Korem's Data-Driven EV Charging Station Placement

Welcome to our #BuiltWithHERE series, where we showcase how HERE location data and services are used to solve real-world challenges. In this blog post, we highlight how Korem, a leading geospatial data and software provider, offers a valuable tool for anyone considering adding EV charging stations to their location. For electric vehicle (EV) charging station site selection, they serve a wide range of customers – from established charging network operators managing hundreds and thousands of different charging points, such as Volta, Shell, EVGo, to companies installing home EV chargers.

What is EV charging station site selection?

EV charging station site selection is an analytical process of choosing the best locations to install new charging stations. Korem's site selection strategy considers a variety of factors such as:

Traffic patterns: Helps in identifying locations with high demand for charging.
Nearby amenities: Helps in choosing locations that are convenient for EV drivers, such as places they can shop or eat while their car is charging.
Demographics: Helps in identifying who is likely to use the charging stations.
Existing EV charging stations: Helps in considering the existing competition in the area.

Other factors include footfall traffic, the distance travelled by customers to get to these locations, time spent at these locations, and more.

Why is EV charging station site selection crucial?

EV adoption is growing exponentially, but charging stations are struggling to keep up with the pace. A major challenge is determining the right location to install the charging stations. It needs spatial analysis and use of multiple datasets, including property data, demographics, points of interest, foot traffic data, and traffic data. Choosing the wrong location can be costly for the retailers and companies investing in this. It's not just important to know the placement location, but also need to know the future performance, the ideal number of charging ports per site, and the total number of chargers needed. According to Korem, many companies underestimate this complexity.

HERE data is at the core of how we can precisely measure how a site is going to perform.

Korem

HERE APIs and data used

1. HERE Geocoding and Search API v7 (previously HERE Places API)

The first and most important layer is the points of interest. Visitation data is usually extracted from points of interest, retail businesses, or restaurants. With this data, Korem finds how many people are visiting and when they are visiting. This information is then aggregated to the week or month level.

EV Charge Points Add On (previously available with Advanced Places): Korem uses HERE's location data of existing charging stations. This provides crucial insights into the current competitive landscape. These unusual POIs - small, non-building elements - are an important consideration for EV charging infrastructure planning. This data provides both aggregated and detailed information on charging stations. The aggregated array shows connector types and power levels, while the detailed array provides a structured view of the station, its contained EV supply equipment (EVSE) and connectors.

2. HERE Traffic API

Using HERE Traffic Analytics Speed Data and HERE Real-time Traffic APIs, Korem correlates sales data from retailers with the traffic speed data. They use the total traffic count for each road. This allows them to identify high-traffic areas and analyze how changes in traffic flow impact sales. The historic traffic data can be aggregated in 5-minute increments, going back 48 hours, to calculate seasonality, holidays, or weekday vs. weekend patterns.

Korem also cross-references the traffic per hour with EV charging transactions. For example, retailers have information on who uses the chargers, where they live and how many kilowatts they bought. This can be cross-referenced with the traffic intensity and see its correlation. The traffic count is translated into the frequency of charger usage. Assuming 8% of vehicles on the road are electric, they multiply the total time used in hours and determine the total power usage in kilowatt hours. Then the total power usage is multiplied by the electricity rate to obtain the charger revenue forecast. They can then calculate the revenue generated for the store by multiplying the time of use in hours by the average spending rate in store, which is approximately $12.00 an hour per consumer.

And finally, Korem calculates the monthly average for each revenue forecast, and it provides a comprehensive outlook on the expected income from both electricity sales and additional store revenue. Based on vehicular traffic and electricity rate, they calculate the charger revenue for a month and additional store revenue per month too.

3. HERE Isoline Routing v8

Korem uses the HERE Isoline Routing API to identify ideal locations for charging stations. The API is used to calculate drive-time polygons (areas reachable within a specific time) and EV-enabled consumption based polygons (areas reachable by electric vehicle bases on its range). Using these, Korem identifies zones where people can reach with an 8-minute drive by electric vehicles. Existing charging stations inside this polygon are considered competition. Korem uses their in-house normalization techniques on the data to further refine these zones and decide on the optimal trade area for new charging stations.

4. HERE Map Data

Korem also uses the road network from the HERE NavStreets data set to visualize the traffic counts, and the POIs.

The more layers of information we utilize, the fewer aspects are left to chance, and the more angles are covered for each location.

Korem

They also use other datasets such as dwell time or visitation, demographics, and revenues in this analysis. The dwell time insights per POI reveal how much time people spend at each location. Demographics help understand EV ownership in the area, specially using parameters such as age group, income bracket and level of education.

The KPIs on the right are extracted for each site under consideration. All parameters are expressed as indexes. 100 is the benchmark or neutral value. A site with an index above 100 is an overperforming location, and a better option to choose.

In Closing

Korem's EV charging station site selection process uses different HERE location data and APIs such as traffic patterns, nearby amenities, isolines, and existing competition. Korem guides their customers in choosing sites with high utilization that can generate the most revenue. The detailed analysis and forecasting by Korem is helpful for companies looking to strategically expand their EV charging network. Watch Korem’s webinar on EV site selection for more details.