Results: Search for United Kingdom

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 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 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 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).

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

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

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) 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.

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.

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

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

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.

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 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 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.

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.

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

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

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.

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.

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.)

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.

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.

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

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.

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 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.

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

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

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

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

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

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.
.

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.

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.

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

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.

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.

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

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 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.

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.

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.

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

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

This data set presents the underlying data used to produce the results for the UKERC working paper: Sensitivity Analysis of Net Zero Pathways for UK Industry or by searching the UKERC Publications section of this website. These data are the outputs of a how the The Net-Zero Industry Pathways (N-ZIP) model results are affected by changing a wider range of inputs than have been previously studied. The Net-Zero Industry Pathways (N-ZIP) model, developed by Element Energy, has been used by both the Climate Change Committee (CCC) and the Government to explore how industry can be decarbonised in way that is consistent with the UKs netzero greenhouse gas (GHG) target. This data set presents the underlying data used to produce the results for the UKERC working paper: Sensitivity Analysis of Net Zero Pathways for UK Industry or by searching the UKERC Publications section of this website.

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

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

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

BEIS produce a wide range of official statistics including downloadable datasets, projections and trend information on a range of energy, environmental and social topics. Official Statistics are produced impartially and free from political influence.Due to organisational change, this webpage is no longer updated after May 2023 Some historical datasets back to 1890. Very wide ranging set of information held in the UK government statistics website.

National and official statistics relating to the environment, rural communities, food and farming. Environment statistics including air quality and emissions statistics, environmental protection expenditure survey, sustainable development indicators,digest of waste and resources statistics; Food statistics including food transport indicators; and Land management and environmental issues. Previous statistical releases are available on the NationalArchives.

This spreadsheet provides a detailed Level 2 Cost Estimate for the Minimum Viable Development of Captain Subsea Option - MVD (No Goldeneye) for CO2 CCS Storage in the Central North Sea.

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

This spreadsheet provides a detailed Level 2 Cost Estimate for the Minimum Viable Development of CCS Storage in the Ormskirk Sandstone in the faulted horst block known as Hamilton (UKCS block 110/13) in the East Irish Sea.

This spreadsheet provides a detailed Level 2 Cost Estimate for CCS Storage in Site 2: Forties 5 - South Site

This spreadsheet provides a detailed Level 2 Cost Estimate for the Minimum Viable Development of Site 7: Bunter Closure 36 for CCS Storage.

This spreadsheet provides a detailed Level 2 Cost Estimate for the Minimum Viable Development of Site 7: Bunter Closure 36 for CCS Storage.

Geological and reservoir engineering models for five potential CO2 storage sites around the UK. Five sites were selected from the UKs national CO2 storage database CO2Stored which was created by the UK Storage Appraisal Project (UKSAP). Outline storage development plans and budgets were prepared for each.
The project was funded by DECC, commissioned by the ETI and carried out by Pale Blue Dot Energy, Axis Well Technology and Costain.
The data are further described by read me files in each directory and by reports in the Reports directory.

This project, funded with up to £2.5m from the UK Department of Energy and Climate Change (DECC - now the Department of Business, Energy and Industrial Strategy), was led by Aberdeen-based consultancy Pale Blue Dot Energy supported by Axis Well Technology and Costain. The project appraised five selected CO2 storage sites towards readiness for Final Investment Decisions. The sites were selected from a short-list of 20 (drawn from a long-list of 579 potential sites), representing the tip of a very large strategic national CO2 storage resource potential (estimated as 78,000 million tonnes). The sites were selected based on their potential to mobilise commercial-scale carbon, capture and storage projects for the UK. Outline development plans and budgets were prepared, confirming no major technical hurdles to storing industrial scale CO2 offshore in theUK with sites able to service both mainland Europe and the UK. The project built on data from CO2stored - the UK's CO2 storage atlas - a database which was created from the ETI's UK Storage Appraisal Project. This is now publically available and being further developed by The Crown Estate and the British Geological Survey. Information on CO2Stored is available atwww.co2stored.com. This spreadsheet is the appraisal model of Site 14: Captain Aquifer

This project, funded with up to £2.5m from the UK Department of Energy and Climate Change (DECC - now the Department of Business, Energy and Industrial Strategy), was led by Aberdeen-based consultancy Pale Blue Dot Energy supported by Axis Well Technology and Costain. The project appraised five selected CO2 storage sites towards readiness for Final Investment Decisions. The sites were selected from a short-list of 20 (drawn from a long-list of 579 potential sites), representing the tip of a very large strategic national CO2 storage resource potential (estimated as 78,000 million tonnes). The sites were selected based on their potential to mobilise commercial-scale carbon, capture and storage projects for the UK. Outline development plans and budgets were prepared, confirming no major technical hurdles to storing industrial scale CO2 offshore in theUK with sites able to service both mainland Europe and the UK. The project built on data from CO2stored - the UK's CO2 storage atlas - a database which was created from the ETI's UK Storage Appraisal Project. This is now publically available and being further developed by The Crown Estate and the British Geological Survey. Information on CO2Stored is available atwww.co2stored.com. This spreadsheet is the appraisal model of Site 19: Hamilton

This project, funded with up to £2.5m from the UK Department of Energy and Climate Change (DECC - now the Department of Business, Energy and Industrial Strategy), was led by Aberdeen-based consultancy Pale Blue Dot Energy supported by Axis Well Technology and Costain. The project appraised five selected CO2 storage sites towards readiness for Final Investment Decisions. The sites were selected from a short-list of 20 (drawn from a long-list of 579 potential sites), representing the tip of a very large strategic national CO2 storage resource potential (estimated as 78,000 million tonnes). The sites were selected based on their potential to mobilise commercial-scale carbon, capture and storage projects for the UK. Outline development plans and budgets were prepared, confirming no major technical hurdles to storing industrial scale CO2 offshore in theUK with sites able to service both mainland Europe and the UK. The project built on data from CO2stored - the UK's CO2 storage atlas - a database which was created from the ETI's UK Storage Appraisal Project. This is now publically available and being further developed by The Crown Estate and the British Geological Survey. Information on CO2Stored is available atwww.co2stored.com. This spreadsheet is the appraisal model of Site 2: Forties 5 (North And South Combined)

This project, funded with up to £2.5m from the UK Department of Energy and Climate Change (DECC - now the Department of Business, Energy and Industrial Strategy), was led by Aberdeen-based consultancy Pale Blue Dot Energy supported by Axis Well Technology and Costain. The project appraised five selected CO2 storage sites towards readiness for Final Investment Decisions. The sites were selected from a short-list of 20 (drawn from a long-list of 579 potential sites), representing the tip of a very large strategic national CO2 storage resource potential (estimated as 78,000 million tonnes). The sites were selected based on their potential to mobilise commercial-scale carbon, capture and storage projects for the UK. Outline development plans and budgets were prepared, confirming no major technical hurdles to storing industrial scale CO2 offshore in theUK with sites able to service both mainland Europe and the UK. The project built on data from CO2stored - the UK's CO2 storage atlas - a database which was created from the ETI's UK Storage Appraisal Project. This is now publically available and being further developed by The Crown Estate and the British Geological Survey. Information on CO2Stored is available atwww.co2stored.com. This spreadsheet is the appraisal model of Site 5: Viking

This project, funded with up to £2.5m from the UK Department of Energy and Climate Change (DECC - now the Department of Business, Energy and Industrial Strategy), was led by Aberdeen-based consultancy Pale Blue Dot Energy supported by Axis Well Technology and Costain. The project appraised five selected CO2 storage sites towards readiness for Final Investment Decisions. The sites were selected from a short-list of 20 (drawn from a long-list of 579 potential sites), representing the tip of a very large strategic national CO2 storage resource potential (estimated as 78,000 million tonnes). The sites were selected based on their potential to mobilise commercial-scale carbon, capture and storage projects for the UK. Outline development plans and budgets were prepared, confirming no major technical hurdles to storing industrial scale CO2 offshore in theUK with sites able to service both mainland Europe and the UK. The project built on data from CO2stored - the UK's CO2 storage atlas - a database which was created from the ETI's UK Storage Appraisal Project. This is now publically available and being further developed by The Crown Estate and the British Geological Survey. Information on CO2Stored is available at www.co2stored.com. This spreadsheet is the appraisal model of Site 7: Bunter Closure 36.

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

Local authority, lower super output area (LSOA), middle super output area (MSOA) and experimental postcode level data on gas consumption. There is also a sub-national electricity and gas consumption statistics analysis tool.

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

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

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

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

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

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

The UK Low Carbon Transition Plan plots how the UK will meet its targets on emissions reduction. Original (archived May 2010) - targetting 34% cut in emissions on 1990 levels by 2020, set out in the 2009 budgetThis publication was published under the 2010 to 2015 Conservative and Liberal Democrat coalition government

First published in December 2011, the Carbon Plan sets out the governments plans for achieving the emissions reductions it committed to in the first 4 carbon budgets.
Emissions in the UK must, by law, be cut by at least 80% of 1990 levels by 2050. The UK was first to set its ambition in law and the Plan sets out progress to date and assesses cost-effective next steps.
Parts 1, 2 and 3 of the report, and Annex A and Annex B set out the governments strategy and fulfil the legal obligation to report on what the UK is doing to ensure it meets carbon budgets set in law.
Annex C sets out, department by department, actions and deadlines for the next 5 years.
Quarterly updates on the implementation of the Carbon Plan are available at
https://www.gov.uk/government/collections/carbon-plan-quarterly-implementation-updates.

The numbers behind the Climate Change Committee's (CCC) sixth carbon budget. The sixth carbon budget provides UK ministers with advice on the volume of greenhouse gases that the UK can emit between 2033 and 2037 and has now been adopted in UK law. Interactive charts are available to explore the data.

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

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

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

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

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

Statistics on the impact of transport on the environment, including greenhouse gas emissions from transport, air quality and electric vehicles, plus new experimental statistics comparing greenhouse gas emissions for individual journeys. This is an annual report, first published in May 2021.

Air pollution forecast and latest measurements and data archive. There are over 1500 sites across the UK that monitor air quality. The data and information made available through on this website is subject to Crown copyright protection unless otherwise indicated.

The UKCCSRC Data and Information Archive holds data and other outputs generated by UKCCSRC and EPSRC-funded projects and other UK CCS projects for the long-term. It aims to provide a national focal point for CCS research and development in order to bring together the user community and academics to analyse problems, devise and carry out world-leading research, and share delivery. All EPSRC-funded projects in carbon storage are expected to archive their supporting data here (data files, reports, presentations, posters, papers, images and educational materials; source code may be included if needed to necessary to validate research findings).

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

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

UKESTO showcases national energy storage innovation, describing energy storage facilities in the UK and providing data from test beds.

In 2012 the Engineering and Physical Sciences Research Council (EPSRC) funded the Energy Storage Capital Grants call, where fifteen institutions received 30m pounds of funding across five consortia for the development and testing of energy storage technologies that span application areas. The consortia leads were the University of Birmingham, Imperial College, Loughborough University, the University of Manchester, and the University of Sheffield.

In 2016 these institutions secured a 4m pound investment from EPSRC to deliver the Multi-scale Analysis for Facilities for Energy Storage (MANIFEST) project, where the UK Energy Storage Observatory is a major deliverable.

Energy trends is a quarterly bulletin containing statistics on all major aspects of energy in the UK. Energy trends focuses on the supply and demand of coal, oil, gas, electricity and renewables in the United Kingdom. Data is published a quarter in arrears.
Previous editions of Energy trends are available from The National Archives.

UK Government annual, quarterly and monthly coal statistics available to download. This page collects together all the UK Government data sources that focus on coal, including historical coal statistics (1853-2012, decadal from 1853, annual from 1913) Brings together coal resources from DUKES (annual data), energy trends (articles, quarterly and monthly data) and historical data. These datasets form part of other dataset collections in UK Government statistics.

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

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

Annual energy projections, analyzing and projecting future energy use and greenhouse gas emissions in the UK to assist in monitoring progress towards meeting carbon budgets for the UK and to inform energy policy and associated analytical work across government departments. The projections are based on assumptions of future economic growth, fossil fuel prices, electricity generation costs, UK population and other key variables regularly updated. They also give an indication of the impact of the uncertainty around some of these input assumptions.
Each year, a PDF report is produced, along with a number of Annexes which are spreadsheets of the tables in the reports.

Annual, quarterly and monthly gas statistics available to download. This page brings together all the UK Government data sources that focus on gas including historic gas production, consumption, and fuel input (1920-2012) and information about European gas flows Brings together gas resources from DUKES (annual data), energy trends (articles, quarterly and monthly data) and historic data.

Annual, quarterly and monthly oil statistics available to download. This page brings together all the UK Government data sources that focus on oil including changes to oil demand data, and crude oil and petroleum production, imports and exports. Includes historical data from 1890 onwards. Brings together oil resources from DUKES (annual data), energy trends (articles, quarterly and monthly data) and historic data.

Green Deal, Energy Company Obligation and Insulation statistics for UK housing. This series presents statistics on the Energy Company Obligation (ECO) and Green Deal (GD). It incorporates changes as set out in response to the user consultation of National Statistics on the Green Deal, Energy Company Obligation and Insulation statistics. The headline releases present monthly updates of ECO measures and quarterly updates of in-depth ECO statistics, carbon savings and the Green Deal schemes. The detailed report presents annual updates on in-depth ECO statistics and insulation levels.
Historical releases are available on request from BEIS.

Historic and projected UK household and population numbers in thousands Three datasets:
UK_households.csv Number of households per year in thousands
UK_population.csv UK population in thousands
UK_population_households.xls Both combined plus calculated number of persons per household
Data developed by the Defra MTP from ODPM (now DCLG) figures, interpolated between 1991 and 2001 to account for 2001 Census data. Population projections in the period 2003 to 2021 have been linearly interpolated from five-years interval projections by UK government. For further information see BNXS25 UK household and population figures, 1970-2020, Version 2.1 (updated 12/1/2007)

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

Quarterly Energy Prices is a quarterly bulletin covering energy prices, to domestic and industrial consumers, for all the major fuels, as well as comparisons of fuel prices in the EU and G7 countries. Previous editions back to December 2010 are available from the National Archive.Issues previous to this are no longer available.

The ETI-funded UKSAP (UK Storage Appraisal Project) provides a fully auditable and defensible overall estimate of UK CO2 storage capacity for CCS in offshore geological formations. <p>The whole UKSAP results have been made available in the CO2 Stored database.</p><p>Most storage reservoirs were modeled as simplified representative structures. Detailed reservoir simulation models known as Exemplar Models were created for two sites, Bunter and Forties. Both were modeled with proprietary geological simulation software Eclipse and Petrel and these models are made available here.</p>

The total final energy consumption data is an aggregation of the electricity, gas, road transport and residual fuels datasets. Statistics provided at regional and local authority level. Please read the Methodology and guidance before using the statistics. Previous editions are available from The National Archive.

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

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

Statistics and breakdown of CO2 emissions across the country, using nationally available data sets going back to 2005. You can access past editions of the statistics via The National Archives.

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

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

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

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

Annual greenhouse gas and carbon dioxide emissions relating to UK consumption. The worldwide production of goods consumed in the UK is taken into account, as well as goods produced in the UK and emissions directly generated by UK households. The data page notes that the data for 1990 to 1996 is included in the spreadsheet, but does not have the same level of confidence as the data from 1997 onwards. Some data are in Open Office ODS format and some in MS Excel format.

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

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

The Public Engagement Observatory of the UK Energy Research Centre (UKERC) maps the many different ways that people are engaging with energy, climate change and net zero on an ongoing basis.It openly shares, experiments with, and undertakes these mappings with others to help make energy and climate-related decisions, innovations and participation more just, responsible and responsive to society. As part of this activity there is an interactive mapping dataset of diverse cases of public participation and engagement with energy, climate change and net zero occurring in the UK since 2010. Here you can explore multiple different cases of public engagement, and filter the case study dataset based on the form, topic, participants and location of engagement. https://ukerc-observatory.ac.uk/mapping/explore/

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

The Knowledge Network is a web-based system which facilitates data exchange in the emerging wave and tidal energy industry. The Knowledge Network contains more than 2000 resources on a range of topics relevant to wave and tidal energy. The resources are of a variety of types, including reports and datasets. The Crown Estate originally developed the Knowledge Network in line with its strategic objective to support growth of the wave and tidal industry and in partnership with the Department of Energy and Climate Change. The WTKN is now managed by the Offshore Renewable Energy Catapult. It is a searchable database containing a wide range of information available to download free of charge and also provides links to information held elsewhere, which may be available on a commercial basis.

UK Government publishes weekly prices for road fuels. The weekly road fuel prices table reports on the cost of unleaded petrol (ULSP) and unleaded diesel (ULSD). Road fuel price statistics providing average UK retail "pump" prices on a weekly basis.

Woodland ecosystem services for England, Scotland, Wales and Northern Ireland, supplementary information. Physical (non-monetary) and monetary estimates of services provided by natural assets in the UK. These data are part of the environmental accounts data set. https://www.ons.gov.uk/economy/environmentalaccounts/datalist?filter=datasets

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

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

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