Results: Search for Commercial

This knowledge building project aims to outline a number of price scenarios for the retail price of electricity across a number of different energy vectors in 2030. This project, delivered by Baringa, builds on their existing time series of hourly supplier electricity costs for 2030. They delivered an hourly electricity price series for 2030 based on traceable assumptions for three different 2030 supply-demand scenarios. The key objectives were:

1. To investigate the costs that domestic electricity suppliers in Great Britain might face in 2030.
2. To make projections on the assumption that, unless formally announced, no changes are made to the electricity market arrangements in place today
3. To focus in particular on the hourly variation and seasonal shape of supplier costs

This spreadsheet provides figures for key inputs to be used for the projection of theretail cost stack in 2030. All figures refer to year 2030 unless otherwise stated. Money is in 1st January 2017 terms unless otherwise stated.

This knowledge building project aims to outline a number of price scenarios for the retail price of electricity across a number of different energy vectors in 2030. This project, delivered by Baringa, builds on their existing time series of hourly supplier electricity costs for 2030. They delivered an hourly electricity price series for 2030 based on traceable assumptions for three different 2030 supply-demand scenarios. The key objectives were:

1. To investigate the costs that domestic electricity suppliers in Great Britain might face in 2030.
2. To make projections on the assumption that, unless formally announced, no changes are made to the electricity market arrangements in place today
3. To focus in particular on the hourly variation and seasonal shape of supplier costs

This deliverable accompanies the slide pack Retail Supply Cost Analysis Purpose of workbook: To provide the key outputs for the three scenarios and the historical year 2017:

1. Hourly Prices: Detailed Retail Cost Stacks
2. Annual Figures ( to add ) :
   • Installed Capacity
   • Generation
   • Wholesale price and captured prices for renewable technologies
   • Imports and exports with neighbouring markets
   • Total carbon dioxide emissions

The three scenarios refer to the year 2030. The year 2017 has been added for comparison purposes. Money is in 1st January 2017 terms unless otherwise stated

The BMRS website provides near real time and historic data about the Balancing Mechanism which is used by the National Grid (System Operator) as a means of balancing power flows on to and off the electricity Transmission System in Great Britain. Data is added on a near real-time basis

This spreadsheet model was produced as part of the CCS Capture Benchmark Refresh Study, and provides a techno-economic analysis of the performance of a state-of-the art CCGT with and without amine capture at 90% capture rate. The spreadsheet enables 'what if' calculations of costs for the following designs: CCGT with and without capture, at 100% and 40% load; CCGT with and without capture, with 38% and 18% exhaust gas recycle rates, at 100% and 40% load; CCGT with an independent capture plant, generating its own power and steam, at 100% load; CCGT with an independent capture plant, generating its own steam only, at 100% load CCGT with retrofitted capture plant, at 100% load. Outputs include capital costs, operating costs, cost of capture and levelised cost of electricity. The spreadsheet concentrates on power generation, capture and compression, but allows manual input of transport and storage costs to provide overall figures. These cases are covered in Benchmark Refresh reports D2.1 (refresh of CCGT benchmark and EGR) and D7.1 (Independent Capture Plant). It should be noted that the underlying capture plant designs were reviewed as part of the Independent Capture Plant work, so the results given by this spreadsheet for the earlier cases may not precisely match those presented in Report D2.1.

CO2 Stored provides access to overview data for over 500 potential CO2 storage sites around offshore UK. The data originate from the UK Storage Appraisal Project (UKSAP) which assessed the UKs CO2 storage capacity for carbon capture and storage (CCS). It is updated, validated and built on as part of The Crown Estate and BGSs ongoing development. The database includes derived data for each storage unit including: location, storage unit type, lithology, water depths, porosity, permeability, formation thickness, formation depth, pressures, and salinity. The original data was developed by the UK Storage Appraisal Project (UKSAP), which was commissioned and funded by the <a href="http://www.eti.co.uk/" target="_blank">Energy Technologies Institute (ETI) </a>. It is hosted and further developed by the <a href="http://www.bgs.ac.uk/">British Geological Survey (BGS) </a> and <a href="http://www.thecrownestate.co.uk/">The Crown Estate </a>.It contains derived geological data, storage estimates, risk data and economics for nearly 600 potential CO₂ storage units located offshore UK. These include oil and gas reservoir and saline aquifers. Each storage unit contains information giving storage estimates, risk data and economics. For most of the data fields a minimum, most likely and maximum values are recorded. The source of the data is recorded as well as a confidence rating in the data provided.

CARMA is a database containing information about the carbon emissions of over 60,000 power plants and 20,000 power companies worldwide. Power generation accounts for 40% of all CO₂ emissions in the United States and about one-quarter of global emissions. CARMA is the first global inventory of a major, emissions-producing sector of the economy. It cased being updated in 2012 but is available for downloading from the link. CARMA is produced and financed by the Center for Global Development, an independent and non-partisan think tank located in Washington, DC.The objective of CARMA.org is to equip individuals with the information they need to forge a cleaner, low-carbon future. By providing complete information for both clean and dirty power producers, CARMA hopes to influence the opinions and decisions of consumers, investors, shareholders, managers, workers, activists, and policymakers. CARMA builds on experience with public information disclosure techniques that have proven successful in reducing traditional pollutants.For power plants within the U.S., CARMA relies upon data reported to the Environmental Protection Agency and Department of Energy by the plant operators themselves. CARMA also includes official reported emissions for many plants in the European Union, Canada, India, and South Africa and annual generation for all of the worlds nuclear power plants, as reported by the International Atomic Energy Agency. For non-reporting plants, CARMA estimates electricity generation and CO2 emissions using statistical models that have been fitted to detailed U.S. plant data and unit-level engineering and fuel specifications. CARMA v3.0 reports emissions for the year 2004, 2009, and the future (based on planned construction and retirements).
CARMA also aggregates data on individual plants to the level of companies and several geographic entities (continents, countries, states/provinces, and cities worldwide, with additional reports for U.S. metro areas, congressional districts, and counties). CARMA is meant to be a repository of the best available information on power sector carbon emissions. Our policy is to correct any errors or omissions if suggested revisions are verified by an independent third party.

Half hourly gas and electricity (and water) consumption data ( not all utilities were monitored at every site) gathered during the Carbon Trusts Advanced Metering for SMEs project (2004-2006). The data was collected from a portfolio of sites by seven independent metering contractors. Sites are characterized by the number of employees, the geographical location, and geographical region. (Please acknowledge The Carbon Trust when making any use of this data)
Meter readings are available for small and medium-sized enterprises (SMEs).The majority of meter readings are for electricity; monitoring of other utilities (gas and water) was available on some sites. Unless otherwise indicated data sets are for electricity; where multiple meters were deployed they are designated (e) for electricity, (g) for natural gas, and (w) for water. In a minority of cases metering on the site was split between several meters: (e1), (e2), etc. The absence of a link indicates some problems in matching the site identifier with the collected data set.
The sectors covered are:-

• Community, social and personal activities
• Education
• Financial and business services
• Government
• Health and social work
• Manufacturing
• Other sectors
• Wholesale and retail trade

A ReadMe page is provided for each subsector containing more detailed information for the datasets that are covered. Use of this data resource requires registration with edc: please contact the EDC Manager
The Carbon Trust has published a report summarising the findings of the project at http://www.ieadsm.org/Files/Content/Carbon%20Trust_2011-06-03.pdf and a full report on the advanced metering field trial, its results, findings and recommendations which is available alongside the data at http://data.ukedc.rl.ac.uk/simplebrowse/edc/efficiency/residential/Buildings/AdvancedMeteringTrial_2006/CTC713_AdvancedMeteringForSMEs.pdf.

Time series data for the carbon sequestration and air filtration ecosystem services in the urban environment. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The characteristics of 5 types of bioenergy feedstock crops were measured in relation to growing conditions and methods.

The Characterisation of Feedstocks Project was commissioned by The Energy Technologies Institute (ETI) and carried out by Forest Research, and Uniper Technologies Ltd (formerly part of E.ON).

Five crops were considered: Miscanthus, willow short-rotation-coppice (SRC), poplar SRC, poplar short-rotation-forestry (SRF), and conifer SRF.

Eight studies were carried out:
In phase 1 (fieldwork spring to autumn 2015):
1. To examine the impact of climate zone, soil type, harvesting time, and storage on Miscanthus, willow SRC, poplar SRC, poplar SRF and conifer SRF
2. To examine the variation between and within fields of Miscanthus and willow SRC
3. To examine the feedstock characteristics of willow SRC and poplar SRF leaves
4. To examine the feedstock characteristics of Miscanthus before and after pelletising
In phase 2 (fieldwork November 2015 to November 2016):
V1. To examine the impact of harvest time on Miscanthus characteristics
V2. To examine the impact of harvest time on willow characteristics
V3. To examine the impact of varieties on willow characteristics
V4. To examine the impact of storage time on Miscanthus characteristics

The Climate Change Levy (CCL) and Carbon Price Floor (CPF) Bulletin National Statistics present statistics from the different rates of CCL and CPF administered by HM Revenue and Customs (HMRC). As a result of the recent consultation on the reduction and consolidation of HMRC statistics publications, the CCL and CPF Bulletin will be published within the Environmental Taxes Bulletin annually from 30 June 2021.
Archive versions of the CCL and CPF Bulletin published on GOV.UK after January 2021 are hosted on this GOV.UK page.
Archive versions of the CCL and CPF Bulletin published between March 2008 and January 2021 are found on the UK Trade Info website.
User should note that between March 2008 and April 2013, the CCL and CPF Bulletin was called the CCL Bulletin before the introduction of CPF in 2013.

The annual State of the Sector report is a dataset about the community energy sector. It has always covered England and Wales, and in 2021 include Scottish data for the first time. Reports detail the data from the community energy sector in the previous year.

The objective of the Consumers, Vehicles and Energy Integration project is to inform UK Government and European policy and to help shape energy and automotive industry products, propositions and investment strategies. Additionally, it aims to develop an integrated set of analytical tools that models future market scenarios in order to test the impact of future policy, industry and societal choices. The project is made up of two stages:

• Stage 1 aims to characterize market and policy frameworks, business propositions, and the integrated vehicle and energy infrastructure system and technologies best suited to enabling a cost-effective UK energy system for low-carbon vehicles, using the amalgamated analytical toolset.
• Stage 2 aims to fill knowledge gaps and validate assumptions from Stage 1 through scientifically robust research, including real world trials with privatevehicle consumers and case studies with business fleets. A mainstream consumer uptake trial will be carried out to measure attitudes to PiVs after direct experience of them, and consumer charging trials will measure mainstream consumer PiV charging behaviours and responses to managed harging options

This spreadsheet is part of Deliverable D3.2, Battery State of Health Model, and accompanies the report on the development and validation of an algorithm that quantifies battery ageing based on input parameters that can be either inferred from Electric Vehicle (EV) usage or measured on-board. It contains the Battery State of Health Model, which provides a relatively high-level overview of battery degradation and state of health, which will be further developed during Stage 2 of the project

Spatial and other data about the management of Scotland's sea-bed, including for wind and marine energy and for carbon capture and storage. The data licence is unclear. We recommend contacting Crown Estate Scotland if you wish to re-use data made available by them.

The DOE Global Energy Storage Database provides free, up-to-date information on grid-connected energy storage projects around the world and relevant state and federal policies. There is a searchable database on projects and policies, with drill-down capability. In the Projects section, it is possible to drill-down to individual plants, detailing technology (e.g. Vanadium Redox Flow Battery), power, duration and status. This data can be downloaded and used freely subject to conditions of use. Data visualization is also available.

The mission of the US Department of Energy Hydrogen and Fuel Cells Program is to reduce petroleum use, greenhouse gas emissions, and air pollution and to contribute to a more diverse and efficient energy infrastructure by enabling the widespread commercialization of hydrogen and fuel cell technologies. The Program Records area contains supporting data for DOE publications, described as Program-related, Analysis, Fuel cells, Production/delivery, Safety codes, and standards and Storage The U.S. DOE Hydrogen and Fuel Cells Program works in partnership with industry, academia, national laboratories, federal and international agencies to:

• Overcome technical barriers through research and development of hydrogen production, delivery, and storage technologies, as well as fuel cell technologies for transportation, distributed stationary power, and portable power applications
• Address safety concerns and develop model codes and standards
• Validate and demonstrate hydrogen and fuel cell technologies in real-world conditions
• Educate key stakeholders whose acceptance of these technologies will determine their success in the marketplace.

The publications supported by these records can also be found on the website.

The database of European energy storage technologies and facilities includes: energy storage technologies and their characteristics; front of the meter energy storage facilities in the EU-28, operational or in project, that are connected to the generation and the transmission grid; behind the meter energy storage installed capacity per country. Database and report available.

We set out to study how the promise of green 5G is produced and circulated. We conducted an analysis of a UK-focused corpus of documents that represent key sites through which the promise of green 5G is produced, circulated and challenged. By the promise of green 5G we refer to an emerging, overarching, dominant expectation that 5G will produce positive environmental sustainability benefits of various kinds. We employed an analytical approach informed by the sociology of expectations and the concept of technoscientific promises. We asked: what are the particular contents of this promise (i.e. the more specific promises and expectations it is built upon), how do enactors seek to boost its legitimacy and credibility, what activities are involved in its production and circulation and what are its present-day material effects, does the promise exclude or overlook alternative options, and is it challenged? We pursued these aims and questions through a document analysis of a diverse corpus (n=260) comprised of UK newspaper articles and newswire results, and reports and webpage content from industry, standardisation bodies and research consortia.

Since 2011, Eoltech has published its wind energy index on 3 major regions of wind power development in France. Today, this indicator of regional wind resource is updated each month on 7 major regions, to allow operators and financial partners of projects to put their park production into the general perspective of the available wind resource. There is also a cumulative report updated monthly, from 2005 to present.

The data is from tests performed at The University of Sheffield, on a 1MWh/2MW lithium-titanate battery energy storage (BESS) by Toshiba SCiB Technology, within the EPSRC funded Multi-scale ANalysis for Facilities for Energy STorage (Manifest) Project EP/N032888/1. The system is connected directly to the grid through an 11kV feed, located at Willenhall Primary Substation. Interfacing to grid is achieved through a 2.2MVA ABB PCS100 inverter, and a 2.1MVA dry-type transformer with 1:30.55 ratio. The main parameters are related to time-series of grid voltage and frequency, AC and DC voltages and currents, operating conditions (such as for example room temperature), etc.

The experimental background is explained in Experiment_Description_Readme.pdf

The data are time-stamped in the format MM/DD/YYYY HH:MM:SS UTC, while the parameters are given using the International System of Units.
This catalogue entry was updated on 2021-02-03 to link directly to the data from the calibration test carried out on 2017-03-01. Previously it linked to the top level of the Sheffield BESS test data at https://data.ukedc.rl.ac.uk/browse/edc/power/storage/MANIFEST/Sheffield. The title was updated to include the words "Calibration Test" to differentiate it from other tests carried out with the Sheffield BESS facility. The previous title was "EPSRC ManIfest Battery Energy Storage System (BESS) The University of Sheffield". No changes have been made to the dataset and no other changes have been made to this catalogue record.

The data was collected during instantaneous power loss and efficiency tests performed at The University of Manchester in 2018 and 2020 , on a 240kVA and 180kWh Siemens SieStorage lithium-ion battery energy storage system (BESS). The system is connected behind the meter to the low-voltage distribution network via a 260kVA, 400/433V TMC isolation transformer. This data was collected as part of an experiment within the MANIFEST project.
The EPSRC-funded Multi-scale ANalysis for Facilities for Energy Storage (MANIFEST) Project (EP/N032888/1) aimed to study and investigate the capabilities of energy storage facilities installed in UK Universities.
There are 47 data files in this dataset.

The data is from efficiency tests performed at The University of Sheffield, on a 1MWh/2MW lithium-titanate battery energy storage (BESS) by Toshiba SCiB Technology, within the EPSRC funded Multi-scale ANalysis for Facilities for Energy STorage (Manifest) Project EP/N032888/1. The system is connected directly to the grid through an 11kV feed, located at Willenhall Primary Substation. Interfacing to grid is achieved through a 2.2MVA ABB PCS100 inverter, and a 2.1MVA dry-type transformer with 1:30.55 ratio. This data was collected as part of an experiment within the MANIFEST project to study the efficiency of the Willenhall Energy Storage System, managed by The University of Sheffield.The EPSRC funded Multi-scale ANalysis for Facilities for Energy STorage (Manifest) Project (EP/N032888/1) aimed to study and investigate the capabilities of energy storage systems installed in UK Universities.The data presented here has contributed to the following publications:'Experimental Analysis of Efficiencies of a Large Scale Energy Storage System', S. Mori, M. J. Smith, D. T. Gladwin & D. A. Stone, 'Practical state estimation using Kalman filter methods for large-scale battery systems', Z. Wang, D. T. Gladwin, M. J. Smith, S. Haass (Under review)

The data is from tests performed at The University of Manchester on a commercial 240 kW 180 kWh lithium-ion battery electrical energy storage system (BESS) within the EPSRC funded Multi-scale ANalysis for Facilities for Energy STorage (Manifest) Project (EP/N032888/1). The system is connected to the LV network (400 V) and is located on campus within a mixed-use (offices, lecture theatres, and laboratories) university building (so behind the meter). The tests carried out in March 2017 are described in the PDF Experiment_Description_Readme.pdf

The experiments were conducted using an Energy Storage System (ESS) in the Smart Grid laboratory at Newcastle University that includes transformers and converters interfacing to the grid, and various energy storage assets. The aim was to demonstrate the control of power flows between the grid and a 90kW / 2kWh supercapacitor bank. Tests were performed to control real power steps (short duration / high power, and long duration / low power) and reactive power steps of the grid-coupled converter. The corresponding power time-series at the supercapacitor bank terminals and the State of Charge (SoC) were recorded and plotted in the accompanying report.

The data were collected as part of an experiment within the MANIFEST project to demonstrate control operations of an ESS using the Smart Grid Laboratory at Newcastle University, UK.

The EPSRC funded Multi-scale ANalysis for Facilities for Energy STorage (Manifest) Project (EP/N032888/1) aimed to study and investigate the capabilities of energy storage systems installed in UK Universities.

In this experiment the efficiency of an emulated Energy Storage System (ESS) is measured in the Smart Grid laboratory at Newcastle University. Real-time simulation is carried out using a TRIPHASE real-time simulator to model the ESS network, allowing the laboratory hardware to operate as though it is coupled to a real distribution-scale network. The ESS emulator was used to represent the characteristics of three Li-ion battery banks with nominal voltage, power and energy ratings as follows: (i) 200V 1kW 1kWh, (ii) 400V 5kW 5kWh, and (iii) 400V 10kW 10kWh.

The data were collected as part of an experiment within the MANIFEST project to study the efficiency of an emulated supercapacitor using the Smart Grid Laboratory at Newcastle University, UK.

The EPSRC funded Multi-scale ANalysis for Facilities for Energy STorage (Manifest) Project (EP/N032888/1) aimed to study and investigate the capabilities of energy storage systems installed in UK Universities.

In this experiment the response time of an Energy Storage System (ESS) was measured in the Smart Grid laboratory at Newcastle University. Real-time simulation was carried out using a TRIPHASE real-time simulator to model the ESS network, allowing the laboratory hardware to operate as though it is coupled to a real distribution-scale network. The ESS emulator was used to represent the characteristics of a Li-Ion battery with a single string of 50 series cells, each with a nominal voltage of 4 V and a capacity of 200 Ah; these parameters were selected in order to set the nominal voltage, power and energy ratings of the ESS to 200 V, 20 kW and 40 kWh respectively.

The data were collected as part of an experiment within the MANIFEST project to study the response time of an ESS using the Smart Grid Laboratory at Newcastle University, UK.

The EPSRC funded Multi-scale ANalysis for Facilities for Energy STorage (Manifest) Project (EP/N032888/1) aimed to study and investigate the capabilities of energy storage systems installed in UK Universities.

The experiments were conducted using an Energy Storage System (ESS) in the Smart Grid laboratory at Newcastle University, that includes transformers and converters interfacing to the grid, and various energy storage assets. They tested the efficiency of the system components, including the supercapacitor bank and associated power converters. Tests were performed to control the supercapacitor power steps, while measuring power at the terminals of each system component. Efficiencies of the system components for various initial values of supercapacitor state of charge (SoC) are presented in the data files and accompanying report.

The data were collected as part of an experiment within the MANIFEST project to demonstrate the efficiency of the supercapacitor energy storage system and associated power converters in the Smart Grid Laboratory at Newcastle University, UK.

The EPSRC funded Multi-scale ANalysis for Facilities for Energy STorage (Manifest) Project (EP/N032888/1) aimed to study and investigate the capabilities of energy storage systems installed in UK Universities.

The Ecosystem Land Use Modelling and Soil Carbon Flux Trial (ELUM) measured greenhouse gas and soil carbon changes arising as a result of direct land-use change to bioenergy crops.

Ecosystem Land Use Modelling and Soil Carbon Flux Trial (ELUM) was funded and commissioned by the Energy Technologies Institute (the ETI) and carried out by the Centre for Ecology and Hydrology (CEH), the University of Aberdeen, the University of Southampton, Forest Research, Aberystwyth University, the University of Edinburgh and the University of York.

The ELUM project aims were to provide greater understanding on the greenhouse gas (GHG) and soil carbon changes arising as a result of direct land-use change (dLUC) to bioenergy crops, with a primary focus on the second-generation bioenergy crops Miscanthus, short rotation coppice (SRC) willow and short rotation forestry (SRF).

Experimental fieldwork on Miscanthus, SRC Willow, and SRF, and adjacent control sites, was conducted at locations across the length and breadth of mainland UK to capture data across both temporal and spatial scales.

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.

Elexon data from the Balancing and Settlement Code (BCS) systems that are available include: Balancing Mechanism Reporting Service (BMRS) data; the Elexon Portal and operational reports. If you're a company who isnt a BSC Party but would like to receive specific BSC data, there are contact details to request standard packages of reports that are available to non-Parties on request, subject to set licensing arrangements and fees.

Central Data Collection Agent (CDCA) data : Inter Grid Supply Point Group Connection Period Data (IPD); Grid Supply Point Period Data (GP9); Aggregated Grid Supply Point Group Take Volumes (AGV); Balancing Mechanism Unit Aggregation Report (ABV). Settlement Administration Agent (SAA) data: Aggregate Party Day Charges (APC); Market Index Day Period Information (MD1); Settlement Period Information (SPI); Settlement Period Information (SSD); Trading Unit Period Information (TRA). Data descriptions are also available on this web page.

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.

Inventory of Carbon & Energy (ICE) database of embodied carbon data in main construction materials. The data download is a zip of 3 excel files. The data files include Terms of Use and method and update notes.

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.

Cost and performance metrics for individual energy storage technologies which track: cost to procure, install, and connect an energy storage system; associated operational and maintenance costs; and end-of life costs. Technologies are: lithium-ion (lithium iron phosphate and nickel manganese cobalt chemistries); vanadium redox flow; lead acid; pumped storage hydropower; compressed air energy storage; and hydrogen. 2020 data and 2030 estimates of costs and performance are available.

A list of UK energy infrastructure development applications currently under consideration, it is regularly updated. This document lists current applications under consideration. It includes:

• recommendations from the Planning Inspectorate to the Secretary of State at the Department for Business, Energy and Industrial Strategy for decisions on energy infrastructure applications under the Planning Act 2008
• applications for changes to Development Consent Orders
• applications under section 36 under the Electricity Act 1989
• applications for variations to existing S36 consents
• applications for Compulsory Purchase Orders under the Electricity Act 1989 and Acquisition of Land Act 1981
• requests to the Secretary of State for Direction under section 35 of Planning Act 2008
• applications under the Transport and Works Act 1992

The UK's energy use by industry (SIC 2007 group - around 130 categories), source (for example, industrial and domestic combustion, aircraft, road transport and so on - around 80 categories) and fuel (for example, anthracite, peat, natural gas and so on - around 20 categories). These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The relationship between the UK Environmental Accounts and the Digest of UK Energy Statistics (DUKES) These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The UKs reallocated energy use and energy intensity - the level of usage per unit of economic output, by industry (SIC 2007 group - around 130 categories). Reallocated energy consumption is where losses incurred during transformation and distribution are allocated to the final consumer of the energy rather than the electricity generation industry. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The UK's fuel use by type (coal, natural gas, petrol, diesel oil for road vehicles (DERV), fuel oil, gas oil, aviation fuel and other). This table excludes biofuels and waste. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The UKs fuel use by industry (SIC 2007 group - around 130 categories) and type (coal, natural gas, petrol, diesel oil for road vehicles (DERV), fuel oil, gas oil, aviation fuel and other); UK level fuel use of nuclear, hydro, wind, solar, geothermal aquifers and net imports. This table excludes biofuels and waste. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The English Housing Survey (EHS) began in 2008 as a continuous national survey collecting information about peoples housing circumstances and the condition and energy efficiency of housing in England. The EHS brought together two previous survey series - the English House Condition Survey (EHCS) and the Survey of English Housing (SEH) - into a single fieldwork operation. The EHS covers all housing tenures and provides valuable information and evidence to inform the development and monitoring of government housing policies. The survey has a complex multi-stage methodology consisting of 3 main elements: an initial interview survey of around 17,000 households with a follow-up physical inspection and a desk-based market valuation of a sub-sample of 8,000 of these dwellings, including vacant dwellings. The interview survey sample forms part of the Integrated Household Survey (IHS), and the core questions from the IHS form part of the EHS questionnaire.

The Environmental Taxes Bulletin National Statistics presents statistics on Climate Change Levy (CCL) and Carbon Price Floor (CPF) (which are grouped under total CCL and CPF receipts), Aggregates Levy (AGL), and Landfill Tax (LFT) administered by HM Revenue and Customs (HMRC). The bulletin contains statistics on receipts up to the latest full month before its release, and statistics relating to declarations that are one month behind that of receipts.
The Environmental Taxes Bulletin is updated annually. It includes statistics on receipts up to the latest full month before its release, and statistics relating to clearances that are one month behind that of receipts.

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.

The data were gathered through a survey undertaken as part of the Financing Community Energy research project with the aim of improving understanding of the business models and financial characteristics of community energy projects in the UK. Data from individual projects have been aggregated into multi-project records in accordance with confidentiality undertakings made to survey participants. The survey formed part of the Financing Community Energy research project, itself part of the UK Energy Research Centre research programme. An analysis of the data has been published in Nature Energy (February 2020) https://doi.org/10.1038/s41560-019-0546-4.
This project was led by Professor Carly McLachlan of the Tyndall Centre for Climate Change Research, University of Manchester, and funded as part of the UKERC research programme. It involved researchers from the University of Manchester, University of Strathclyde, and Imperial College. The researchers involved with the survey were Carly McLachlan, Sarah Mander, Maria Sharmina, Ed Manderson and Tim Braunholtz-Speight (University of Manchester); Matthew Hannon (University of Strathclyde); and Jeff Hardy (Imperial College). Christina Birch and Christopher Walsh (University of Manchester) also provided some research assistance to the survey. Some data from Community Energy Englands (CEE) 2017 State of the Sector survey was also used, by agreement with CEE.
The survey covered characteristics of community energy organisations, and of the projects they run. With regard to organisations, it included legal structure, annual turnover, numbers of paid staff and volunteers, and numbers of members. In relation to each project, topics included: energy activities (including electricity or heat generation, and energy efficiency); ownership (sole or partnership type); financing (details of each instrument type, value, terms etc.); resources employed (including sites, technical, financial and legal services, general administration); costs (operating and financing); revenues (values and sources); value propositions (a range of economic, social and environmental propositions); customers (types, rates paid, etc.); and other beneficiaries.

The Fuel Cell Hydrogen Observatory (FCHO) provides data (statistics, facts and analysis) and up to date information about the entire hydrogen sector. The FCHO focuses on technology and market statistics, socio-economic indicators, policy and regulation, and financial support. Funded by the FCH JU, the observatory is created for the use of policy makers, industry stakeholders and the general public.

Estimates of gas consumption at regional (NUTS1) and local authority levels (NUTS4) using base data at meter point level from the re-structured gas distribution network. Data before 2005 was collected by the National Grid This data is held in the National Archive.

Global spatial data on solar resource and photovoltaic power potential over land. Methology and data source information available.

Spatial wind speed data and wind farm siting parameters. Wind speed measurements from satellite data (SAR and scatterometer) and from re-analysis data (MERRA). Spatial data

Annual total installed capacity of wind energy (MW) from 1990 to end of 2009 compiled from 5 separate (but not necessarily independent) sources. Sourced from : European Wind Energy Association 2002; Global Wind Energy Council 2005; BP Statistical Review of World Energy 2006/2007; Windpower Monthly, April 2008; GWEC - Global Wind 2009; Global Wind Energy Council, March 2010
Version containing records up to 2009 GlobalWindCapacity.csv
Previous version (up to 2007) GlobalWindCapacity_v2008.csv

Global, open-access, harmonised spatial datasets of wind and solar installations from OpenStreetMap data. Also included: user friendly code to enable users to easily create newer versions of the dataset; first order estimates of power capacities of installations. Data article, data, meta data and code available.

The ETI commissioned the HEMS & ICT Market project to undertake an in depth study and assessment of HEMS along with data, processes and controls and potential additional services enabled via a linked ICT system. The project delivers key insights and findings in terms of potential future offerings and capabilities of these products along with market assessment information. The aim of the project was to characterise the existing market for HEMS and ICT systems and to quantify the market/commercial opportunities for future HEMS and ICT propositions for both consumer and business. Our main report identified an opportunity for the ETI to lead the Advanced ESCo scenario through 3 key business propositions:

• ESCOs 'right-size' heating solutions then provide supply contracts with price guarantees
• HEMS enable optimised ToU tariffs and DR benefits via localstorage
• Hybrid heat pump driving arbitrage opportunities in the home

The HEMS ICT Market Forecast Tool is an excel work book that provides the user with a UK market forecast for Home Energy Management Systems and related ICT hardware. Users are able to vary various control parameters and create market forecasts to meet individual needs. This model is not intended as a final answer but rather provides a flexible forecast tool to inform a forward view of households that could potentially take up any of the 3 Advanced ESCo HEMS propositions set out in the main report. The report was initially published in November 2014. Some details and analysis may be out of date with current thinking.

HyMARC assembles expertise in hydrogen science, large-scale computational modeling, and state-of-the-art characterization tools to accelerate discovery of solid-state materials for on-board vehicular hydrogen storage. Some data and tools are shared here. Focus on solid state hydrogen storage materials.

Various scenarios for the UK's power fleet composition in 2030 and 2040 were developed. Dispatch modelling in Plexos was carried out by Baringa on these fleets to investigate the role gas fed plants might have in future. This includes the ability to study load factors, stop/starts etc, and together with concomitant pricing, provide a picture of investment remuneration. The effect of key drivers is studied e.g. gas price. This spreadsheet provides the modelling results for 2030 for Scenarios 3 and 4.

Various scenarios for the UK's power fleet composition in 2030 and 2040 were developed. Dispatch modelling in Plexos was carried out by Baringa on these fleets to investigate the role gas fed plants might have in future. This includes the ability to study load factors, stop/starts etc, and together with concomitant pricing, provide a picture of investment remuneration. The effect of key drivers is studied e.g. gas price.

Various scenarios for the UK's power fleet composition in 2030 and 2040 were developed. Dispatch modelling in Plexos was carried out by Baringa on these fleets to investigate the role gas fed plants might have in future. This includes the ability to study load factors, stop/starts etc, and together with concomitant pricing, provide a picture of investment remuneration. The effect of key drivers is studied e.g. gas price. This spreadsheet contains baseline, and scenario 1,2 and 3 results for aeverage power generation mix, winter mix amd modelled generation duration.

Various scenarios for the UK's power fleet composition in 2030 and 2040 were developed. Dispatch modelling in Plexos was carried out by Baringa on these fleets to investigate the role gas fed plants might have in future. This includes the ability to study load factors, stop/starts etc, and together with concomitant pricing, provide a picture of investment remuneration. The effect of key drivers is studied e.g. gas price. The purpose of this spreadsheet is to provide:

1. The pathway results (capacity, generation ,costs) for all scenarios. The pathway results are the output of the capacity optimisation model (LT: Long-Term)
2. Levelised cost of electricity and value of capacity for the Base Case (Model LT: Long-Term)
3. Detailed dispatch results for the Base Case for a spot year (2030). The dispatch results have been simulated with the full year dispatch model (ST: Short-Term)
4. Dispatch results for two spot years (2030, 2050) for the rest of the scenarios. These results were simulated with the capacity optimisation model (LT)
5. Comparisons between the Base Case and sensitivities
6. Comparisons between Base Case and other GB scenarios

Various scenarios for the UK's power fleet composition in 2030 and 2040 were developed. Dispatch modelling in Plexos was carried out by Baringa on these fleets to investigate the role gas fed plants might have in future. This includes the ability to study load factors, stop/starts etc., and together with concomitant pricing, provide a picture of investment remuneration. The effect of key drivers is studied e.g. gas price. This spreadsheet contains the data supporting the report "Hydrogen Turbines Follow On - Scenario 5 Results Pack - Power sector CCS and H2 Turbine Asset Modelling"

The International Energy Agencys Demonstration Projects Database seeks to map major demonstration projects of clean energy technologies, globally. For each project, it provides information on location, sector and technology grouping, status, capacity, timing and funding, when available.

Database of baseline energy use and emissions for key process industries (iron & steel; chemicals; food & drink manufacture; paper; cement) in the UK industrial sector and opportunities for reducing these (improvement potentials). Total sectoral energy flows (PJ) and emissions (MtCO₂e) and sectoral energy flows (PJ/t) and emissions (kgCO₂e/t) per unit output.
Industrial sectors: Iron & steel; Chemicals; Food & drink manufacture; Paper; Cement The usable energy database (UED) contains baseline energy use and emissions, and opportunities for reducing these (improvement potentials). The project report should be read alongside the UED. The work is currently presented as a Beta version to allow feedback from project partners and other interested parties to be incorporated in a final version. The UED was produced to improve the representation of the UK industrial sector within the whole systems TIMES model developed by the UK Energy Research Centre (UKERC). Due to the substantial variability in energy use within the industrial sector the approach was to undertake bottom-up studies of subsectors of industry that were important from an energy use and emissions perspective, and to supplement this with information on cross-cutting technologies that could be applied throughout industry. Baseline data variously sourced from: International Steel Statistics Bureau (ISSB); the Confederation of Paper Industries; Mineral Products Association; and others (for a full list of source references see the project report.)
Please acknowledge the UKERC Energy Demand theme when making use of this data
The data is presented as .xls and .xlsx
The final project report is UED_Documentation.pdf

Photovoltaic Geographical Information System (PVGIS) provides a map-based inventory of solar energy resource and assessment of the electricity generation from photovoltaic systems in Europe, Africa, and South-West Asia. It is a part of the SOLAREC action that contributes to the implementation of renewable energy in the European Union as a sustainable and long-term energy supply Aggregated data of solar and PV potential for European countries and regions is available. Monthly/daily irradiance data via clickable maps. Location can also be specified using latitude and longitude. Output as graphs, webpage, text file or PDF.

Levelised unit cost data (£/MWh 2006) for electricity generation from various primary energy sources in various countries. Unit cost“relevance” rating. Plant types comprise: Coal, Nuclear, Gas, Wind, Coal (other), CHP, PV, Gas (other), Biomass & Energy Crops, Hydro, Waste, Wind (offshore), Geothermal, Solar Thermal, Wave & Tidal Stream, Fossil Fuel (other), Fuel cell, Nuclear (other). The database is in Heptonstall2007_LevelisedElectricityCostData.xls
Contains information for Australia, Austria, Belgium, Brazil, Canada, China, Czech Republic, Denmark, Finland, France, Germany, Greece, India, Indonesia, Italy, Japan, Mexico, Netherlands, New Zealand, Portugal, Spain, Romania, Slovakia, South Africa, South Korea, Sweden, Switzerland, Turkey, UK, USA
A full list of references with links to original documents is provided in "A Review of Electricity Unit Cost Estimates" (PDF 300 KB)

The Local Engagement in UK Energy Systems (LEUKES) Database is about local authority energy projects. The data being made available is a database of 458 UK local authority energy projects collated from 29 different data sources. The energy projects database was produced as part of the Local Engagement in UK Energy Systems (LEUKES) project. The database is developed from datasets published by the European Commission, UK and devolved Governments, and their agencies which included information on grants and loans which LAs use for financing energy initiatives and information on operational energy projects.
The research aimed to examine the current and future contribution of local governments to changing energy production, supply and use with a primary focus on providing knowledge about the extent of local engagement in energy initiatives under current institutional structures; and, identifying local energy governance and business models being developed. This data formed one component of research in the LEUKES project and was funded by the Research Councils UK Energy Programme as part of the UK Energy Research Centre (UKERC) research programme and the Energy Technologies Institute (the ETI) and was carried out by the University of Edinburgh. https://heatandthecity.org.uk/project/local-engagement-with-uk-energy-systems/

The LCCC manages Contracts for Difference (CfD) and the Supplier Obligation Levy that supports low carbon electricity generation in the UK. The portal provides access to CfD, levy and capacity market data. The published datasets can be downloaded as CSV and JSON formats. The data portal also provides an API, allowing the data to be read programmatically. Users can follow a particular dataset, or a particular data publisher on the portal, so that when a particular dataset gets updated, the users will receive email notifications.

MEDIN is public-private alliance to provide a marine environmental data centre. Dataset metadata can be searched by keyword or interactive map using the data discovery portal, providing a federated search across other data repositories. Searches can also be done by themes via the reference layers. Data can also be lodged in MEDIN with standardised metadata Some datasets may have restrictions on access and use.

The Marine Data Exchange provides access to survey data and reports collated during the planning, building and operating of offshore renewable energy projects. There are two divisions: Wind and Aggregates. Wind consists of raw, cleaned and modelled wind datasets from various meteorological masts, LiDAR systems and meteorological buoys around the UK. Aggregates includes Marine ALSF Regional Environmental Characterisation Surveys (RECs). Can be searched by data type, industry, round, date range, topics and a selection of predefined keywords, interactive map and then further refined by keyword. Includes COWRIE (Collaborative Offshore Wind Research into the Environment). Registration is not required, but gives access to additional resources, including posting notices of datasets wanted.Definitions are at http://www.marinedataexchange.co.uk/data-requirements.aspxWhen downloading data, it looks as though you are buying it because your choice goes into your basket, but in fact there is no charge. You enter your email address and a link to download the data is mailed to you within the next five days; there may also be a short usage feedback survey.

Estimates of the value of marine natural capital to people in the UK. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

Hourly energy consumption data gathered from 94 (originally 160) low energy homes in Milton Keynes Energy Park (1989-1991). These homes were of conventional design for the UK (35 different designs) but included energy efficiency features (primarily increased insulation in the roof, wall, and flooring and energy efficient boilers) so that they correspond with SAP values of 75-90. The results were used to generate a database of energy consumption data to assist in development of the Building Research Establishment Domestic Energy Model (BREDEM). The ReadMe_MiltonKeynes.html file contains more detailed information about the datasets. Registration with EDC is required for access to the data.
This data was originally collected by the Building Research Establishment (BRE) during a project in 1988-91 in an area then known as Milton Keynes Energy Park, located some 75 km north-west of London. The study monitored more than 100 sites for hourly electricity and gas consumption; the dwellings essentially follow conventional UK housing design, but were built in 1987 to higher standards for energy performance than were required by the building regulations at that time (Edwards, 1990). They incorporated energy efficiency features, such as increased floor, wall, and loft insulation, double-glazing, and in some cases condensing boilers, so that they broadly corresponded to UK building standards of almost a decade later.
The data has been rescued off the original 5.25 inch floppy disks by Steve Pretlove of UCL towards his PhD thesis and has since been cleaned and further processed by Alex Summerfield. Data were successfully retrieved for 94 sites with more than 200 days of valid date each. Some building data, including floor areas and U-values were recovered, unfortunately related social data, such as the number of occupants in each household, were not available.
Reference: J. Edwards (1990), Low energy dwellings in the Milton Keynes Energy Park, Energy Management v26 p32-33.
See also: numerous internal Buildings Research Establishment (BRE) reports.
Note that there are some missing data points largely due to problems of recovery from the original media (the data from July 1989 are missing from many data sets) but nonetheless there are many sites with > 12 months of data.

The IAEA's NUCLEUS information resource portal provides access to over 100 scientific, technical and regulatory resources, including databases, applications, publications and training material. As it is mainly meant for IAEA counterparts in the government, industry and scientific community, NUCLEUS hosts a number of resources that require registration. Many sites, however, can be accessed without a password. Terms of use are available: <a href="https://www.iaea.org/topics/temporary/nucleus-terms-of-use">https://www.iaea.org/topics/temporary/nucleus-terms-of-use</a>

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.

National Grid gas transmission data for Great Britain. A wide range of data available on balancing, calorific value, demand, flows, linepack, LNG, price, storage, supplies and trading. An API is available for data access.

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

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.

Reports outlining average summer day and night noise exposure contours for Heathrow, Gatwick and Stansted airports. Environmental Research and Consultancy Department (ERCD) have produced annual reports on noise exposure contours at Heathrow, Gatwick and Stansted airports. Contours from 2016 onwards are commissioned and published by the designated airports.

The North Sea Transistion Authoritys open data portal. Holding spatial data on offshore, UK oil and gas facilities, licences and production and on gas and carbon capture and storage licences.
It was previously called the Oil and Gas Authority

Quarterly bulletin and annual compendium of housing statistics and the ongoing review of data including housing publications and the changes proposed. Various reports and bulletins issued regularly, with recent years available and information about requesting earlier data.

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.

GIS map of all known wave and tidal energy installations in the world. Annual detailed reports per country are also available for the 29 member countries. The Ocean Energy Systems Implementing Agreement (OES) is an intergovernmental collaboration between countries, operating under the framework of the International Energy Agency (IEA). PDF Annual reports for previous years along with the global report are available in the Library section of the site.

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.

Estimates of the UK's remaining recoverable oil and gas reserves and resources. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

A free and open data platform for energy system modelling. OPSD collect, check, process, document, and publish data that are publicly available but currently inconvenient to use. Open access where possible but some data published here might be subject to copyright. Check specific terms by data set.
For further information see "Open Power System Data Frictionless data for electricity system modelling" in Applied Energy. https://doi.org/10.1016/j.apenergy.2018.11.097

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.

Public opposition to new energy technology can harm the chances of successful deployment. Less is known about knock-on effects on the wider energy system, including whether such opposition impacts public perceptions of other technologies. Here we present a mixed-methods study into perception spillover, examining whether the controversy over fracking for oil and gas affects public attitudes to two novel low-carbon energy technologies: deep enhanced geothermal systems, and green hydrogen. We argue that perception spillover is multi-faceted, and we conceptualise and test spontaneous, prompted and primed forms, examining how and why particular types occur. Using a nationally-representative UK survey and two focus groups, we show that perception spillover from fracking could lead to widespread negative perceptions of deep geothermal energy, influencing the conditions which deep geothermal would be expected to meet. Conversely, a minority of participants expressed more positive perceptions of green hydrogen because they deemed it dissimilar to fracking.Flexible fund project under the UK Unconventional Hydrocarbons project. Aims to understand the impact of fracking on public perceptions of other energy technologies This is a linked dataset held in the UKDS

Phyllis is a database containing information on the composition of biomass and waste. From Phyllis you can obtain analysis data of individual biomass or waste materials or average values for a group of materials. Groups can be selected from one of three classification schemes: the ECN Phyllis scheme, the NTA 8003 scheme (only in Dutch), and the European standard CEN/TS 14961. The latter scheme is used for the BIODAT database, which has been made an integral part of Phyllis. The BIODAT database was developed in co-operation with European partners within the PHYDADES project. BIODAT is restricted to data from standard analysis methods. In 2012, BIODAT became a subset of Phyllis and the Phyllis website was adapted accordingly. In the future, the BIODAT subset will be the main growth area of the Phyllis database.

POD (Platform for Operational Data) from ORE (Offshore Renewable Energy) Catapult allows requests for data sets arising from ORE Catapult and partners' innovation projects and operational assets. Includes demonstration turbine data, system performance analysis and floating turbine design cases. Samples of each data collection are available to view. There is a small charge to cover the data retrieval, depending on the size or complexity of the request, and this will be calculated after the request has been made.

The Power Reactor Information System (PRIS), developed and maintained by the IAEA for over five decades, is a comprehensive database focusing on nuclear power plants worldwide. PRIS contains information on power reactors in operation, under construction, or those being decommissioned. PRIS is available to both the general public and registered users, with registered users able to input their own data and access a statistics reporting tool. There is more information at https://pris.iaea.org/pris/About.aspx.

Energy systems are changing rapidly, bringing new types of risks, and new forms of potential disruption to energy supplies. Our growing dependence on energy, particularly electricity, means that more than ever we need to plan for disruptions and be prepared for them. What happens during the disruption is important: we need to understand how individuals, communities and organisations experience the event, and what measures can be taken to reduce the overall impacts. This study investigates how people and communities in the city of Glasgow (Scotland) might be expected to respond to a lengthy, widespread disruption to energy supplies. A novel three-stage diary-interview methodology was used to explore energy practices and expectations dependency, and to understand the ways in which peoples experience of disruptions may change in the coming decade. The results show that the most consistent determinant of participants perceived resilience, over and above socio-demographic factors, is their expectations and their degree of dependency on routine. In addition, the results suggest that common assumptions regarding peoples vulnerability may be misplaced, and are shifting rapidly as digital dependency grows, and are sometimes misplaced: in particular, determinants such as age and income should not be seen as straightforward proxies for vulnerability. A new set of indicators of vulnerability are identified. For longer outages, peoples ability to cope will likely decrease with duration in a non-linear step-change fashion, as interdependent infrastructures and services are affected. Community-level actions can improve resilience, and local scales may be more appropriate for identifying vulnerabilities than socio-demographic proxies, but this is only feasible if organisations and institutions are adequately resourced.Recent events have highlighted the potential impact of long, widespread energy supply interruptions, and the need for resilience is likely to create a requirement for greater flexibility from both the electricity and gas systems. This project will examine the engineering risks, and assess the need for new industry standards to drive appropriate action; and conduct a systematic assessment of the impacts of a serious energy disruption on consumers and critical services, such as heating, water, communications, health and transport. This dataset is held in the UKDS

Refining Estimates of Land for Biomass (RELB) was a project commissioned and funded by the ETI. As part of the RELB project, the ETI commissioned the project team to complete three case studies of farms growing bioenergy crops. This workbook consists of the data and calculations for the Abbey Farm Miscanthus case study and should be read alongside the other case studies and the rest of the RELB documentation.

Refining Estimates of Land for Biomass (RELB) was a project commissioned and funded by the ETI. As part of the RELB project, the ETI commissioned the project team to complete three case studies of farms growing bioenergy crops. This workbook consists of the data and calculations for the Friars Farm Miscanthus case study and should be read alongside the other case studies and the rest of the RELB documentation.

Refining Estimates of Land for Biomass (RELB) was a project commissioned and funded by the ETI. As part of the RELB project, the ETI commissioned the project team to complete three case studies of farms growing bioenergy crops. This workbook covers the data and calculations for the Brackenthwaite Farm SRC Willow case study

Refining Estimates of Land for Biomass (RELB) was a project commissioned and funded by the ETI. This workbook includes the data for the charts displayed in Appendix 1 of the report, Job implications of establishing a bioenergy market.

Refining Estimates of Land for Biomass (RELB) was a project commissioned and funded by the ETI. This workbook includes the data for the charts displayed in the main body of the report, Job implications of establishing a bioenergy market.

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.

UK Government has collected and compiled estimates of gas consumption at regional (NUTS1) and local authority levels (LAU1 - formally NUTS 4) using data at meter-point level from the re-structured gas distribution network. In March 2008, this gas consumption dataset gained National Statistics status. This status applies to all data from 2005 onwards. The 2004 data are still classed as experimental.

The Renewable Energy Planning Database (REPD) and the Heat Networks Planning Database are updated and published every quarter. The Renewable Energy Planning Database tracks the progress of renewable electricity and heat networks projects. The Heat Networks Planning Database covers district as well as communal heat network projects. The Renewable Energy Planning Database tracks the progress of renewable electricity and heat networks projects. It provides as accurate and comprehensive a snapshot as possible of projects in both areas, and of progress across the technology sectors.The Heat Networks Planning Database covers district as well as communal heat network projects.It aims to provide a more complete picture of heat network deployment across the UK.
The databases are: updated during the month following the end of each quarter; and are provided in 2 separate CSV files, and on separate worksheets within a single XLSX file.

Renewables.ninja allows users to run simulations of the hourly power output from wind and solar power plants located anywhere in the world. Data has been derived from NASAs MERRA-2 re-analysis data and CM-SAFs SARAH satellite data.
The usage rights for this data is governed by a Creative Commons Attribution-Non Commercial 4.0 International (CC BY-NC 4.0) licence.

Local authority level residual fuel (ie non-gas, non-electricity, non-road transport) consumption statistics. This includes: the full dataset and a factsheet summarising the key points of the dataset. This residual fuels dataset is also sometimes known as other fuels consumption data.

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.

Physical (non-monetary) and monetary estimates of services provided by natural assets in Scotland. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

Recent and historic solar photovoltaic generation estimates for Great Britain, updated every 30 minutes. Including embedded generation. Data are available as plots or tables and are also available via an API.

Survey of the tendency to regret purchases across 20 product groups. Conducted by YouGov for the wholeSEM project, 19th-20th March 2015. 2,036 responses to an online survey. Results have been weighted and are representative of GB adults. The results were analysed and findings are reported in Skelton & Allwood (2017) Questioning demand: a study of regretted purchases in the UK, Ecological Economics 131, p.499-509

Modelling of the costs, efficiencies and greenhouse gas emissions of biomass supply chains with and without significant pre-processing.

The TEAB project compares the costs, efficiencies and GHG emissions of biomass supply chains with and without significant pre-processing, to assess whether and how pre-processing steps can benefit UK bioenergy supply chains.

Ten supply chains were selected for modelling and analysis in the project, two of which generate heat, and eight generating power. These are compared in groups according to their shared conversion technology, and all the chains are able to use a blend of Miscanthus and woody feedstocks (from 0-100%).

Available here are gPROMS and Excel models describing bioenergy supply chains, and project reports. Further README files in the models and reports sub-directories describe the contents further.

Geographic data of the Crown Estate's offshore leasing to renewable energy and other users. Terms of use are available on the website. They do not include re-use.

The Wind Power is a set of databases covering wind farms, turbines, manufacturers, developers, operators and owners worldwide, with market information. Downloads are available for each database, plus photographs and maps, and analysis of the wind power market. There is an interactive map.

This spreadsheet provides the underlying breakdown of the capital cost estimate for the the Teeside location. Note that minor changes have been made to numbers in the spreadsheet to protect commercially sensitive cost data that was used in calculating the capital cost in the main report, amd hence the total numbers in the spreadsheet may differ slightly from those presented there.

This tool presents the costs to consumers of support to different electricity generation technologies. It is designed to help show the impact of different policy / market arrangements on the required support for different generation technologies. Users can also examine the effect of amending some inputs (although due to the interdependency of the system, sensitivities such as changing variable costs will require a re-run of the underlying dispatch/investment model.

This toolkit presents the whole-system impacts of electricity generation technologies. It is designed to help show the underlying assumptions driving differences in the whole system impact calculated from a dispatch and investment model. Users can examine the effect of amending some inputs on the whole system impact (although due to interdependency of the system, sensitivities such as changing variable costs will be a re-run of the underlying dispatch/investment model). The toolkit is set up to easily accept input from EnVision/DDM, but could (with appropriate transformation of outputs) be used with another dispatch and investment model.

This spreadsheet provides the underlying breakdown of the capital cost estimate for the NE England location. Note that minor changes have been made to numbers in the spreadsheet to protect commercially sensitive cost data that was used in calculating the operating cost in D5.1. Hence the total numbers in the spreadsheet may differ slightly from those presented in D5.1.

Data arising from multiple measurement campaigns comprising primarily velocimetry conducted at the European Marine Energy Centre (EMEC) Tidal Test Site during the ReDAPT Tidal Project. Data arising from multiple measurement campaigns comprising primarily velocimetry conducted at the European Marine Energy Centre (EMEC) Tidal Test Site during the ReDAPT Tidal Project. These campaigns consisted of both stand-alone seabed mounted Acoustic Doppler Profiling and Tidal Energy Converter (TEC) mounted Acoustic Doppler Profiling. Multiple instrument configurations were used across multiple seasons between June 2011 and October 2014. The data was used for resource characterisation and the validation of multiple numerical modelling techniques used in the Tidal Industry. Data is provided in MATLAB v7.3 .mat files and has also been converted to NETCDF. There is a project www at <a href="http://www.eti.co.uk/programmes/marine/redapt">http://www.eti.co.uk/programmes/marine/redapt</a>. Further information is also available at <a href="http://redapt.eng.ed.ac.uk/index.php">http://redapt.eng.ed.ac.uk/index.php</a>

Physical (non-monetary) and monetary estimates of tourism services provided by natural assets in the UK. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

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/

Model output from UK MARKAL Elastic Demand for all UKERC Energy 2050 project revised scenarios.
This consists of datasets as .xls files plus graphics summaries as PDFs Please acknowledge the UKERC Energy Systems Theme when making use of this data.
Reference this data source as: Keppo I Skea J. and Ekins P. 2013 UK Energy 2050 Revised Scenario Set Data UKERC Energy Data Centre http://ukedc.rl.ac.uk
The revisions are described in UKERC_Energy_2050_RevisedScenarios.pdf
There is further information at ReadMe_2050Scenarios.htmll
The .xls files are in the Data subdirectory

The UK government conversion factors for greenhouse gas reporting are for use by UK and international organisations to report on greenhouse gas emissions. Government produce a new set of conversion factors each year, together with a methodology paper explaining how the conversion factors are derived, and a paper explaining the major changes in the latest years factors.

Technology variants, capital & O&M costs, efficiency, plant life-time characteristics for electricity generating plant as input to the UKERC Markal Energy Model (2007) sub-divided as CHP, Renewables, Nuclear, CO2 Pipeline & Storage, Gas-fired Plant, Coal, Electricity data for MARKAL The MARKAL_Electricity_cost_data_version_EDC_2007.xls spreadsheet contains cost information in the electricity generation sector drawn from a variety of sources. These references are listed in the worksheet entitled Sources.
The workbook is divided into labelled worksheets, according to different generic types of generating technology: CHP, Renewables, Nuclear, CO₂ pipeline and storage, Gas-fired plant, Coal. Each worksheet contains the data as input to the MARKAL model, showing a range of aspects of different generation technologies. The full set of MARKAL data covering all technologies is included in worksheet 7, entitled 7 Electricity data for MARKAL.
In worksheets 1-6, beneath the MARKAL data, other data has been added from the sources reviewed to illustrate the range of data which the models assumptions could plausibly have covered. The data is provided in two forms. In the first worksheet for each technology, the data is included in the form in which it is presented in the original sources. Thus, the units and currencies are not always those of the MARKAL model. Notes have been inserted to indicate the currency or unit of measurement. The information has been provided in this way so as to maintain transparency. In the second worksheet for each technology (marked A - for Adjusted), the data has been adjusted to match the currencies and units used in MARKAL. The numbers which have been subject to adjustment have been highlighted in yellow. A separate sheet showing the conversion factors used has been included (Conversion).
The information from other sources covers only a subset of the information within MARKAL. The definitions of key terms (such as operational and maintenance cost), is rarely consistent from one source to the next. In two places therefore, new columns have been inserted to the original structure. Information on construction periods (in years) has been included adjacent to the existing column showing first year available. The lack of distinction in the sources between fixed and variable O&M costs has also resulted in the creation of a single O&M column so that information can still be included.
The workbook should be used in conjunction with the report: Derek Smith, Comparative Cost Information: Supporting the development of the MARKAL MACRO model of the UK Energy Research Centre (UKERC), November 2006 which summarises the cost comparisons. These summaries include additional information to provide the context from which the data in this workbook have been drawn.

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.

The UKs direct use of energy from fossil fuels and other sources (nuclear, net imports, renewables, biofuels and waste) and reallocated use of energy by industry. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The Wind Energy Database (UKWED) contains data about operational onshore and offshore wind projects of 100kW or more. Some data are available only to renewableUK members. The basic search is open access, but Project Status, Project Intelligence Hub and Wind Energy Map are available to renewableUK members only.

Estimates of the financial and societal value of natural resources to people in the UK These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

Ecosystem accounts for the mountains, moorlands and heath (MMH) environment in the UK. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

Natural capital accounts for peatlands measures the ecosystem services which peatlands provide, including water, carbon sequestration, food and recreation. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The UKEOF Catalogue provides access to information about environmental observations from the UKs monitoring programmes. It contains over 2000 metadata records of environmental observations undertaken and funded by public and third sector organisations. The UKEOF Catalogue contains metadata records of environmental observations undertaken and funded by public and third sector organisations, not the data observations themselves. <p> The oldest records related to the Bird ringing scheme</P>

Model output (from UK MARKAL Elastic Demand) for all UKERC Energy 2050 project scenarios. Please acknowledge the UKERC Energy Systems Theme when making use of this data.
Reference this data source as: Strachan N. Anandarajah G. Hughes N. and Ekins P. 2010 UKERC Energy 2050 energy systems scenario data UKERC Energy Data Centre http://ukedc.rl.ac.uk
More information is available in UKERC_Energy_2050_Scenario_Data.pdf and ReadMe_2050Scenarios.html

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

Data collected at the UKGEOS (UK Geoenergy Observatories) facilities including drilling data packs, ongoing monitoring data and experiment results. The data from UKGEOS will apply to geothermal energy, hydrogen, carbon capture and storage, and storage solutions for wind, solar and tidal energy can reduce our carbon emissions.

UNSD maintains the Energy Statistics Database, which provides annual statistics on production, trade, transformation and consumption (end-use) for solid, liquid, and gaseous fuels, electricity, and heat. It contains basic statistics for more than 230 countries/territories from 1950 year onwards and is updated annually. The database contains data in their original units (e.g. metric tonnes, GWh) as well as calorific values to allow interfuel comparison in a common energy unit (terajoules).

These files are the core subset of the updated and expanded versions of the data originally collated for the UKERC "Costs and Impacts of Intermittency - 2016 update" project, see https://ukerc.ac.uk/project/the-intermittency-report/. This dataset includes the references, costs and impacts from this systematic review of the evidence on the costs and impacts of intermittent electricity generation technologies. These files are the core subset of the updated and expanded versions of the data originally collated for the UKERC "Costs and Impacts of Intermittency - 2016 update" project, see https://ukerc.ac.uk/project/the-intermittency-report/.
The dataset was further updated and expanded for a 2020 paper in Nature Energy "A systematic review of the costs and impacts of integrating variable renewables into power grids" - https://doi.org/10.1038/s41560-020-00695-4

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.

Statistical information on all aspects of housing in Wales Data sets include housing energy performance statistics.

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.

Physical (non-monetary) and monetary estimates of services provided by woodland natural assets in the UK These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

This document is an MS Excel database of zero emission powertrain components and overall costs for EV and FCEV powertrains in heavy duty vehicles. The dataset includes:

• Indicative fuel cell light and heavy vehicle specifications for each of the truck and bus categories currently used by the ETI
• Fuel cell system component costs by year and global production volume
• Initial production cost, TCO and CO2 savings assessment
• Equivalent data for battery electric vehicles for comparison purposes