Results: Search for UK Electricity Market

This is an evidence base of available literature on the impacts of offshore wind farm (OWF) developments and the outcomes for marine ecosystem services. The evidence was collated through a systematic search of global primary literature (also known as peer-reviewed or published literature) and UK grey literature regarding the impacts of OWF developments (the scope for including global grey literature was unfeasible). Grey literature refers to multiple types of report or document, and is defined as: "information produced on all levels of government, academia, business and industry in electronic and print formats not controlled by commercial publishing" i.e. where publishing is not the primary activity of the producing body(ICGL, 1997). Data was extracted from each evidence source, for each subject or marine ecosystem component that was impacted by the OWF development, the phase of development, the specific pressure and other relevant information about the wind farm or location. Expert judgement was used to map each piece of evidence for impacts on the marine environment according to CICES (Common International Classification of Ecosystem Services) or MEA (Millenium Ecosystem Assessment) and other published classification systems for ecosystem services (Ryfield et al., 2019; Hooper et al., 2020). The dataset was created to provide a central evidence base of available primary and grey literature regarding the impacts of OWF developments (for construction, operational and decommissing phases) on ecosystem service outcomes in the marine environment. The primary literature represents a global semi-systematic search, while the grey literature is restricted to a semi-systematic search for reports and documents from the UK (that also include wind farms in adjacent waters). The database provides a comprehensive list of available literature on this topic, and it enables the assessment and comparison of the evidence for enviromental impacts and ecosystem service outcomes between primary and grey literature sources. This will be critical for marine policy makers when gathering evidence for future OWF developments and advances understanding of the impacts and trade-offs associated with OWF and ecosystem services. A tool (currently in development by Plymouth Marine Laboratory) will improve accessibility of the data for this purpose. This research was funded by the UKERC Phase 4 research programme.

High voltage electricity network data for Ireland, Northern Ireland and for all island of Ireland. Data include system demand and generation, wind generation, interconnection, balancing and prices, frequency, system non-synchronous penetration, carbon intensity and network maps. Can select Ireland, Northern Ireland or all island data.

Electricity North West is a distribution network operator. Data available includes network data, network assets, capacity and embedded generation. Electricity North West is a distribution network operator (DNO) covering the north-west of England.

Half-hourly electricity daily load profiles for standard UK profile class definitions (01 Domestic Unrestricted; 02 Domestic Economy 7; 03 Non-domestic Unrestricted; 04 Non-domestic Economy 7; 05 Non-domestic Maximum Demand 0-20% Load Factor; 06 Non-domestic Maximum Demand 20-30% Load Factor; 07 Non-domestic Maximum Demand 30-40% Load Factor; 08 Non-domestic Maximum Demand >40% Load Factor) for weekday (Wd), Saturday (Sat), and Sunday (Sun) at five different times of year (Autumn Aut, Winter Wtr, Spring Spr, High Summer HSr, Summer Smr) The year is broken down into the following seasons: (a) Spring: defined as the period from the day of clock change from GMT to BST in March, up to and including the Friday preceding the start of the summer period; (b) Summer: defined as the ten-week period, preceding High Summer, starting on the sixteenth Saturday before the August Bank Holiday; (c) High Summer: defined as the period of six weeks and two days from the sixth Saturday before August Bank Holiday up to and including the Sunday following August Bank Holiday; (d) Autumn: defined as the period from the Monday following the August Bank Holiday, up to and including the day preceding the clock change from BST to GMT in October; (e) Winter: defined as the period from the day of clock change from British Summer Time (BST) to Greenwich Mean Time (GMT) in October, up to and including the day preceding the clock change from GMT to BST in March.
For creation and first use of the data see: Load Profiles and their use in Electricity Settlement (Load_Profiles.pdf)

ELEXON Ltd is the Balancing and Settlement Code Company (BSCCo) defined and created by the Balancing and Settlement Code (BSC and also known as the Code). ELEXON Ltd procures, manages and operates services and systems, which enable imbalance settlement of the wholesale electricity market and retail competition in electricity supply. The Portal gives access to the archives of historic SSP, SBP and NIV data which are updated automatically every day, and historical BMRS data via the BMRA Data Archive on this site (formerly TIBCO Relay Service). The Elexon portal gives access to historical data from the Balancing Mechanism Reporting System (BMRS) (which only retains around 18 months of data online) along with reports and other publications, policy information and the contents of the actual BMRS code. There is a useful site map at the bottom of the home page.

ENERGYDATA.INFO is an open data platform providing access to datasets and data analytics that are relevant to the energy sector. Data on energy access, transmission and distribution, renewable energy and resource assessment. Tools and data sets are available.

Energy Networks Association databases including statutory data, safety statistics, engineering standards and terms, and an Energy Data Request Tool for requesting any type of network data. The Energy Data Request Tool can be used by anyone to request any type of network data.

European electricity harmonisation and electrotechnical standards, based on a consensus, which reflects the economic and social interests of 33 CENELEC Member countries channelled through their National Electrotechnical Committees (NCs). Most standards are initiated by industry. Other standardization projects can come from consumers, Small and Medium-sized Enterprises (SMEs) or associations, or even European legislators. Besides European Standards, CENELEC produces other reference documents, which can be developed quickly and easily: Technical Specifications, Technical Reports and Workshop Agreements. CENELEC is a Non Profit International Association, forming the officially recognised European Standards Organisations (ESOs) together with CEN, the European Committee for Standardization and ETSI, the European Telecommunications Standards Institute. CENELEC acts as a platform for experts to develop European Standards (ENs), which facilitate world trade by removing barriers to trade, enhancing economic growth and leading to new markets.CENELEC concentrates most of its work on 2 major deliverables: The European Standard (EN) and the Harmonization Document (HD). These two documents are referred to commonly as "standards" and must be implemented in all CENELEC member countries, who must also withdraw any conflicting standard.

Measuring and Evaluating Time-use and Electricity-use Relationships (METER) data on UK household electricity use, activities and other contextual and demographic information. High-resolution household electricity readings with simultaneous activity records of household members. This study is subject to restrictive Secure Access conditions as it contains an additional detailed activities variable. The End User Licence (EUL) version which is the same, but excludes this detailed variable, is available from the UK Data Service under SN 8634. Users are advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.

Data Portal for National Grid Electricity System Operators (ESO) in Great Britain. Data available include: ancillary services, balancing costs, carbon intensity, connection registers, constraint management, demand, generation, network charges, system-wide data, trading, plans, reports and Future Energy Scenarios. An API is available.

A forecast of electricity use in the UK in the next ten years, with different scenarios base on different assumptions about demand, supply and European interconnection. Published annually. The PDF report gives the overview and scenario forecasts. All the supporting data is downloadable to Excel.

Automated Demand Response trials within the New Thames Valley Vision (NTVV) project installed Building Management Systems within 27 commercial buildings within the Bracknell area. The project was then able to enact load shed events on the building with differing notice periods. Background information on the NTVV project and the ADR trial can be found in report SDRC_9.1c_Demand_Side_Response_Evidence_Report_1.0.pdf

The data set records EMMA thermal storage devices trialed in the New Thames Valley Vision (NTVV) project and includes PV and grid data for 73 households. The EMMA unit is a device which is fitted in conjunction with Solar PV installs in properties that have an immersion heater. The device diverts any excess generation energy, into the immersion heater to heat water, rather than send the excess electricity back onto the grid. The data set records EMMA, PV and grid data for 73 households.
Background information on the NTVV project and the EMMA trial can be found in report SDRC_9.4b_Evidence_Report_1.0.pdf.
Data format information is in EMMA_readme.txt.

End point monitoring of household electricity demand and generation carried out within the New Thames Valley Vision (NTVV) project. End Point Monitoring in domestic households was carried out with two types of devices with 30 minute granularity. The data are described in EPM_readme.txt.
Background information on the NTVV project and end point monitoring with the EDMI units can be found in SDRC_9.2a_Evidence_Report_Rev_1.0_Final.pdf.

Data from a trial of an Ice Bear cold thermal energy storage unit in one building during the New Thames Valley Vision (NTVV) project. This data records the trial of one Ice Bear unit in the New Thames Valley Vision (NTVV) project. The Ice Bear unit provides a block of ice, which is installed as part of an air conditioning system. During the day, the air conditioning unit will blow air through the ice, creating cool air. During the night, the Ice Bear will freeze the ice again, ready for use the next day, so deferring energy usage from the day time, to the night time.
The data format is described in Ice_Bear_readme.txt.
Background information on the NTVV project and the Ice Bear unit can be found in report SDRC_9.8a_4_Cold_Thermal_LV_Network_Energy_Storage.pdf.

Monitoring data from 4 primary and 316 secondary substations in the New Thames Valley Vision (NTVV) project. Information about the substations data can be found in Substations_readme.txt.
Background information on the NTVV project and substation monitoring can be found in SDRC_9.2b_Evidence_Report_Rev_1.0.pdf.

Northern Power Grid is a distribution network operator. Their network data includes Distribution Future Energy Scenarios, Auto Design connection tool, embedded generation capacity register, long-term development statement (including network information), generation and demand heat maps, and contracted capacity register. Northern Power Grid is a distribution network operator (DNO) covering north east England, Yorkshire and north Lincolnshire.

Great Britain energy market data from the retail market, from the wholesale market, energy network indicators and customer service data. Material featured on the Ofgem website is subject to Crown copyright protection unless otherwise indicated. You may use Crown copyright information (not including logos) free of charge in any format or medium, under the terms of the Open Government Licence.

Spatially disaggregate half-hourly data on GB electricity generation and consumption, including detailed per-generator half-hourly generation and balancing operations. The P114 data will be uploaded in batches currently the dataset contains folders for data released in June 2016, then yearly from January 2018 to January 2022 and then quarterly from January 2023 to present with the latest release April 2024. A data description document or read me file is available for each release. NB the number of records is very large - indicated by the value of 999M in the number of records field.

UK Government has collected and compiled estimates of electricity consumption at regional (NUTS1) and local authority levels (LAU1 - formally NUTS 4) using aggregated Meter Point Reference Number (MPRN) readings throughout Great Britain as part of government's annual meter point electricity data exercise. In March 2008, this electricity consumption dataset gained National Statistics status. This status applies to all data from 2005 onwards. The 2003 and 2004 data are still classed as experimental.

Flexible Networks for a Low Carbon Future was a Low Carbon Networks Fund innovation trial project, led by SP Energy Networks. As part of the project, network monitoring equipment was installed in eight primary (33/11kV) and over 150 secondary (11kV/415V) substations in three test areas

SP Energy Networks are pleased to provide access to the complete data set (which is hosted by the University of Strathclyde) in response to requests.

SP Energy Networks is a distribution and transmission network operator. The data hub includes mapping data, strategic documentation, asset data and stakeholder data. SP Energy Networks is the distribution network operator for northern Wales, southern Scotland and part of north-west England. It is also the transmission operator for southern Scotland.

Scottish and Southern Electricity Networks is a distribution and transmission network operator. The embedded capacity register includes generation and storage resources (1MW) that are connected, or accepted to connect. It includes information on the flexibility services that are being provided by connected resources. Scottish and Southern Electricity Networks is the distribution network operator (DNO) for central southern England and northern Scotland. It is the transmission operator for southern Scotland.
The embedded capacity register provides information on generation and storage resources (1MW) that are connected, or accepted to connect, to the electricity distribution networks owned and operated by us and it will be updated on a monthly basis. The register also includes information on the flexibility services that are being provided by connected resources, assisting to control or schedule demand and/or generation to reduce network constraints. As of July 2020, the register has been updated to include additional data fields and information including the network reinforcement needed to provide connections.

Scottish and Southern Electricity Networks is a distribution and transmission network operator. Data available include network assets maps, generation availability map, demand heat map, loading and rating information and high voltage schematics, long-term development statement and technical specifications. Scottish and Southern Electricity Networks is the distribution network operator (DNO) for central southern England and northern Scotland. It is the transmission network operator for northern Scotland.

The SERL research portal will allow accredited UK academic researchers access to pseudo-anonymised gas and electricity smart meter data via a Secure Lab environment. Access is for accredited UK researchers only and must be applied for. Researchers must apply for accreditation to access the data.

Quarterly statistics on the roll-out of smart meters in Great Britain, covering meters operating and meters installed. These quarterly updates on the smart meter roll-out in Great Britain report on the numbers operated and installed for: smart meters in domestic properties; smart and advanced meters in smaller non-domestic sites.
Data on large suppliers is updated each quarter, with an end-year update which includes details on the whole energy market. Historic data available on request.

High speed (16 kHz) power meter data for 3 houses.
Data is stored in individual directories for each house.

NOTE to UK-DALE data users: the UK-DALE data sets are large. It may not be possible to download all the data in one go.

See Kelly, J. and Knottenbelt, W. The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes. Sci. Data 2:150007 doi: 10.1038/sdata.2015.7 (2015). arXiv:1404.0284 (2015)
This data is made freely available under Creative Commons Attribution 4.0 International (CC BY 4.0). See more at https://creativecommons.org/licenses/by/4.0/

Appliance-by-appliance and whole-home power demand for 5 UK homes recorded approximately once every 6s. For 3 of the homes, whole-home data was also recorded at 1s and 16kHz
Data is stored in individual directories for each house. Each appliance has a separate time series file channel_nn.dat and most have a channel_nn_button_press.dat file indicating switching events (see Other Information).

NOTE to UK-DALE data users: the UK-DALE data sets are large. It may not be possible to download all the data in one go.

See Kelly, J. and Knottenbelt, W. The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes. Sci. Data 2:150007 doi: 10.1038/sdata.2015.7 (2015). arXiv:1404.0284 (2015)
This data is made freely available under Creative Commons Attribution 4.0 International (CC BY 4.0). See more at https://creativecommons.org/licenses/by/4.0/

High speed (16 kHz) whole-house voltage and current data for 1 house. Data is stored in individual directories for each week. This dataset continues UK-DALE-2015 : UK-DALE-16kHz

NOTE to UK-DALE data users: the UK-DALE data sets are large. It may not be possible to download all the data in one go.

This data set continues UK-DALE-2015 : UK-DALE-16kHz
There is further information on UK-DALE-2015, which is also relevant to this data set, in Kelly, J. and Knottenbelt, W. The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes. Sci. Data 2:150007 doi: 10.1038/sdata.2015.7 (2015). arXiv:1404.0284 (2015)
This data is made freely available under Creative Commons Attribution 4.0 International (CC BY 4.0). See more at https://creativecommons.org/licenses/by/4.0/
There is a README associated with these data at ReadMe_DALE-2017 (#HighSpeed section).

The Electricity Pool operated from 1st April 1990 to 26th March 2001, controlling the trading of electricity within England and Wales. The Electricity Pool data contains system demand and transmission losses plus the price information (/MWh) within the trading pool, comprising the three main prices: Pool purchase price (PPP), the basis of payments to generators; Pool selling price (PSP), the basis of payments by suppliers; and system marginal price (SMP), the highest offered price for any generating set scheduled by the Pool to run before system constraints are taken into account. The Electricity Pool system was replaced by the New Electricity Trading Arrangements (NETA/BETTA) from 27 March 2001. (Note : It is mandatory to acknowledge the UKERC EDC and the data owner Poolit Ltd when any use of this data is made in publications) Explanation of parameters and pool operation
PSP : Pool Selling Price, is the price paid mostly by RECs purchasing electricity from the Pool to sell to their final commercial, industrial and residential customers; this value is determined for two distinct price-rule regimes referred to as Table A and Table B periods, such that: PSP = SMP + CC + UPLIFT = PPP + UPLIFT
SMP : System Marginal Price is the highest offered price for any generating set scheduled by the Pool before system constraints are taken into account
LOLP : Loss Of Load Probability, a decreasing function of the expected amount of excess capacity available during each half-hour period, determined for each half-hour as the probability of a supply interruption due to generation capacity being insufficient to meet demand (the greater the amount of capacity available relative to expected demand in any half-hour, the lower the LOLP and therefore the lower the capacity charge per KWH paid to generators)
VOLL : Value Of Lost Load, representing the per kWh willingness of customers to pay to avoid supply interruptions; it was set by the Director General of the Office of Electricity Regulation (OFFER) at 2,000 per megawatt-hour (MWH) for 1990/91 and was then increased annually by the growth in the RPI
PPP : Pool Purchase Price, is the price paid to generators for electricity purchased into the Pool
CC : Capacity Charge: CC = LOLP * (VOLL - SMP) is a signal to generators of the necessity for additional generation capacity and to consumers that their consumption has a significant probability of requiring the maximum amount of generating capacity available in that load period
UPLIFT : a charge to compensate generators for reserve, plant available but not actually used to meet demand, and startup costs, known only ex post and therefore the only price uncertainty from the day ahead perspective; it is collected over at least 28 Table A pricing periods each day (UPLIFT is zero for Table B pricing periods) according to the formula: Availability Payment/MWh = LOLP*(VOLL - max(SMP, bid price))

Annual, quarterly and monthly electricity statistics available to download. This page brings together all the UK Government data sources that focus on electricity including historic data (1920-2012) and imports, exports and transfers of electricity Brings together electricity data from DUKES (annual data), energy trends (articles, quarterly and monthly data) and historic data. These datasets form part of other dataset collections in the UK Government statistics.

UK Power Networks distribution network operators open data include data about their networks, operations, embedded generation and market intelligence data. UK Power Networks are the distribution network operator (DNO) for parts of eastern and south eastern England and London. Data is open, but new users will need to register.

This dataset relates to the modelling component of the UKERC Phase 4 Project '4.2a Investment in infrastructure'. The aim is to assess the scale of investment risks in the electricity generation sector associated with uncertainty over the pathway towards net zero. The model comprises three components:1. Input data. Based in Excel, contains the scenario assumptions on the electricity system including generation technologies, wind and solar power availability, demand profiles, interconnector and storage capacities etc.2. Modelling files based on the open-source Antares modelling framework. This requires additional free software to be able to run the model. The model calculates the hourly dispatch of all types of plant included in the system.3. Excel-based financial model, based on post-processing the output of the Antares model.Additional 1_Metadata.xls, Input_ReadMe and Outputs_ReadMe files explain the method for running each step of the modelling process. Software available at https://antares-simulator.org/. Version used 8.0.2

Meteorological and panel production data from the solar PV project - Southerly Winds Increase the Electricity Generated by Solar Photovoltaic Systems. This project looked at meteorological effects on solar panel electricity output in a field-based setting, demonstrating how differences in exposed surface area under northerly and southerly winds can affect the efficacy of surface cooling with implications for electricity output. This project, Southerly Winds Increase the Electricity Generated by Solar Photovoltaic Systems, is further described in this journal article: https://www.sciencedirect.com/science/article/abs/pii/S0038092X20303303?dgcid=author.

Western Power distribution network operators Connected Data Portal includes data about their networks, operations, generation included embedded generation, flexibility and trial projects. Western Power Distribution is the electricity distribution network operator (DNO) for the Midlands and South West of England and for South Wales.