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 109 of 109 results
- 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 soil data to 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: https://ukpowernetworks.opendatasoft.com/pages/glossary/1Licence not specified11 months 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 Project Progression 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.1Licence not specified11 months 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 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)1Licence not specified11 months 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/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 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/1Licence not specified11 months ago
- Introduction Active transformer characteristics from our Primary Sites. Methodological Approach Data stems from our data warehouse 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 Glossary1Licence not specified11 months 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/1Licence not specified11 months 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/1Licence not specified11 months 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. 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 vectorized yet, so the dataset provides only partial coverage. Refer to our EPN Vectorisation Delivery Plan. 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/1Licence not specified11 months 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 and Network Development Plan 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: Glossary.1Licence not specified11 months ago
- 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 Glossary1Licence not specified11 months 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/1Licence not specified11 months 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 Glossary1Licence not specified11 months 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 categorizes 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. 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. Energy reduction has been estimated using a recent history baseline. Future enhancements will look at using more sophisticated baseline estimation methodologies. 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 categorize 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 minimize 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.1Licence not specified11 months ago
- Introduction This dataset contains the geographical locations of Low Voltage overhead lines that are in use in the UK Power Networks license areas. Locations are available as Geo Point (latitude and longitude) and Geo Shape. The dataset can be downloaded as a shapefile. Please be aware that not all locations are fully vectorized yet, so the dataset provides only partial coverage. Refer to our EPN Vectorisation Delivery Plan. 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 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 Glossary1Licence not specified11 months 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.1Licence not specified11 months 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 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/1Licence not specified11 months 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 Networks1Licence not specified11 months 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. Vectorisation: Shapefiles will be regularly updated to account for vectorisation updates. Quality Control Statement Please be aware that not all locations are fully vectorized yet, so the dataset provides only partial coverage. Refer to our EPN Vectorisation Delivery Plan. 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 Glossary1Licence not specified11 months 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.1Licence not specified11 months 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 29 November 2024), 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 and Network Development Plan 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 Glossary1Licence not specified11 months 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/1Licence not specified11 months 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 29 November 2024. More information and full reports are available from the landing page below: Long Term Development Statement and Network Development Plan 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/1Licence not specified11 months ago
- Introduction The dataset provides detailed information about UK Power Networks' Grid 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 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 Districts (April 2020) Names and Codes in the United Kingdom - data.gov.ukContains 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/1Licence not specified11 months 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. Vectorisation: Shapefiles will be regularly updated to account for vectorisation updates. Quality Control Statement Please be aware that not all locations are fully vectorized yet, so the dataset provides only partial coverage. Refer to our EPN Vectorisation Delivery Plan. 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/1Licence not specified11 months 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/1Licence not specified11 months ago
- Our Distributed Future Energy Scenarios Network Scenario Headroom Report (DFES NSHR) is part of our Network Development Plan (NDP). The April 2024 DFES NSHR dataset uses our 2023 network, loading and scenario data, with the Long Term Development Statement November 2023 as baseline. For further information on the NDP and the methodology to produce the DFES NSHR dataset please see Long Term Development Statement and Network Development Plan Landing Page The DFES NSHR indicates the amount of unused network capacity for demand and generation over time to 2050 on our Bulk Supply Point and Primary substations. It shows where we may need to further reinforce our substations or procure flexibility services beyond our existing plans, if the energy system develops as indicated in each of our scenarios. 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 headroom tables show firm capacity - 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 2024 LTDS. As noted in the methodology, unused substation capacity (headroom) is indicative and may be already contractually-committed to specific customers. Methodological approach 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 over the next 5 to 10 years. Data Collection: Gathering data from various sources, including historical usage patterns, projected growth in renewable energy, and changes in regulatory frameworks. Analysis of Network Capacity: Assessing the current capacity of the network to identify areas where reinforcement or upgrades are necessary. This includes evaluating substations and distribution lines. Option Development: Creating potential solutions to address identified constraints. This may involve traditional reinforcement methods or exploring flexibility services that can alleviate pressure on the network. Stakeholder Engagement: Consulting with stakeholders, including local authorities, developers, and energy providers, to gather input and ensure the plans align with community needs and regulatory requirements. 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 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/1Licence not specified11 months 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 29 November 2024), 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 and Network Development Plan Landing Page 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 Glossary1Licence not specified11 months 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/1Licence not specified11 months 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 29 November 2024), 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 and Network Development Plan 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 Glossary1Licence not specified11 months 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 29 November 2024), 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/1Licence not specified11 months 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/1Licence not specified11 months 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/1Licence not specified11 months ago
- 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/1Licence not specified11 months 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 29 November 2024. 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 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 Glossary1Licence not specified11 months 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/1Licence not specified11 months 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/1Licence not specified11 months 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/1Licence not specified11 months 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 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/To view this data please register and login.1Licence not specified11 months 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)1Licence not specified11 months 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/1Licence not specified11 months ago
- Shown on a rolling 3 month period, number of API calls on the UK Power Networks' open data portal.1Licence not specified11 months 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/1Licence not specified11 months 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. 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/1Licence not specified11 months 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 29 November 2024), 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 and Network Development Plan 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/1Licence not specified11 months 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 Glossary1Licence not specified11 months 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/1Licence not specified11 months 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 Glossary1Licence not specified11 months 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 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 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.Additional informationDefinitions 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 Networks1Licence not specified11 months 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/1Licence not specified11 months ago
- 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/1Licence not specified11 months 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/1Licence not specified11 months 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 29 November 2024. 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 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/1Licence not specified11 months 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 29 November 2024), 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 and Network Development Plan 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/1Licence not specified11 months 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/1Licence not specified11 months 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 29 November 2024. 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 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 Glossary1Licence not specified11 months 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. 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/1Licence not specified11 months 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 soil data to 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: https://ukpowernetworks.opendatasoft.com/pages/glossary/1Licence not specified11 months 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 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/1Licence not specified11 months 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)1Licence not specified11 months 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. Methological 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 Networks1Licence not specified11 months 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 Networks1Licence not specified11 months 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. 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. 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. 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 Glossary1Licence not specified11 months 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/1Licence not specified11 months 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) license 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. 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 vectorized yet, so the dataset provides only partial coverage. Refer to our EPN Vectorisation Delivery Plan. 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.1Licence not specified11 months 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 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.To find half-hourly current and power flow data for a transromer, 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 Networks1Licence not specified11 months 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. 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 vectorized yet, so the dataset provides only partial coverage. Refer to our EPN Vectorisation Delivery Plan. 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/1Licence not specified11 months 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 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.1Licence not specified11 months 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 monthly. 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 monthly. 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 Glossary1Licence not specified11 months 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.com 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/1Licence not specified11 months 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/1Licence not specified11 months 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/1Licence not specified11 months 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/1Licence not specified11 months 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.1Licence not specified11 months 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. 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/1Licence not specified11 months 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. 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. 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.1Licence not specified11 months 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 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: https://ukpowernetworks.opendatasoft.com/pages/glossary/1Licence not specified11 months 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/1Licence not specified11 months 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 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/1Licence not specified11 months ago
- Introduction Shapefile showing UK Power Networks' 132kV overhead lines. 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 vectorized yet, so the dataset provides only partial coverage. Refer to our EPN Vectorisation Delivery Plan. 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/1Licence not specified11 months ago
- 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/1Licence not specified11 months 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 29 November 2024. 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 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/1Licence not specified11 months ago
- IntroductionHigh level statistics for each Licence Area taken from the Regulatory Instructions and Guidance (RIGs) submission 2023 / 2024. 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/1Licence not specified11 months 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. Vectorisation: Shapefiles will be regularly updated to account for vectorisation updates. Quality Control Statement Please be aware that not all locations are fully vectorized yet, so the dataset provides only partial coverage. Refer to our EPN Vectorisation Delivery Plan. 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 Glossary1Licence not specified11 months 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/1Licence not specified11 months ago
- IntroductionShapefile showing UK Power Networks' 66kV overhead lines. 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 vectorized yet, so the dataset provides only partial coverage. Refer to our EPN Vectorisation Delivery Plan. 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/1Licence not specified11 months 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 20 November 2024. 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/1Licence not specified11 months ago
- IntroductionThis dataset shows the utilisation band of our secondary sites across our three networks, over 1 April 2022 to 31 March 2023. 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/1Licence not specified11 months 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 Glossary1Licence not specified11 months ago
- Introduction The dataset presented shows import consumption data at secondary substation level, together with a count of smart meters contributing the aggregated half-hourly values. The data shown now includes values for both Active Energy import and Reactive. This dataset is currently from 40,000 smart meters in our Eastern Power Networks (EPN) region. This will be gradually expanded during 2025 to include both import and export energy data from all smart meters within our three regions of EPN, London Power Networks (LPN), and South Eastern Power Networks (SPN). Methodological Approach Primary Consumption Active Import is aggregated from the number of active devices during a half hour period. Note: if a device was not contactable during a half period, its data is not aggregated.Quality Control Statement Please be aware that this data is being made available to provide an early insight of what we propose to publish from all smart meters within our regions. We continue to carry out data validation checks to improve data quality before publishing the full dataset - so suggest caution if you plan to utilize this currently available information. We will update this message once the full dataset that includes both import and export energy data is published. Please provide any thoughts, comments, or suggestions here. Assurance Statement The Smart Metering Team has checked 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)1Licence not specified11 months 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/1Licence not specified11 months ago
- 13/08/2024: Please note we have removed the data table due to data being out of date. We are working to improve upon this by providing a more regularly updated dataset.This dataset contains data captured from remote Power Quality logging devices. It represents the last 7 days of the required ENA (The Energy Network Association) Engineering Recommendation (EREC) G5/5 data. 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/1Licence not specified11 months ago
- Introduction 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 Glossary1Licence not specified11 months 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=2022-11-02&ss=bfqt&srt=sco&sp=rlp&se=2025-10-16T17:48:02Z&st=2024-10-16T09:49:02Z&spr=https,http&sig=sJUKAh698V2nQ8dBAmXBw6FIZooyhXGmWgAXkyfbadI%3DShared Access Signature URL (SAS)https://ukpnoppublicdata001.blob.core.windows.net/optimiseprime?sv=2022-11-02&ss=bfqt&srt=sco&sp=rlp&se=2025-10-16T17:48:02Z&st=2024-10-16T09:49:02Z&spr=https,http&sig=sJUKAh698V2nQ8dBAmXBw6FIZooyhXGmWgAXkyfbadI%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 Prime1Licence not specified11 months ago
- Introduction The dataset presented shows import consumption data at a low voltage (LV) feeder level, together with a count of smart meters contributing the aggregated half-hourly values. The data shown now includes values for both Active Energy import and Reactive. This dataset is currently from 40,000 smart meters in our Eastern Power Networks (EPN) region. This will be gradually expanded during 2025 to include both import and export energy data from all smart meters within our three regions of EPN, London Power Networks (LPN), and South Eastern Power Networks (SPN). Methodological Approach Primary Consumption Active Import is aggregated from the number of active devices during a half hour period. Note: if a device was not contactable during a half period, its data is not aggregated.Quality Control Statement Please be aware that this data is being made available to provide an early insight of what we propose to publish from all smart meters within our regions. We continue to carry out data validation checks to improve data quality before publishing the full dataset - so suggest caution if you plan to utilize this currently available information. We will update this message once the full dataset that includes both import and export energy data is published. Please provide any thoughts, comments, or suggestions here. Assurance Statement The Smart Metering Team has checked 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)1Licence not specified11 months 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/1Licence not specified11 months 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 29 November 2024), 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 and Network Development Plan 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/1Licence not specified11 months ago
- Introduction Active transformer characteristics from our Grid Sites. Methodological Approach Data stems from our data warehouse 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 Glossary1Licence not specified11 months ago
- IntroductionDaily Demand Statistics (Minimum, Average, Maximum) for the last 12 months 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). This data is refreshed at midnight daily. Methodological Approach This dataset is extracted from UK Power Networks ADMS database. 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 DSO Data Science team has checked this dataset to ensure data accuracy and consistency. OtherDefinitions 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)1Licence not specified11 months ago
- Shown on a rolling 3 month period, number of datasets downloaded from UK Power Networks' open data portal.1Licence not specified11 months 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/1Licence not specified11 months 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/1Licence not specified11 months 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/1Licence not specified11 months ago
- Shown on a rolling three month period, number of unique users to the UK Power Networks' open data portal.1Licence not specified11 months 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/1Licence not specified11 months 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 Networks1Licence not specified11 months 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/1Licence not specified11 months ago
- 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)1Licence not specified12 months ago
- 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/1Licence not specifiedalmost 3 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/1Licence not specifiedalmost 3 years ago
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