Dive into our datasets – Mel Abraham

Comment by Mel Abraham, Impact & Business Insight Manager at Energy Systems Catapult.

One of the Energy Digitalisation Taskforce recommendations was to increase the amount of open data that organisations make available, to help spur innovation. Building on that recommendation we would like to introduce you to some of the datasets we have published over the last 12 months. If you have used any of them, we would love to hear what for – please email me on mel.abraham@es.catapult.org.uk

Mapping & Predicting Energy Production and Usage

Future Hydrogen Production Sites

We have produced a list of proposed hydrogen production facilities around the UK. There are currently 78 sites, and we have included as much detail as possible. Here are where the green hydrogen sites might be located:

Proposed green hydrogen sites

Proposed green hydrogen sites

UK biomass, energy from waste, coal and combined cycle gas turbines in the Bioenergy Value Chain Model database

The Bioenergy Value Chain Model (BVCM) is a national scale modelling toolkit for bioenergy in the UK to 2050. This data set contains locations, capacities, and other information on current UK power generation technologies as are represented in BVCM.

Locations, capacities, and other information on current UK power generation technologies

Locations, capacities, and other information on current UK power generation technologies

2032 United Kingdom Energy System Forecasts

For one of our projects, we brought together a set of forecasts for aspects of the UK Energy System in 2032, with separate values for Great Britain and Northern Ireland. The forecasts are based on projections produced by other organisations in the sector, supplemented by the Catapult’s analysis.

There are datasets of half-hourly forecasts for the Greenhouse Gas Intensity, Wholesale Energy Costs, and Network Costs (transmission and distribution) for various energy sources in the year 2032, for multiple scenarios. The data includes Grid Electricity, Grid Gas, and other fuels. The Grid Electricity dataset also contains forecasts for the value of national and local flexibility services.

Measuring the Consumer Response to the Energy Crisis

With energy prices soaring into Autumn 22, lots of policy makers wondered how consumers would respond. Using 36 homes from our Living Lab, we examined what differences we could see across the years. We published some analysis showing people were keeping their homes 0.6⁰C cooler than the previous year. Now the data is available for you to investigate yourselves.

Electrification of Heat & Running Vehicles

Electrification of heat (Property Design & Installation Information, Interim Heat Pump Performance Data Summary)

The Electrification of Heat (EoH) demonstration project is funded by DESNZ (formerly BEIS) and seeks to better understand the feasibility of a large-scale roll-out of heat pumps in homes across the UK.

The project has installed 742 heat pumps in a wide range of property types and ages. Data on the participant, the home and the heat pump can be found within the Property, Design & Installation Information dataset.

All of the heat pumps have been monitored since installation and a summary of the heat pump performance can be found in the Interim Heat Pump Performance Data Summary dataset.

Over the trial, the temperatures went down to a chilly -12⁰C… Interested to know how well the heat pumps managed? You can dive into the data!

Additional 2-minute granularity data is also published open-source, this can be accessed via the UK Data Archive.

HED archetypes library

Home Energy Dynamics is a tool we use to model how new technologies will work in people’s homes, to help us understand how decarbonising domestic buildings will help us get to Net Zero. Every home is different, so we have a set of archetypes to represent the UK housing stock that covers everything from Victorian terraces to modern flats.

You have to request access to this one, but it’s free. Please contact Carl.Holland@es.catapult.org.uk.

Electric Vehicle Charging Profiles

This data is based upon real world vehicle journeys captured in the Department for Transport’s National Travel Survey. Within this survey, families maintain a travel diary for 7 days which contains information about all car journeys completed by the family. Data collected over 8 years for a total of 67,848 vehicles, was used in the analysis around EV charging.

Would you have guessed that the lowest power demand at a work-place chargers is during the week and not at the weekend?

Electric Vehicle Energy Taskforce (EVET) Drivers For Success 2035, Modelling Assumptions

The EV Energy Taskforce’s (EVET) Charging the Future: Drivers for Success 2035 report, published March 2022, made a number of assumptions. We have gathered them together here. The data covers assumptions around:

  • End Users
  • Chargepoints
  • Vehicles
  • Electricity Networks
  • Other supporting assumptions

For example, we used the average miles per trip as 10.9, but we also ran sensitivity on 7.1 miles per trip to see how that would affect the network.

If you want to build on the EVET work, or work out alternative scenarios, the data is here to be used.

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