National Grid Electricity Distribution and Scottish and Southern Energy Networks. These are included, as electricity networks do not match up with administrative boundaries. Methodological Approach Data Extraction: The shapefile is downloaded from the Boundary Commission for England. Data Filtering: Only parliamentary constituencies that are served by UK Power Networks are included. Quality Control Statement Quality Control Measures include: Manual review and correction of data inconsistencies Use of additional verification steps to ensure accuracy in the methodology Assurance Statement The Open Data Team checked to ensure data accuracy and consistency. Other Download dataset information: Metadata (JSON) Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: Open Data Portal Glossary4last year
- Latest Demand Statistics (Voltage, Active Power, ReActive Power, Generation) by Grid Supply Point (GSP).This dataset shows data from a sample of GSPs which account for 1/5th of the total GSPs in our area (we will add more sites across the network in future). Please note that not all of the connected generation is metered. This means that some connected generators in our networks do not supply live output data and are therefore not included in the data table.This data is refreshed every 30 minutes.To streamline and enable faster data refresh, we have structured our data into a header file which is light. Methodological Approach The power flow data is streamed from our PI server, into an FTP server before being published on the Open Data Portal. To streamline and enable faster data refresh, we have structured our data into a header file which is light. Quality Control Statement The data is published as is from the network. Assurance Statement The Open Data Team and DSO Data Science Team worked together to ensure data accuracy and consistency. Other Definitions of key terms related to this dataset can be found in the Open Data Portal Glossary: https://ukpowernetworks.opendatasoft.com/pages/glossary/Download dataset information: Metadata (JSON)2last year
- This is where you will find all our documentation relating to datasets within the Open Data Portal, and other documents such as, our Open Energy Data Maturity assessment - which indicates our baseline position on our Open Energy Data journey, and our Open Data Principles. 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/23 years ago
- Shapefile showing local authority boundaries within the UK Power Networks area (across all licence areas). District/Borough councils and Unitary Authorities are shown. Contains public sector information licensed under the Open Government Licence v3.0. 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/43 years ago
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