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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

Open geographic data for over 260,000 solar PV installations across the UK, covering an estimated 86% of the capacity in the country, arising from a major crowd-sourcing campaign. The data set focuses in particular on capturing small-scale domestic solar PV, which accounts for a significant fraction of generation but has been poorly documented. Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13050869

The Annual Gas and Electricity Consumption at Meter Level, Great Britain, 2004-2022: Secure Access study includes annual gas and electricity consumption data at an individual property level, covering England, Scotland and Wales from 2004 onwards. Both domestic and non-domestic properties are included.

The relationships between UK Environmental Accounts measures and those of United Nations Framework Convention on Climate Change (UNFCC) and United Nations Economic Commission for Europe (UNECE). These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

Greenhouse gas and carbon dioxide emissions intensity - the level of emissions per unit of economic output, by industry (SIC 2007 group - around 130 categories), UK. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The emissions of carbon dioxide, methane, nitrous oxide, hydro-fluorocarbons, perfluorocarbons, sulphur hexafluoride, nitrogen trifluoride and total greenhouse gas emissions, by industry (SIC 2007 group - around 130 categories), UK. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The emissions generated from fuel sources used by road transport vehicles in the UK. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The Australia Hydrogen Opportunities Tool (AusH2) provides free access to geoscience data and tools for mapping and understanding the potential for hydrogen production in Australia. GIS data and publications available

The Electrification of Heat (EoH) demonstration project is funded by the Department for Business, Energy and Industrial Strategy (BEIS) and seeks to better understand the feasibility of a large-scale roll-out of heat pumps in homes across the UK. It aims to demonstrate that heat pumps can be installed in a wide variety of homes and deliver high customer satisfaction across a range of customer groups.This dataset provides data collected by the Delivery Contractors during the participant recruitment, home survey, system design and installation phase of the project. It also contains a unique property ID number which can be used to link this data to future published project datasets. All users are directed to the "Heat Pump Installation Statistics", "Participant Recruitment Report", and "Home Surveys and Install Report" for more information and analysis relating to this data. Additional documentation is also provided as outlined below which indicates what the data is, how the data was collected, and how it may be used.
https://es.catapult.org.uk/project/electrification-of-heat-demonstration/

The BP Statistical Review of World Energy is published annually. The Statistical Review is one of the most widely respected publications in the field of energy economics and has been published since 1952.<p> From 2023 it has moved to be provided by the Energy Institute.</p> <a href="https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html ">Legacy link</a> <p> Resource includes outlook forecasts, an energy charting tool and app, country and regional insights, webcasts, on-demand video and downloadable content, a review of the previous year and for each energy area, a review of reserves, production, consumption, trade and prices.</p>

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 work benchmarks the existing UK cold chain and provides robust evidence-based data on emissions in 2020. Only emissions from refrigeration within UK borders was considered, both from refrigerant leakage and from electrical power usage. Energy consumption For energy consumption the Digest of UK Energy Statistics (DUKES) was widely used. This data is compiled by the Department for Business, Energy & Industrial Strategy (BEIS) and contains data for many years up until the current year. The United Kingdom Statistics Authority has designated these statistics as National Statistics, in accordance with the Statistics and Registration Service Act 2007 and therefore they were considered as the most accurate data available. DUKES data does not always differentiate the energy consumed by refrigeration systems in each of the cold chain sectors and therefore further analysis and assumptions were often required. Energy consumption values shown were collated per year for the years 2019/2020, unless otherwise stated. Emissions from refrigerant leakage The main GHG refrigerants are the fluorinated gases (f-gases); hydrofluorocarbons (HFCs) and hydrochlorofluorocarbons (HCFCs). According to Brown et al (Brown et al., 2021) emissions of f-gases can occur at various stages of the refrigeration equipment life-cycle: During manufacturing, During installation, Over the operational lifetime, At disposal. The most comprehensive source of information for direct emissions is the UK Greenhouse Gas Inventory. This contains national greenhouse gas emission estimates for the period 1990-2019 and is the United Kingdoms National Inventory Report (NIR) submitted to the United Nations Framework Convention on Climate Change (UNFCCC). It includes losses during manufacture/initial charging and at decommissioning as well as losses in use.

TESBiC: Techno-Economic Study of Biomass to power with CCS. This model was developed as part of Work Package 3. It examines changes in cost, efficiency and emissions under different operating conditions for biodedicated IGCC with CCS. It should be read in conjunction with the Work Package 3 reports on model specification and user documentation. The Biomass to Power with CCS Phase 1 project consisted of four work packages: WP1: Landscape review of current developments; WP2: High Level Engineering Study (down-selecting from 24 to 8 Biomass to Power with CCS technologies); WP3: Parameterised Sub-System Models development; and WP4: Technology benchmarking and recommendation report. Reports generally follow this coding. We would suggest that you do not read any of the earlier deliverables in isolation as some assumptions in the reports were shown to be invalid. We would recommendthat you read the project executive summaries as they provide a good summary of the overall conclusions. This work demonstrated the potential value of Biomass to Power with CCS technologies as a family, but it was clear at the time of the project, that the individual technologies were insufficiently mature to be able to 'pick a winner', due to the uncertainties around cost and performance associated with lower Technology Readiness Levels (TRLs).

TESBiC: Techno-Economic Study of Biomass to power with CCS. This model was developed as part of Work Package 3. It examines changes in cost, efficiency and emissions under different operating conditions for biomass to power with amine-based carbon capture. It should be read in conjunction with the Work Package 3 reports on model specification and user documentation. The Biomass to Power with CCS Phase 1 project consisted of four work packages: WP1: Landscape review of current developments; WP2: High Level Engineering Study (down-selecting from 24 to 8 Biomass to Power with CCS technologies); WP3: Parameterised Sub-System Models development; and WP4: Technology benchmarking and recommendation report. Reports generally follow this coding. We would suggest that you do not read any of the earlier deliverables in isolation as some assumptions in the reports were shown to be invalid. We would recommend that you read the project executive summaries as they provide a good summary of the overall conclusions. This work demonstrated the potential value of Biomass to Power with CCS technologies as a family, but it was clear at the time of the project, that the individual technologies were insufficiently mature to be able to 'pick a winner', due to the uncertainties around cost and performance associated with lower Technology Readiness Levels (TRLs).

TESBiC: Techno-Economic Study of Biomass to power with CCS. This model was developed as part of Work Package 3. It examines changes in cost, efficiency and emissions under different operating conditions for biomass to power with chemical looping CCS. It should be read in conjunction with the Work Package 3 reports on model specification and user documentation. The Biomass to Power with CCS Phase 1 project consisted of four work packages: WP1: Landscape review of current developments; WP2: High Level Engineering Study (down-selecting from 24 to 8 Biomass to Power with CCS technologies); WP3: Parameterised Sub-System Models development; and WP4: Technology benchmarking and recommendation report. Reports generally follow this coding. We would suggest that you do not read any of the earlier deliverables in isolation as some assumptions in the reports were shown to be invalid. Wewould recommend that you read the project executive summaries as they provide a good summary of the overall conclusions. This work demonstrated the potential value of Biomass to Power with CCS technologies as a family, but it was clear at the time of the project, that the individual technologies were insufficiently mature to be able to 'pick a winner', due to the uncertainties around cost and performance associated with lower Technology Readiness Levels (TRLs).

TESBiC: Techno-Economic Study of Biomass to power with CCS. This model was developed as part of Work Package 3. It examines changes in cost, efficiency and emissions under different operating conditions for biodedicated IGCC with CCS. It should be read in conjunction with the Work Package 3 reports on model specification and user documentation. The Biomass to Power with CCS Phase 1 project consisted of four work packages: WP1: Landscape review of current developments; WP2: High Level Engineering Study (down-selecting from 24 to 8 Biomass to Power with CCS technologies); WP3: Parameterised Sub-System Models development; and WP4: Technology benchmarking and recommendation report. Reports generally follow this coding. We would suggest that you do not read any of the earlier deliverables in isolation as some assumptions in the reports were shown to be invalid. We would recommend that you read the project executive summaries as they provide a good summary of the overall conclusions. This work demonstrated the potential value of Biomass to Power with CCS technologies as a family, but it was clear at the time of the project, that the individual technologies were insufficiently mature to be able to 'pick a winner', due to the uncertainties around cost and performance associated with lower Technology Readiness Levels (TRLs).

TESBiC: Techno-Economic Study of Biomass to power with CCS. This model was developed as part of Work Package 3. It examines changes in cost, efficiency and emissions under different operating conditions for biodedicated IGCC with CCS. It should be read in conjunction with the Work Package 3 reports on model specification and user documentation. The Biomass to Power with CCS Phase 1 project consisted of four work packages: WP1: Landscape review of current developments; WP2: High Level Engineering Study (down-selecting from 24 to 8 Biomass to Power with CCS technologies); WP3: Parameterised Sub-System Models development; and WP4: Technology benchmarking and recommendation report. Reports generally follow this coding. We would suggest that you do not read any of the earlier deliverables in isolation as some assumptions in the reports were shown to be invalid. We would recommend thatyou read the project executive summaries as they provide a good summary of the overall conclusions. This work demonstrated the potential value of Biomass to Power with CCS technologies as a family, but it was clear at the time of the project, that the individual technologies were insufficiently mature to be able to 'pick a winner', due to the uncertainties around cost and performance associated with lower Technology Readiness Levels (TRLs).

TESBiC: Techno-Economic Study of Biomass to power with CCS. This model was developed as part of Work Package 3. It examines changes in cost, efficiency and emissions under different operating conditions for biodedicated IGCC with CCS. It should be read in conjunction with the Work Package 3 reports on model specification and user documentation. The Biomass to Power with CCS Phase 1 project consisted of four work packages: WP1: Landscape review of current developments; WP2: High Level Engineering Study (down-selecting from 24 to 8 Biomass to Power with CCS technologies); WP3: Parameterised Sub-System Models development; and WP4: Technology benchmarking and recommendation report. Reports generally follow this coding. We would suggest that you do not read any of the earlier deliverables in isolation as some assumptions in the reports wereshown to be invalid. We would recommend that you read the project executive summaries as they provide a good summary of the overall conclusions. This work demonstrated the potential value of Biomass to Power with CCS technologies as a family, but it was clear at the time of the project, that the individual technologies were insufficiently mature to be able to 'pick a winner', due to the uncertainties around cost and performance associated with lower Technology Readiness Levels (TRLs)

TESBiC: Techno-Economic Study of Biomass to power with CCS. This model was developed as part of Work Package 3. It examines changes in cost, efficiency and emissions under different operating conditions for biodedicated IGCC with CCS. It should be read in conjunction with the Work Package 3 reports on model specification and user documentation. The Biomass to Power with CCS Phase 1 project consisted of four work packages: WP1: Landscape review of current developments; WP2: High Level Engineering Study (down-selecting from 24 to 8 Biomass to Power with CCS technologies); WP3: Parameterised Sub-System Models development; and WP4: Technology benchmarking and recommendation report. Reports generally follow this coding. We would suggest that you do not read any of the earlier deliverables in isolation as some assumptions in the reports were shown to be invalid. We would recommend that you read the project executive summaries as they provide a good summary of the overall conclusions. This work demonstrated the potential value of Biomass to Power with CCS technologies as a family, but it was clear at the time of the project, that the individual technologies were insufficiently mature to be able to 'pick a winner', due to the uncertainties around cost and performance associated with lower Technology Readiness Levels (TRLs)

TESBiC: Techno-Economic Study of Biomass to power with CCS. This model was developed as part of Work Package 3. It examines changes in cost, efficiency and emissions under different operating conditions for biodedicated IGCC with CCS. It should be read in conjunction with the Work Package 3 reports on model specification and user documentation. The Biomass to Power with CCS Phase 1 project consisted of four work packages: WP1: Landscape review of current developments; WP2: High Level Engineering Study (down-selecting from 24 to 8 Biomass to Power with CCS technologies); WP3: Parameterised Sub-System Models development; and WP4: Technology benchmarking and recommendation report. Reports generally follow this coding. We would suggest that you do not read any of the earlier deliverables in isolation as some assumptions in the reports were shown tobe invalid. We would recommend that you read the project executive summaries as they provide a good summary of the overall conclusions. This work demonstrated the potential value of Biomass to Power with CCS technologies as a family, but it was clear at the time of the project, that the individual technologies were insufficiently mature to be able to 'pick a winner', due to the uncertainties around cost and performance associated with lower Technology Readiness Levels (TRLs).

The British Oceanographic Data Centre (BODC) is a national facility for looking after and distributing data concerning the marine environment. The British Oceanographic Data Centre (BODC) is a national facility for looking after and distributing data concerning the marine environment. It is part of the UKs National Oceanography Centre.

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.

The CEDA Archive forms part of NERCs Environmental Data Service (EDS) and is responsible for looking after data from atmospheric and earth observation research. It hosts over 18 Petabytes of data from climate models, satellites, aircraft, met observations, and other sources.

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.

UK household energy consumption (quantiles) aggregated by household income (quantiles) developed by Centre for Sustainable Energy (CSE) for the Distributional Impacts Model for Policy Scenario Analysis (DIMPSA), also used under license by the UK Government for assessment of the distributional impacts of Government policy. Underlying Dimpsa is a comprehensive dataset developed of UK household energy consumption. This dataset is derived from the socio-demographically representative sample of UK households surveyed in the Office of National Statistics Living Costs and Food Survey. Data from six of these surveys (2004/5 to 2009) has been combined, generating a sample size of over 36,000 cases.

The Centre for Sustainable Energy (CSE) Fuel Poverty Calculator has been updated to account for the new definition of fuel poverty: Low Income Low Energy Efficiency (LILEE).

Fuel poverty is when people have to spend a high proportion of their income to keep their home warm due to a combination of poor housing with inadequate insulation and heating, expensive energy tariffs, and low incomes. One outcome for those in fuel poverty is poor physical and mental health. NICE, which provides evidence-based guidance for NHS and social care professionals, recognises that living in a cold home will make most health conditions worse from childhood asthma to heart disease.

The Centre for Sustainable Energy (CSE) has downloaded and compiled selected data relevant to housing and energy use at the lowest available geographical area level from the UK Office for National Statistics 2011 census summary data. Lower Super Output Areas (LSOA) typically contain 70 to 150 households and so cover a relatively small geographical area. The Office for National Statistics publishes summary census data over a range of geographical levels after a national census has been performed. As the 2011 census data has become available, CSE has downloaded and compiled selected datasets at the lowest available geographical area. Output levels typically contain 70 to 150 households and so cover a relatively small geographical area, dependent upon rurality.
CSE has downloaded and joined key data sets from the Office for National Statistics census 2011 website. There are many potentially interesting topics that could be investigated from the data available, and CSE has chosen data that could be relevant to characterising housing and their energy usage.
No processing has been performed on this data, and so for any questions and information about the data users should refer to the Office for National Statistics website. Users should be particularly aware of the statistical disclosure control for 2011 census information.

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.

Carbon Reduction Commitment Energy Efficiency Scheme (CRC) participant information on the basis of their annual reports plus details submitted when they registered for the scheme. Each year, CRC participants have to monitor their energy consumption and report this information into the CRC Registry, an online IT system, which calculates their carbon dioxide (CO2) emissions. Participants must purchase and surrender 'allowances' to cover these emissions - one allowance for each tonne of CO2. Further information on the scheme can be found on the CRC pages of GOV.UK
The data should be read in combination with the equivalent years CRC Energy Efficiency Scheme: annual report publication which are located on GOV.UK

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.

Annual data on carbon dioxide emissions intensity, measuring the level of emissions per unit of economic output. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

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 population censuses are a vital resource for social scientific research and policy development, providing a snapshot of demographic and social life in the UK. They are collected by three census agencies. Census support gives access to:

• 2011 Census - aggregate data, boundary data, flow data and microdata
• 2001 Census - aggregate data, boundary data, flow data andmicrodata
• 1991 Census - aggregate data, boundary data, flow data and microdata
• 1981 Census - aggregate data, boundary data and flow data
• 1971 Census - aggregate data, boundary data

Also has a link to other census tools for investigating other longitudinal, historical or secure versions of data. The next Census is due in 2021.Data types held include

• aggregate data
• flow data
• microdata
• boundary data

Also holds data related to the census, such as Experian data anddeprivation data.

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.

Climate Watch provides open climate data, visualizations and resources on national and global progress on climate change. This free platform enables users to create and share custom data visualizations and comparisons of national climate commitments. Citation of the Climate Watch platform and data: Climate Watch. 2020. Washington, DC: World Resources Institute. </br>Most data carry a Creative Commons CC BY 4.0 license unless noted otherwise.

Climate data explorer, provides free access to climate related data and visualization tools. Climate Watch, a new online climate data platform aimed at policymakers, researchers, media and other stakeholders. Climate Watch holds climate data, visualizations and resources on national and global progress on climate change.

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.

Peer-to-peer (P2P) energy trading could help address grid management challenges in a decentralizing electricity system, as well as provide other social and environmental benefits. Many existing and proposed trading schemes are enabled by blockchain, a distributed ledger technology (DLT) relying on cryptographic proof of ownership rather than human intermediaries to establish energy transactions. This study used an online survey experiment (n = 2064) to investigate how consumer demand for blockchain-enabled peer-to-peer energy trading schemes in the United Kingdom varies depending on how the consumer proposition is designed and communicated. The analysis provides some evidence of a preference for schemes offering to meet a higher proportion of participants energy needs and for those operating at the city/region (as compared to national or neighbourhood) level. People were more likely to say they would participate when the scheme was framed as being run by their local council, followed by an energy supplier, community energy organization, and social media company. Anonymity was the most valued DLT characteristic and mentioning blockchains association with Bitcoin led to a substantial decrease in intended uptake. We highlight a range of important questions and implications suggested by these findings for the introduction and operation of P2P trading schemes.

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 Customer-Led Network Revolution project assessed the potential of novel smart grid network technologies, new commercial arrangements and customer flexibility solutions to find cost-effective ways to prepare UK electricity networks for the future. Datasets include Enhanced profiling of domestic customers electric hot water immersion heating & storage heating; Real-Time Thermal Rating for Extra High Voltage Underground Cables; Enhanced Automatic Voltage Control for Low Voltage Network Regulator; and many more Many resources available including datasets, analysis, reports and videos. The datasets are in the Project Library: search for Dataset to find them, including an overview guide to the datasets.

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.

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.

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.

A set of maps, graphs and other figures showing countries power consumptions, population densities, and areas, and comparing power consumptions per unit area with the power production per unit area of various renewables. Created Sir David John Cameron MacKay, FRS, FInstP, FICE, Regius Professor of Engineering in the Department of Engineering at the University of Cambridge. From 2009 to 2014 he was Chief Scientific Adviser to the UK Department of Energy and Climate Change (DECC). Author of the book Sustainable Energy - Without the Hot AirVarious versions of each map, chart or figure are available depending on the intended use, such as higher resolution for printing and as sequences for presentations.

Large collection of statistics on many transport-related subjects, many of which are updated on a monthly basis. This includes the Transport Statistics for Great Britain; in many cases statistics publications during the year provide the first release of data and these are consolidated into the TSGB tables. TSGB is a snapshot of the latest data available at the time of publication. It is published annually The whole set of statistics covers Aviation, Biofuels, Buses, Disabled parking badges, Driving tests and instructors, Free flow speeds, Journey time statistics, Light rail and tram, Maritime and shipping, National Travel Survey, Public attitudes towards transport, Rail, Road accidents and safety, Road congestion and reliability, Road freight: domestic and international, Road network size and condition, Road traffic, Search and rescue helicopter, Taxis, Transport energy and environment, Transport Statistics Great Britain, Vehicles, Walking and cycling

DUKES is an extensive collections of tables, charts and commentary with separate sections on coal, petroleum, gas, electricity, renewables and combined heat and power, providing a comprehensive picture of energy production and use over the last five years, with key series taken back to 1970. 2013 to date are online here, while older data is available at the National Archive. NB There is a pdf containing an useful index to the archived data. This is a series of PDF files, also available as printed booklets. The tables can be downloaded to Excel.

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.

Estimated unit energy consumption per annum (kWh/annum) (2006/2007) for various UK domestic cold appliances (chest freezer, fridge-freezer, refrigerator, upright freezer) by appliance energy class NC08 Assumptions underlying the energy projections for domestic cold appliances, Version 2.1 (2006) and Version 3.0 (2007) from DEFRA MTP. See also DEFRA Market Transformation Programme - efficient-products.ghkint.eu/

The Domestic Heating Data from the Energy Systems Catapult Living Lab covers approximately 100 domestic properties and includes data collected directly from sensors in each room: room temperature, room humidity, gas usage, electricity usage, radiator temperatures, boiler temperatures and water temperatures (hot and cold). Also data on how participants use their heating system: the times they request heating, the target temperatures requests and the type of schedule changes made. Also included are local weather data, including forecasts and local observations. The participants were approximately 100 owner occupied homes with gas boilers from across the United Kingdom.

Estimated ownership of UK domestic washing machines and washer dryers (percentage of households) Historic data suggests that the average annual unit energy consumption for a domestic washing machine in the UK is 268 kWh (1999). It is assumed that a 60C wash uses 40% less energy than a 90C wash; and a 40C wash uses 40% less energy than a 60C wash for estimated number of uses of each cycle). An average load capacity of 5.58 kg in 2006 was assumed, rising by 0.025 kg/year to allow for the future availability of larger capacity machines. Washing machines typically do not adjust water and energy consumption if a smaller load is washed. Average water consumption per wash was estimated to be 50 litres (2006); 80% of energy consumption is for heating water in the wash phase.
It is assumed that the best available appliances will be A (2006-2009) and A+ (2010-2020).
BNW05 Assumptions underlying the energy and water projections for washing machines, Version 2.0 from Defra MTP; data based on Gfk and historical modelling by DECADE and Fawcett, T., Lane K., Boardman, B., et al, 2000, Lower Carbon Futures for European Households, Environmental Change Institute Oxford Appendix F, UK 1 Table 1 (using data from the English Housing Condition Survey)

Estimated unit energy consumption per cycle (2006) for UK domestic washing machines by appliance energy class Historic data suggests that the average annual unit energy consumption for a domestic washing machine in the UK is 268 kWh (1999). It is assumed that a 60C wash uses 40% less energy than a 90C wash; and a 40C wash uses 40% less energy than a 60C wash. An average load capacity of 5.58 kg in 2006 was assumed, rising by 0.025 kg/year to allow for the future availability of larger capacity machines. Washing machines typically do not adjust water and energy consumption if a smaller load is washed. Average water consumption per wash was estimated to be 50 litres (2006); 80% of energy consumption is for heating water in the wash phase.
It is assumed that the best available appliances will be A (2006-2009) and A+ (2010-2020).

Estimated number of use cycles by temperature programme for UK domestic washing machines

The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information. The International Energy Statistics provides an overview with visualizations for different energy sources, an interactive graphical tool, and various analyses at country and topic level.

The U.S. Energy Information Administration is committed to enhancing the value of its free and open data by making it available through an Application Programming Interface (API) and open data tools to better serve our customers. The data in the API is also available in bulk file, in Excel via the add-in, and via widgets that embed interactive data visualizations of EIA data on any website. By making EIA data available in machine-readable formats, the creativity in the private, the non-profit, and the public sectors can be harnessed to find new ways to innovate and create value-added services powered by public data. https://www.eia.gov/opendata/

Annual update to tables on emissions of important air pollutants in the UK: sulphur dioxide, nitrogen oxides, non-methane volatile organic compounds, ammonia and particulate matter. The estimation methodology is regularly developed to take account of new emission factors and modelling methods. This means the whole time series is revised annually. The figures given in this document and the supporting dataset show the revised estimates.

An annual update of data on concentrations of major air pollutants in the UK. This data set contains data on the concentrations of major air pollutants as measured by the Automatic Urban and Rural Network (AURN). Data formats various - CSV and open document ODS.

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 Greenhouse Gas Reporting Program (GHGRP) collects Greenhouse Gas (GHG) data from large emitting facilities, suppliers of fossil fuels and industrial gases that result in GHG emissions when used, and facilities that inject carbon dioxide underground. Datasets available include high level summaries (maps, charts etc), an interactive tool for facility-level access, multi-year data summary spreadsheets and searchable, downloadable facility-level datasets by 32 industry types. The data is not confined to CO₂ There are other datasets available on the site from the Greenhouse Gas Reporting Program (GHGRP) and the U.S. Inventory of Greenhouse Gas Emissions and Sinks. The Inventory goes back to 1990, but is not mappable to location as it works on aggregate national figures. The GHGRP is a more recent program, developed in response to Congressional mandate from 2008, so there are fewer years of data available. It works on reports from facilities, so can be mapped by location. Annual GHG data for covered facilities in 29 industry types is available starting in 2010. Annual GHG data for covered facilities in an additional 12 industry types is available starting in 2011.

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 EU ETS data viewer provides access to emission trading data contained in the European Union Transaction Log (EUTL) which is the central transaction log. Including data from more than 15000 stationary installations reporting under the EU emission trading system, as well as 1500 aircraft operators.

European economic statistics - includes climate and energy (total energy, electricity generation, energy intensity). Eurostat is the statistical office of the European Union situated in Luxembourg. Its task is to provide the European Union with statistics at European level that enable comparisons between countries and regions. The website has available downloadable statistics, population census information for 2011, web services, microdata, GIS, metadata definitions, SDMX (Statistical Data and Metadata eXchange), and data validation information. Datasets are in tab separated values and sdmz format. Downloads can be automated. All information is updated twice a day.Eurostats main role is to process and publish comparable statistical information at European level. Eurostat does not collect data. This is done in Member States by their statistical authorities. They verify and analyse national data and send them to Eurostat. Eurostats role is to consolidate the data and ensure they are comparable, using harmonized methodology. The European Statistical System (ESS) is the partnership between the Community statistical authority, which is the Commission (Eurostat), and the national statistical institutes (NSIs) and other national authorities responsible in each Member State for the development, production and dissemination of European statistics. This Partnership also includes the EEA and EFTA countries. Member States collect data and compile statistics for national and EU purposes. The ESS functions as a network in which Eurostats role is to lead the way in the harmonization of statistics in close cooperation with the national statistical authorities. ESS work concentrates mainly on EU policy areas - but, with the extension of EU policies, harmonization has been extended to nearly all statistical fields. The ESS also coordinates its work with candidate countries and at European level with other Commission services, agencies and the ECB and international organisations such as OECD, the UN, the International Monetary Fund and the World Bank.

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.

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 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.

Emissions factors for road transport atmospheric pollutants and vehicle fleet projections data. Archived versions are also available. Please refer to the guidance notes (either in PDF or within the spreadsheet Notes page) for more information about the datasets provided.

This file provides a harmonised data for the UK main manufacturing industry based on the NAEI 2020 data https://naei.beis.gov.uk/data/map-large-source, which can be used for analysis and modelling.Since the original NAEI data include sites that do not fall within the definition of manufacturing industry, we created this harmonised data for ease of use. We classified the sectors into: Iron and steel, Chemicals, Cement, Food and drink, Paper, Refining, Lime, Glass, Ceramics, Other minerals, and Other industry. We also converted the 'Easting' and 'Northing' to 'Latitude' and 'Longitude'.

Energy Consumption in the United Kingdom (ECUK) is an annual statistical publication that provides a comprehensive review of energy consumption and changes in efficiency, intensity and output since the 1970s, with particular focus on trends since 2000. ECUK is split into five chapters: (1) Overall energy consumption in the UK; (2) Transport sector energy consumption; (3) Domestic sector energy consumption; (4) Industrial sector energy consumption; (5)Services sector energy consumption. Each chapter contains an Excel workbook and a factsheet summarising key trends and information within that sector. ECUK is split into five chapters:

• Chapter 1: Overall energy consumption in the UK
• Chapter 2: Transport sector energy consumption
• Chapter 3: Domestic sector energy consumption
• Chapter 4: Industrial sector energy consumption
• Chapter 5: Services sector energy consumption

Each chapter contains an Excel workbook and a factsheet summarising key trends and information within that sector.

Previous issues may be available from the National Archive

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.

The Energy Performance of Buildings provides access to Energy Performance Certificates and Display Energy Certificates data for buildings in England and Wales by search and browsing, or via and API, and for individual or bulk download. Access rights are mixed. Some parameters are Royal Mail Copyright and other data fall under the Open Government Licence. For more information see https://epc.opendatacommunities.org/docs/copyright
The Energy Performance of Buildings Register is the official place for all Energy Performance Certificates (EPCs), Display Energy Certificates (DECs) and Air Conditioning Inspection Reports (ACIRs).
This site is has been made available for data analysis. To check for compliance with all regulatory and legal requirements the definitive source of EPCs, DECs and ACIRs is the registers and not the data published on this website.

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.

Energy Systems Catapult was set up to accelerate the transformation of the UK’s energy system and ensure UK businesses and consumers capture the opportunities of clean growth. The Catapult is an independent, not-for-profit centre of excellence that bridges the gap between industry, government, academia and research. This links to the searchable interface for the public datasets.

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 UK's energy use from renewable sources used to generate heat (active solar heating, heat pumps, geothermal aquifers) These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

The English House Condition Survey (EHCS) was a national survey of housing in England. It was originally called the National House Condition Survey and covered England and Wales. From April 2008, the EHCS merged with the Survey of English Housing (SEH) to form the English Housing Survey (EHS). The English House Condition Survey (EHCS) was a national survey of housing in England, commissioned by the Ministry of Housing, Communities and Local Government (MHCLG). The survey was originally called the National House Condition Survey and covered England and Wales. The EHCS ran quinquennially from 1967-2001. From 2002, the survey moved to a continuous basis and the data were provided as a two-year rolling sample of approximately 16,000 cases. From April 2008, the EHCS merged with the Survey of English Housing (SEH) to form the English Housing Survey (EHS).

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 English Housing Survey (EHS), 2012: Fuel Poverty Dataset is derived from the 2012 EHS database. The dataset is the outcome of analysis conducted to produce estimates of the number of households living in fuel poverty in England in 2012. Previously, a household was defined as being fuel poor if they spent more than 10% of their income on fuel. The English Housing Survey, 2012: Fuel Poverty Dataset is derived from the 2012 EHS database created by the DCLG. This database is constructed from fieldwork carried out between April 2011 and March 2013. The midpoint of this period is April 2012, which can be considered as the reference date for the fuel poverty dataset.

Statistics from the Welsh Government on air quality, energy, flooding, fly-tipping, greenhouse gases, land, state of the environment and waste management. Releases of official statistics and research on Wales are found at https://gov.wales/statistics-and-research

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 European Environment Agency provides sound, independent information on the environment for those involved in developing, adopting, implementing and evaluating environmental policy, and also the general public. The site includes interactive data viewers for datasets. There are also visualizations on specific topics such as Progress on Energy Efficiency in Europe, and publications. A major information source for those involved in developing, adopting, implementing and evaluating environmental policy, and also the general public. Currently, the EEA has 33 member countries. The website is available in a wide range of languages. There is a Semantic Data Service, allowing access to datasets using APIs, but datasets can also be downloaded as zip files and INSPIRE-compliant metadata sets. No registration is needed, but on download, some usage feedback is requested.

The Industrial Emissions Portal covers over 60,000 industrial sites from 65 economic activities across Europe. These activities cover a range of sectors including energy. Data can be browsed in a map of sites, here. Full datasets and guidance documents can be downloaded. Various data analysis tools and visualisations are available.

Annual, quarterly and monthly feed-in tariff statistics. Solar photovoltaic deployment and costs. Load factors. The feed-in-tariff is a payment made to some renewable energy generators. Although the feed-in-tariff stopped accepting new applications from 31st March 2019, the solar photovoltaic and other data and analysis are more recent.

Final estimates of UK greenhouse gas emissions going back to 1990. These statistics are used to monitor progress against the UK's emissions reductions targets and take into account the EU Emissions Trading System (EU ETS). Estimates are presented by source in February each year, then updated in March each year to include estimates by end-user and fuel type, and in June to include estimates by Standard Industrial Classification (SIC).

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.

Fuel poverty statistics on households in fuel poverty in rural and urban areas (fuel poverty by rurality). Statistics on the proportion of households that are fuel poor in rural and urban areas, and the average fuel poverty gap (the additional income which would be needed to bring a household to the point of not being fuel poor.)

Statistics relating to the demographics of fuel poverty in England, where fuel poverty is defined by the Low Income / High Costs balance, which considers a household to be in fuel poverty if: (i) the household has required fuel costs above average (national median level) and (ii) was the household to spend that amount it would be left with a residual income below the official poverty line. The key drivers behind fuel poverty are:
The energy efficiency of the property (and therefore, the energy required to heat and power the home);
The cost of energy;
Household income.
Registration with the UK Data Archive is required before data can be accessed

Centre for Sustainable Energy (CSE) has published a complete list of Great Britain postcodes that are not connected to the mains gas grid, up-to-date for 2017. Also included are the census area and the co-ordinates of the centre of each postcode on the list. NB There are over 381,385 postcodes in this dataset. Please be aware that conversion to other file formats such as .xls may result in loss of data, because not all spreadsheets support a sufficient number of rows. After conversion, please check the number of records before you use the data (the final postcode - ZE3 9JZ - should be in row number 381,386).

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 energy transition statistics: production, consumption and trade of oil, gas, coal, power and renewables; CO2 emissions from fuel combustion. Data browsing, interactive map and visualisations.

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

Global wind speed data for onshore and offshore, up to 200km from the coast. 250m grid wind speeds at 10, 50, 100, 150 and 200m above ground or sea level. Energy yield tool 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

DS4DS: Heat, non-heating electricity and home-based transport energy demand for Great Britain in 2009 at 1 km square resolution in units of kWh/km² from UK Department of Energy & Climate Change (DECC) sub-national energy consumption statistics.
Please acknowledge the School of Civil and Building Engineering, Loughborough University when making any use of this data. Data is available as a txt file (which is really a csv file) and ESRI Shapefiles.
Methods and results were reported in Taylor S, Firth S, Wang C, Allinson D, Quddus M, Smith P (2014) Spatial mapping of building energy demand in Great Britain. Global Change Biology Bioenergy, 123-135. https://doi.org/10.1111/gcbb.12165.
The coordinate system is British National Grid.

DS4DS Great Britain energy demand (2009) - Proportions of energy demand projected for future years (for application to table of energy demand data for GB in 2009).
Tables of dimensionless scenario factors for 2000 to 2050 in 5-year steps for domestic and non-domestic heat and non-heating electricity demand for two scenarios: UKERC scenarios ADD and LC
Please acknowledge the School of Civil and Building Engineering, Loughborough University when making any use of this data. Two csv files, one for each scenario.
Methods and results were reported in Taylor S, Firth S, Wang C, Allinson D, Quddus M, Smith P (2014) Spatial mapping of building energy demand in Great Britain. Global Change Biology Bioenergy, 123-135.

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.

Using heat demand data for domestic buildings sourced from the UKERC Energy Data Centre's "Spatio-temporal heat demand for LSOAs in England and Wales", we have identified Lower Layer Super Output Areas (LSOAs) exhibiting a linear heat density surpassing 2900 kWh/m indicating their potential suitability for a heat network. We have integrated borehole information from the British Geological Survey (BGS) Single Onshore Borehole Index (SOBI), the average thermal conductivity of general soils and rocks, SAP 10.2 annual average temperature on the ground surface, and the average geothermal gradient for council areas in Great Britain. Employing the specific heat extraction rate methodology, and referencing MCS 022 Borehole Heat Exchanger look-up tables, we have generated comprehensive heat supply potential data from boreholes.

View an interactive map using ArcGIS map viewer

This data collection includes a User Guide and the anonymised transcripts of 30 semi-structured interviews of #60-90 minutes each, with 31 high household energy consumers, about their homes, appliances, infrastructures, vehicles, and everyday life and travel practices that generate household (domestic and travel-related) energy demand. It also includes the anonymised transcripts of 4 3-hour deliberatively workshops of ~8 public participants and 2 facilitators, one recruited from the interviewees, and the others recruited to represent different levels of domestic and travel-related energy consumption, held to discuss the validity, fairness, effectively and acceptability of four broad policy approaches to reduce (particularly high levels of) household energy consumption: Rationing; Economic (Dis)Incentives; Structural Change; and Behaviour Change

The data are the results of tests carried out in a project funded by the Energy Technologies Institute (ETI) to model at reduced scale, the consequences of a flameout in a full-size combined cycle gas turbine (CCGT) when running on high hydrogen fuel mixtures. The High Hydrogen data set includes data from 69 Circular Duct Tests and 76 tests with a Heat Recovery Steam Generator. The data are further described by read me files in each directory and by reports in the directory Supporting_Documentation.
Phase 1 data (Circular Duct tests 1 - 69 and Heat Recovery Steam Generator tests 1 to 17) were added in December 2017. Phase 2 data (Heat Recovery Steam Generator tests 18 to 76) were added in December 2019, when this catalogue entry was updated accordingly.

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.

The HES measured electricity consumption at an appliance level in 250 owner-occupied households across England from 2010 to 2011, the most detailed monitoring of electricity use ever carried out in the UK. Extensive analysis has been undertaken on appliance ownership, labels, actual efficiencies and potential for savings in different social groups. The study has also examined the scope for reducing peak electricity demand. The full dataset is not available via the web. A sample, and numerous reports and analyses are freely available. There are also three spreadsheet tools provided.
The Household Electricity Survey (HES) was the most detailed monitoring of electricity use ever carried out in the UK. Electricity consumption was monitored at an appliance level in 250 owner-occupied households across England from 2010 to 2011. Extensive analysis has been undertaken on appliance ownership, labels, actual efficiencies, potential for savings in different social groups and the potential to reduce peak electricity demand.

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.

Impact is a parish-level carbon emission estimator which tells you how people in the parish travel and heat their homes, and other activities in the area that contribute to the local carbon emissions total. It shows territorial and consumption based emissions calculations. Graphical data charts and csv download are available.

The Aquifer Brine project assessed the modeled impact of removing brine from potential undersea carbon dioxide stores on store capacity and costs using selected real locations and synthetic models. It followed on from the UK Storage Appraisal Project which assessed the UK CO2 storage capacity for CCS in offshore geological formations.

The Aquifer Brine project assesses the potential for brine production through dedicated wells in target CO2 storage formationsto increase CO2 storage capacity and reduce the overall cost of storage - as well as any other potential benefits forCO2 store operators associated with brine production.

It followed on from the UK Storage Appraisal Project.

Proprietary software is needed to access the geological models. See ReadMe file with data for details.

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

This interactive map shows CO2 totals by local authority from the UK National Atmospheric Emissions Inventory. For Northern Ireland only:
This is Crown Copyright and reproduced with the permission of Land & Property Services under delegated authority from the Controller of Her Majestys Stationary Office Crown Copyright and database right 2021 INSP594.
Ordnance Survey of Northern Ireland (OSNI) branded Land & Property Services (LPS) mapping (or any mapping based on, or derived from OSNI branded mapping) is exempt from the terms of the OGL.
If you intend to use or re-use this information you need to email to copyright@dfpni.gov.uk for an appropriate licence.

Aluminium production statistics, including energy intensity and fuel and power consumption The International Aluminium Institute is an industry body.

World energy data and statistics which can be explored by category, indicator, country or region. Most downloads are Excel or PDF. Topics include Coal, CO₂ emissions, Electricity, Energy balances, Energy efficiency, Natural gas, Oil, Prices and taxes, RD&D and Renewables. Visualizations include Energy balance flows, energy indicators, European gas trade flows and key world energy statistics. There is a lot of analysis and synthesis provided.

Interviews with actors concerned with local transport decarbonisation in the UK, including challenges related to finance, governance arrangements, and public support. Data were collected using a series of 54 interviews, spread equally across three case study sites: 18 Nottingham, 18 Leeds, and 18 Oxford. Of those, 12 of the Nottingham interviews, all 18 of the Leeds interviews, and 8 of the Oxford interviews are shared in this data deposit (the rest did not give permission for their data to be deposited). The interviews were designed to reveal different local perspectives on areas recent attempts to decarbonise their transport system. The initial introduction to each participant was facilitated by pre-existing professional contacts, after which subsequent participants were identified by snowballing (i.e. feedback from interview participants) in combination with criteria-specific identification (i.e. from a review of published local authority documents

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.

The Community Energy Saving Programme (CESP) was designed to target the lowest income households living in homes that need significant investment in energy saving measures and low carbon technologies. CSE mined the CESP data stores to develop and publish a database of useful information to assist with this targeting. Ofgem CESP programme page:
https://www.ofgem.gov.uk/environmental-programmes/energy-companies-obligation-eco/previous-energy-efficiency-schemes
CESP Report location:
https://www.ofgem.gov.uk/ofgem-publications/58763/cesp-final-report-2013final-300413.pdf
For super output area (SOA) definitions:

http://www.ons.gov.uk/ons/guide-method/geography/beginner-s-guide/census/super-output-areas--soas-/index.html

The MAGIC website provides geographic information about the natural environment from across government. The information covers rural, urban, coastal and marine environments across Great Britain. It is presented in an interactive map which can be explored using various mapping tools that are included. Datasets in MAGIC have licences depending on their origin. The map images are provided by Ordnance Survey and subject to Crown Copyright. Further information about copyright is found on the MAGIC site under About, Legal Documentation, Copyright information. Further information about dataset licences is found on the Dataset and Download Listings page (a link in the Copyright information page).

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.

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.

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

Researchers at the Met Office Hadley Centre produce and maintain a range of gridded datasets of meteorological variables for use in climate monitoring and climate research. Including datasets that started in the 1830s onwards. This site provides access to these datasets or, in some cases, links to other places from where where they can be obtained. Each data set is provided under specific license terms please check the terms and conditions for each data set before you use it. <p>Please note that this is not an operational service. This site is run by research staff with the primary aim of improving collaboration with fellow researchers. Everyone is welcome to use the site, and we aim to make it reliable, but it does not have the same level of support as the main Met Office website.</p> Please consider the use of these data resources in your work, if appropriate.</p>

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.

A sample of 49,815 records selected to be representative of the housing stock (based on Region, property age, property type and floor area band) representative of the national NEED data set (over 27 million records) of energy use and energy efficiency in domestic and non-domestic buildings in Great Britain. A sample dataset of 49,815 anonymised records selected to be representative of the housing stock (based on region, property age, property type and floor area band) representing a subset of the much larger NEED (address level) database.
A larger sample of 4 million records (4,086,448) is available from the UK Data Archive via an end user licence (https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=7518).

Large anonymised sample of 4 million records from the national NEED dataset of energy use and energy efficiency in domestic and non-domestic buildings in Great Britain. The data framework matches gas and electricity consumption data collected for UK Government sub-national energy consumption statistics and records of energy efficiency measures from HEED. It also includes typographic data about dwellings and households obtained from a variety of sources.
UKDA user licensing restructions apply.
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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>

A national dataset of energy use and energy efficiency in domestic and non-domestic buildings in Great Britain. The data framework matches gas and electricity consumption data collected for UK Government sub-national energy consumption statistics and records of energy efficiency measures from HEED. It also includes typographic data about dwellings and households obtained from a variety of sources. The National Energy Efficiency Data-Framework (NEED) was set up by UK Government to provide a better understanding of energy use and energy efficiency in domestic and non-domestic buildings in Great Britain. The data framework matches gas and electricity consumption data, collected for UK Government sub-national energy consumption statistics, with information on energy efficiency measures installed in homes, from the Homes Energy Efficiency Database (HEED). It also includes data about property attributes and household characteristics, obtained from a range of sources.

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.

A forecast of gas use in the UK in the next ten years, with different scenarios based on different assumptions about supply, demand, legislative change and asset health. Published annually. The PDF chapters provide the overview and context. The maps, charts and tables are in the appendices. The data supporting each chapter can be downloaded to Excel.

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

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.

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 non-gas map is a detailed map of Great Britain showing the distribution of properties without a gas grid connection across local authorities, LSOAs (lower-level super output areas) and, for registered users, postcodes. It also provides other information about properties and residents, from the type of house or flat to the type of heating and tenure. The data sources are as follows: Off-gas-grid properties, ECO and energy efficiency measures: BEIS. Tenure, central heating type, number of bedrooms (England/Wales) or rooms (Scotland): ONS (2011 census). Domestic Energy Performance Certificates: DCLG. Rural-urban designation: DEFRA, Scottish government. Indices of multiple deprivation: ONS, Welsh Government, Scottish Government. Claimant count: DWP, Scottish Government.

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.

Organisation for Economic Cooperation and Development (OECD) data - statistics, API access and publications. Database access available on the data warehouse, OECD.Stat. A suite of statistical tools is also available, as is a developer API. Topics include agriculture, development, economy, education, energy, environment, finance, government, health, innovation and technology, jobs and society. A range of charts and visualizations are also provided. A related resource is the OECD Library

As well as linking to the OECD Data statistics, this includes statistics from other sources such as the IEA, Nuclear Energy Agency and EUROSTAT, indicator information, factbook and yearbook series and other analyses and syntheses. Differs from the OECD Data offering as it draws on more sources and covers a wider range of countries. Acts as a federated search rather than holding its own datasets. However, there are far more books, papers, factbooks and so on accessible from here.

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.

The Odyssee database contains detailed energy efficiency and CO2-indicators with data on energy consumption, their drivers (activity indicators) and their related CO2-emissions. The Mure database contains a description, with their impact evaluation whenever available, of all energy efficiency measures implemented at EU or national level. Some data and tools are publically accessible but some are restricted access.

ONS main responsibilities are collecting, analysing and disseminating statistics about the UKs economy, society and population. This resource contains a large number of detailed datasets covering subjects such as

• The UKs national accounts (such as GDP, national income and expenditure)
• the UK balance of payments
• population, demography and migration statistics
• government output and activity
• business output and activity
• prices statistics (such as consumer prices and producer prices)
• the labour market (such as employment, unemployment and earnings)
• vital events statistics (such as births, marriages and deaths)
• social statistics (for example, about neighbourhoods and families)
• economic, societal and personal well-being

Data is presented on screen, and is downloadable as image, csv or xls. For each dataset, similar datasets are linked, along with publications using that dataset and a contact for the data. Time filters and revision data are presented. There are search tools and many other aids to interpretation and analysis

The Office of Rail and Road (ORR) Data Portal provides statistics and information about the UK railway industry. Much of the data is available without registration, but free registration gives access to more tools. The Office of Rail and Road (ORR) is a statutory board which is the combined economic and safety regulatory authority for Great Britains railway network, as well as being responsible for monitoring Highways England. As a non-ministerial government department it is operationally independent of central government.

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.

The Ofgem Energy Company Obligation (ECO) Eligibility System is a tool for confirming which postcodes are eligible for the Home Heating Cost Reduction Obligation (HHCRO). See https://eco.locationcentre.co.uk/help.aspx for more details.

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

Electricity data measured at one-minute resolution in 22 dwellings over two complete years (2008 and 2009). Each dwelling was fitted with a single meter covering electricity use of the whole dwelling, however, the one-minute resolution allows the switching of individual domestic appliances to be observed. The meters conform to BS EN 62053-21:2003 and measure true active power (taking proper account of the voltage). The study also includes the results of a dwelling characteristics survey which was completed for each dwelling detailing its characteristics and the types of appliances and lighting installed. The data are separated by dwelling (22) and year (2) so there are 44 data files of one-minute resolution domestic electricity use. A short survey of dwelling characteristics is includes; the main topics covered are: general energy use; lighting; and available appliances.

The Open Geography portal from the Office for National Statistics (ONS) provides free and open access to the definitive source of geographic products, web applications, story maps, services and APIs. Data include boundaries, administrative areas, classifications of a range of parameters as maps. All content is available under the Open Government Licence v3.0, except where otherwise stated.

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

Summary of analyses of options for a low carbon economy (includes MARKAL model results by Future Energy Solutions). This report contains the results of a study, undertaken on behalf of DTI, DEFRA and the PIU, to develop a range of bottom-up estimates of carbon dioxide emissions from the UK energy sector up to 2050, and to identify the technical possibilities and costs for the abatement of these emissions. Three levels of abatement by 2050 have been considered: a 60% reduction relative to emissions in 2000 - approximating to the level considered by the Royal Commission on Environmental Pollution (RCEP 2000) - plus 45% and 70% reductions relative to 2000 levels. Marsh, G, Taylor, P, Haydock, H, Anderson, D, Leach, M (2003). Options for a Low Carbon Future. DTI Economics Paper No 4, Department of Trade and Industry.

This report summarises the modelling work undertaken for the 2003 Energy White Paper using the MARKAL energy model. It describes the scenarios andsensitivities used in the modelling work. It concludes that there is a variety of carbon abatement options across the energy supply sector, in improving energy efficiency and across the transport sector. Total abatement costs are uncertain and vary considerably by scenario andsensitivity but are unlikely to have a significant impact on GDP growth.Innovation and technical progress are key elements in reducing the costs ofcarbon abatement. The report compares the costs from the MARKAL model with those from a range of other models. Most of the studies suggest GDP losses of under 3% in 2050. It looks at the different types of economic models used to analyse abatement costs and the reasons why they might produce varying cost estimates This is now archived.Leach, M, Anderson, D, Taylor, P, Marsh, G (2005). Options for a Low Carbon Future: Review of Modelling Activities and an Update. DTI Occasional Paper No 1, Department of Trade and Industry.

Energy data for countries, different energy sources, energy mix data, production, consumption and access data. Data from Global Change Data Lab in partnership with Oxford University's Oxford Martin School License: All the material produced by Our World in Data, including interactive visualizations and code, are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited. All other material, including data produced by third parties and made available by Our World in Data, is subject to the license terms from the original third-party authors.

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.

The Place-based Carbon Calculator (PBCC) is a free tool which estimates the per-person carbon footprint for every Lower Super Output Area (LSOA) in England. LSOAs are small statistical areas with a population of about 1,500 - 3,000. Includes data on housing, transport and other consumption emissions. Bulk download data and further information about the data sets are available at https://www.carbon.place/data/.

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 Pollution Inventory (PI) includes information on annual mass releases of specified substances to air controlled waters and sewers as well as quantities of waste transferred off site from large industrial sites regulated by the Environment Agency including sites in energy sectors. This replaced the Chemical Release Inventory (CRI) in 1998 and is sometimes referred to as the Inventory of Sources and Releases (ISR).

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.

The latest provisional estimates of UK greenhouse gas emissions based on provisional inland energy consumption statistics. Data are based on provisional inland energy consumption statistics, which are published in the government's quarterly Energy Trends publication.

UK Government's Department for Business, Energy and Industrial Strategy (BEIS), and predecessor departments, track public attitudes four times a year, in a range of its policy areas including climate change and energy. Questions on issues where it is thought that attitudes might shift quickly or be affected by seasonal changes are repeated quarterly; other questions are asked annually.

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

The datasets available for download include:1. The thermal characteristics for 16 dwelling categories for all the LSOAs in England and Wales before and after considering energy efficiency measures.2. The magnitude and duration of positive and negative flexibility services that can be provided by air source heat pumps in dwellings at local authority level. Dates refer to the input data to the model.

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.

The data collection form used during the field survey

Results from the field survey carried out to validate the provisional constraint mask developed during the desk study

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.

Deployment data for the non-domestic Renewable Heat Incentive (RHI) and the domestic RHI. Datasets are published on a monthly basis with supplementary statistical information published quarterly. Historical releases are available on request.

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.

Annual residential heat demand data for Scotland at Lower Layer Super Output Area (LSOA) level, before and after energy efficiency measures

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.

This spreadsheet contains the results for the article, "Meeting the costs of decarbonising industry – the potential effects on prices and competitiveness (a case study of the UK)". These include projected impacts for industrial process decarbonisation (costs, fuel use, residual emissions), for key years (2030, 2040, 2050), distributed in the following ways:

• Directly allocated to industrial sector in which they occur


• Shared between sectors in proportion to the share of GVA of each supply chain


• Embodied in final products


• Embodied in final products, aggregated to consumption patterns

The source of the projections and the method to perform the distribution are described in detail in the associated article.

Consumption statistics for fuels used in road transport at regional and local levels are available below. In March 2008, this dataset gained National Statistics status. This applies to all data from 2005 onwards.

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.

The Scottish Household Survey (SHS) is an annual, cross-sectional survey on the composition, characteristics, attitudes and behaviour of private households and individuals as well as evidence on the physical condition of Scotlands homes. Data Explorer tool available. Earlier data are available from the archive (linked from this site).

The Scottish House Condition Survey (SHCS) combines both an interview with occupants and a physical inspection of dwellings to build up a picture of Scotlands occupied housing stock.

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.