Recent Additions to the EDC

This data is for academic use only and is by request. The request may need to be approved by Cenex.

The dataset provides insights into current vehicles on the road as well as a range of future projections for the vehicle parc, EVs and emissions. The data tables are as follows.

Current Status - Vehicle Parc: Vehicles within the Local Authority, based on the latest DfT data. Company registered vehicles are allocated to LAs based on Experian data (if filtered to 'Allocated' in column D). This is broken down by vehicle body type and fuel.

Current Status - EVI: Number of public charging devices installed in the LA, based on the latest Zapmap data. Devices are categorised as either 'Low Power' (<50kW) or 'High Power' (>=50kW). The data is shown over time and the geographies change as LAs combine (e.g. Cumberland). They also changed their low/high power threshold from 25kW to 50kW in Oct 2023. The data shows the number of devices (note not connectors).

Projections - Vehicle Parc Projections of the number of vehicles in the LA, broken up by fuel type. Use of Experian demographic data accounts for the propensity to adopt EVs in each LA. Old NEVIS versions are also in this file.

Projections - EVI: Projected publicly accessible charging connectors in the LA required to support the vehicle parc. Use the EVI Power Strategy options to change the blend of device powers. Old NEVIS versions are also in this file. The data shows the number of connectors (note not devices).

Emissions - CO2/NOx/PM: Projected emissions from the vehicle parc in the LA. Values show emissions in tonnes. This is broken down by vehicle body type and fuel. Old NEVIS versions are also in this file.

Emissions - Mitigated Damages: Projected mitigated damages from reducing emissions in the LA. Values are in £000's and the savings are relative to the Low Scenario.

Implementation Benefits: Rough costs to install and operate EVI in the LA, as well as potential revenue. All installations and costs vary, these data should be used as a guide only. Costs do not include DNO connection or upgrade costs.

EAS_RCI_CoCharger.parquet (Early Adopter Index, Residential Charging Index, CoCharger Hosts): Output area level data. No data for NI or Scotland. Early Adopter Index - The Early Adopter Index is based on census data and is a measure of the propensity of residents to adopt electric vehicles. The higher the score, the more likely residents are to adopt EVs Residential Charging Index - The Residential Charging Index is based on census data and dwelling types. It is a measure of the likelihood of residents to require public EVI. CoCharger Hosts - CoCharger hosts have registered for a scheme to enable other EV drivers to use their private chargepoints.

Vauxhall_Electric_Streets_Publish.parquet: Vauxhall data capturing resident requests for public EVI installations. One line per survey response, generalized to postcode centroid.

Overview

The raw SPEN data is available from their Open Data Portal. SPEN publish data for their two coverage areas as separate datasets. SPD (Southern Scotland) can be found here, and SPM (North West England) can be found here.

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Coverage and update rate

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Acknowledgements

The ZapMap Database contains details on public electric vehicle chargepoints in Great Britain. This dataset shows this data aggregated to an MSOA (for England and Wales) and Intermediate Zone (for Scotland) level. For each area, the data shows the total number of public chargepoints broken down by power group (slow, fast, rapid and ultra-rapid) and location category (accommodation, supermarket etc.). This is a dataset owned by ZapMap and the license must agreed to in order to use this data. Individual location data is available on request, please see the 'ZapMap EV Chargepoint Locations' dataset.

The ZapMap Database contains details on public electric vehicle chargepoints in Great Britain. This dataset shows the location of these chargepoints with information on installation date, connector type, location category, operator, power rating and more. This is a dataset owned by ZapMap and the license must agreed to in order to use this data. As part of the licensing agreement, a maximum of 20% of the data can be shared per end user customer. Therefore, a request must be put in for an area of interest and this data will be provided to each user separately.

Overview

Acknowledgements

Overview

The raw NPG data is available from their Open Data Portal.

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Coverage and update rate

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Acknowledgements

Estimates of fuel poverty at the regional level are taken from the main fuel poverty statistics for 2022. Estimates at the sub-regional level are modelled and constrained to regional totals, they should only be used to look at general trends and identify areas of particularly high or low fuel poverty. They should not be used to identify detailed trends over time.

Charging sessions data from Scottish chargepoints from September 2024 through October 2025 supplemented with demographic data provided by the ONS.

Merged Distribution Network Operator (DNO) Source dataset consolidates essential data sourced from various DNOs into a single comprehensive dataset providing a consistent summary of commonly required information, such as voltage, capacity and substation ID.

This annual publication provides a comprehensive view of the latest statistical trends and analysis of fuel poverty in England in 2024. Fuel poverty in England is measured using the Low Income Low Energy Efficiency (LILEE) indicator. Under this indicator, a household is considered to be fuel poor if: they are living in a property with a fuel poverty energy efficiency rating of band D or below and when they spend the required amount to heat their home, they are left with a residual income below the official poverty line.

Synthetic (i.e., computer-generated as opposed to real) monthly electric vehicle charging sessions, and their corresponding weekly charging profiles, for every public chargepoint listed in the national chargepoint database as of November 2024. Note that this is an initial version of this dataset and as such the data values may not be very realistic at this stage. We expect to improve these values over time to make the more realistic.

Overview

The raw UKPN data is available from their Open Data Portal.

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Acknowledgements

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), 1990 to 2023.

Overview

The raw SSEN data is available from their Open Data Portal.

Methodology

Coverage and update rate

Units

Acknowledgements

This is an evidence base of available literature on the impacts of offshore renewable energy developments (fixed-base wind, floating wind, wave and tidal) and the outcomes for marine ecosystem services. The evidence was collated through a systematic search of global primary literature (also known as peer-reviewed or published literature) and UK grey literature regarding the impacts of OWF developments (the scope for including global grey literature was unfeasible). Grey literature refers to multiple types of report or document, and is defined as: "information produced on all levels of government, academia, business and industry in electronic and print formats not controlled by commercial publishing" i.e. where publishing is not the primary activity of the producing body (ICGL, 1997). Data was extracted from each evidence source, for each subject or marine ecosystem component that was impacted by the OWF development, the phase of development, the specific pressure and other relevant information about the wind farm or location. Expert judgement was used to map each piece of evidence for impacts on the marine environment according to CICES (Common International Classification of Ecosystem Services) or MEA (Millenium Ecosystem Assessment) and other published classification systems for ecosystem services (Ryfield et al., 2019; Hooper et al., 2020). The dataset was created to provide a central evidence base of available primary (2002-2025) and grey literature (2012-2022) regarding the impacts of offshore renewable developments (for construction, operational and decommissioning phases) on ecosystem service outcomes in the marine environment. The primary literature represents a global semi-systematic search, while the grey literature is restricted to a semi-systematic search for reports and documents from the UK that relate to offshore wind farms only. The database provides a comprehensive list of available literature on this topic, and it enables the assessment and comparison of the evidence for environmental impacts and ecosystem service outcomes between primary and grey literature sources. This will be critical for marine policy makers when gathering evidence for future developments and advances understanding of the impacts and trade-offs associated with developments and ecosystem services. This database can also be accessed through the ORIES (Offshore Renewable Impacts on Ecosystem Services) decision support tool www.ories.pml.space.

This dataset supersedes an earlier version in our records. It can be found at 554a8785-3f6f-4202-a742-d55708391a0a

A survey was undertaken with UK energy and climate change stakeholders involved in and/or effected by Brexit - it was undertaken as part of the UK Energy Research Centre (UKRC) funded project on 'Brexit and UK Net Zero Energy Policy'. The survey was designed to ascertain views on the implications of Brexit for energy and climate change policy and politics, and to build knowledge about actual effects in practice. There were 83 respondents - from UK government (Westminster and devolved), business (mainly energy industry and finance), think tanks and non-governmental organisations (NGOs), academics researching Brexit, and representatives of EU countries.

Data from the survey was used to inform the analysis underpinning 2 papers: the UK Energy Research Centre (UKERC) policy briefing paper, Brexit Implications for UK Decarbonisation Objectives, and the Policy & Politics journal article, Brexit Implications for Sustainable Energy in the UK.

The programme was funded by UK Research and Innovation (UKRI) under the Industrial Strategy Challenge Fund. Its aim: to work with businesses, communities and academics to explore intelligently joining up energy supply, storage and use at a local and regional level.

We live, work and travel in regions, cites, towns and communities. Yet our energy infrastructure is still very centralised - sending energy one way, from bulk supply points to the networks' edges where we live and work.

This programme asked: what if we could bring together energy supply, storage and use to create energy-smart places, enabled by the latest technologies? Could we balance supply and demand locally, improve flexibility and resilience, save costs and carbon, and create new ways of living with energy?

With £104m of funding from UKRI, the programme funded over 80 projects around the UK, from feasibility studies to large-scale demonstrators.