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Projects: Projects for Investigator
Reference Number NIA_NGSO0021
Title Development of GB electric vehicle charging profiles
Status Completed
Energy Categories Other Cross-Cutting Technologies or Research(Energy system analysis) 25%;
Energy Efficiency(Transport) 25%;
Other Power and Storage Technologies(Electricity transmission and distribution) 50%;
Research Types Applied Research and Development 100%
Science and Technology Fields ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100%
UKERC Cross Cutting Characterisation Systems Analysis related to energy R&D (Energy modelling) 100%
Principal Investigator Project Contact
No email address given
National Grid plc
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 December 2018
End Date 01 June 2019
Duration ENA months
Total Grant Value £60,000
Industrial Sectors Power
Region London
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , National Grid plc (100.000%)
  Industrial Collaborator Project Contact , National Grid plc (0.000%)
Web Site https://smarter.energynetworks.org/projects/NIA_NGSO0021
Objectives This project will look to improve demand forecasting for electric vehicles by developing a series of hourly annual profiles reflecting: un-incentivised current electric vehicle charging behaviour without large proportions of “smart-charging” (i.e. a baseline) without the effects of project specific goals potentially skewing the results without observer (Hawthorne) effects potentially distorting the results across different charger sizes (kW) across different location types in GB covering each of the 8,760 hours in a year These profiles will be created from historic charging data from the charger network providers identifying the current pattern of usage by charger type and location type. The project proposes to request charging data from charge point operators. The project will process the charging data and create hourly profiles covering one full year for: a single GB charging profile (regardless of charger size, location type); and a limited number of other chargers varying by location type and charger size. The format of these profiles would show the: deviation away from the annual average for the charger size and location type for each hour within the year (8.760 periods); and percentage utilisation rate by hour for each charger size and location type. This will provide a fuller profile for the demand from chargers across GB and allow this demand to be compared between different geographical regions and charger sizes. The objectives for this projects are as follows: Contact charge point operators regarding data availability and willingness to supply data with the project Collect anonymised charging activity from charge point operators covering a minimum of one full calendar year (same period from each of the networks i.e. 2017-2018) start and end date and time of each charging instance kWh supplied in each charging instance identifying charger size (kW) identifying location type (residential, destination, road-size etc.) Identifying post code district (i.e. first part of the post code e.g. CV34) Analysis of the individual charging data including: cleaning of the data sets provided erroneous data types, formatting, errors, misalignments etc. analysis of the charging data to produce a 8760 hour profile of the charging instances data split by:  hour bar within the year (8760 hours) charge type (kW) charger location (Residential, road-side, destination etc.) proportion of annual charging that occurs at that hour bar (%)  deviation away from the annual average energy (multiplication factor from average). addition split of the above by postcode district (i.e. first part of the post code) if possible.
Abstract There is currently limited public availability of annual Electric Vehicle (EV) charging profiles in Great Britain that are based on actual charger use. This means that currently available charging profiles do not adequately represent EV charging behavior within Great Britain (GB). This project will look to improve demand forecasting for electric vehicles by developing a series of hourly annual profiles
Publications (none)
Final Report (none)
Added to Database 08/11/22