Earlier this year, UK Power Networks launched the innovation competition “Charge Challenge”, calling everyone across data enthusiasts to trained data specialists to predict future Electric Vehicle uptake, to enable companies to better plan where future charging infrastructure will be required.
Our Senior Location Intelligence Analyst, Alice, took upon this challenge; using a combination of open-source data and the DNO’s Distribution Future Energy Scenarios (DFES) data, and utilising Emu’s mapping solutions Location Insights Explorer to visualise the predicted scenarios and allow for easy exploration of the results.
This 5-page report shares insights on how to promote EV uptake through geospatial data-driven technology:
To best demonstrate the power of data-driven approaches and to attain the most valuable insights; Alice drew from the goals of the Green Agenda in Cambridge to develop a robust charging infrastructure to promote EV adoption in Chelmsford. These two places are both promising and pose interesting challenges to ensure future EV uptake.
Because of the limitations of census data, previous strategies struggled to account for the intricacies of individual areas. By incorporating data on an LSOA level Alice identified early adopters’ profiles more easily on a detailed level. Alice analysed the conditions for early adopter of electric vehicles to account what conditions would be necessary to foster to enable a successful transition.
Next to individual characteristic such as income, house price, education and employment level, broader conditions such as off-street parking availability, walking distance to chargers and charging speed can be juxtaposed and studied together with our Location Insights Explorer to determine where to locate public charging infrastructure.