Infrastructure planning part 1: Influence of sociodemographics on residential EV charging

Matching EV charging infrastructure to customer demand is a pre-requisite to developing a sustainable and commercially viable strategy for local authorities and nationally. In this blog post we will use sociodemographic segmentation to help us find the best locations for residential EV charging points in the city of Coventry.

What is sociodemographic segmentation and why is it useful?
Sociodemographic segmentation puts the population into smaller groups based on similarity, giving us a better picture of customer needs. For instance, it can help understand which customer segments are likely to buy and use EVs, informing the design and roll out of public charging infrastructure.

Our sociodemographic segmentation model divides the population into eight main groups, each with several subgroups that have more specific traits. Vehicle registration data can be used to link them with EV adoption rates.

The data shows that 77% of Battery Electric Vehicle (BEV) registrations in England and Wales are within four of the eight sociodemographic groups. These are the groups that have higher income, education, and environmental awareness, and tend to travel more frequently and longer distances.

Visualising EV demand in Coventry
Using Coventry as exemplar, the shaded areas in Figure 1 show current EV demand with the colour boundaries representing the geospatial presence of the four main sociodemographic groups adopting EVs i.e. confirming that there is a correlation between the two. White areas within the coloured boundaries of these sociodemographic groups are likely to represent latent EV charging demand relevant for forecasting.

Figure 1 Residential EV charging demand with sociodemographic context

Satisfying EV demand
To achieve a commercially viable EV charging infrastructure, it is critical that charge points are deployed in locations that will satisfy significant charging demand and drive utilisation. Charge points in the wrong location can incur a significant expense and loss of profitability.

Local authorities and charge point operators should adopt an evidence-based approach to planning and rolling out charging infrastructure. This should include identifying areas of latent demand that will provide a path of progression to scale up the EV charging network. Sociodemographic data is a key contributor to forecasting this future EV demand.

Evaluating the effectiveness of EV residential infrastructure rollout
Using the mentioned principles, we can evaluate the effectiveness of existing EV infrastructure and its growth potential. Figure 2 illustrates the area covered by the four main sociodemographic groups adopting EVs in orange and the location of current charging infrastructure in Coventry. Only 57% of the EV charging infrastructure is in areas of residential charging demand. Therefore 43% of the charging infrastructure is in locations likely to be underutilised.

Figure 2 Residential charging infrastructure in Coventry with 43% of locations suboptimal

Conclusion
Sociodemographic segmentation is an important aspect in identifying areas of current and future residential EV charging demand. In our next blog, we will illustrate how the demand for on-street residential charging can be derived by adding property and land use data to the model.