Who are the 5% of EV drivers that are commanding all the attention?
Posted on September 27th by Field Dynamics
Posted on September 27th by Field Dynamics
Delivering public EV infrastructure is difficult because there are many unknowns. The market changes quickly, yet infrastructure needs to be in place for many years, so it’s easy to get caught out. Despite these unknowns, a clearer view of drivers needs are emerging. Drivers without a drive (On-Street drivers), will need to park on the street and get their charge from the public network, either Nearby (close enough to walk home) or at a Destination.
There has already been significant investment in both of these charging types, but it hasn’t been clear how many drivers will be dependent on each type until now. Following work with a number of local authorities we have built up a view of the distribution of different EV drivers and their demands in the short to medium term. What has been surprising is the clear difference in sizing of groups, and how little this stark disparity appears to be driving the shape of infrastructure spend.
Broadly speaking, there are two key variables that define residential EV driver groups – Annual Mileage and On/Off street parking. This results in four core groups across EV Charging personas which drive adoption, core behaviours and patterns of usage.
What makes these groupings really interesting is that they are not evenly distributed. High milers only account for around 1 in 6 of the national fleet, and On-Street Households make up just over a third of all households. Therefore, Frequent Chargers only make up the smaller part of the smallest part. This part can be a very small percentage perhaps less than 5% , but this is the group that often gets the most attention and investment from local authorities.
As an example of this imbalance, we picked a representative district council that reflects the national averages; Ipswich Borough Council, and ran the numbers…
Ipswich is a typical area with an On-street percentage of households of 36% (vs 34.8 % national average) and a good mix of demographics. The borough has a population of 137,913, living in 59,850 households and an estimated fleet of 75,345 cars and vans.
Having evaluated a number of adoption curves, most councils we know are planning for the future using the National Grid’s Future Energy Scenarios (1) . If we use their System Transformation curve, we would expect an adoption rate of 14.8% by 2030 – assuming BEV availability etc. This would mean 11,151 BEV’s would need to be accommodated in the borough by that date, but these would not be evenly distributed across our groups because of two key assumptions. It is reasonable to assume that;
Households with off-street parking are likely to adopt faster than those without, who find EV ownership less convenient. This matters because the Off-Street owners are already the bigger part of the bigger group, and are adopting faster.
It is also reasonable to assume that those reliant on high mileages, around 1 in 6 of the fleet, are likely to adopt at a slower rate than those who drive less miles. The process of remote ‘refuelling’ for petrol vs electric is likely to deter many high mileage drivers. So, the smaller part of the group is now adopting more slowly.
Combining these two factors magnifies the differences in an already uneven group of vehicles and drivers.
If we take the fleet of Ipswich and apply these assumptions, balancing the percentages to bring the total to the prediction of 11,151 we get the chart below. While the difference in adoption rates between the groups is low, the impact and contribution is very different.
Clearly this is a model, and we could flex the adoption rates further, but what is interesting is that the overall effect tends to be very consistent.
Across our ULEV Strategy project work these distributions have ended up very consistent across a mix of different types of local authority client.
Despite some exceptions (e.g. very dense urban environments) and putting accessibility challenges or visitors to one side, these ratios do provide a good indication of where most local authorities should expect residential demand to come from in the short to medium term.
In summary, if these numbers are representative of demand, they should also be guiding where the greatest effort in partnerships and investment are made at a local level.
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