EV charger Location Planning Tool
Client
Co-funded by the EU under the H2020 Research and Innovation Programme
Partners
The problem
Public authorities and private actors are faced with the challenging task to roll out a comprehensive charging infrastructure without the certainty of the specific demand of each area.
eCharge4Drivers improves the Electric-Vehicle charging experience in urban areas and on interurban corridors, making it more convenient for users to go green. The project demonstrates new technologies and services to improve the drivers experience before, during and after charging their electric vehicle.
Mosaic Factor has contributed mainly doing the initial study of user needs and preferences, coordinating the design and description of the requirements of the different services and in the integration and development of the Charging Points Location Planning Tool (LPT) to guarantee the optimum mix of charging options to cover users’ needs.
The solution
eCharge4Drivers substantially improves the EV charging experience within cities and for long trips.
Our Location Planning Tool enables public administrations or private companies to plan future charging infrastructure deployment in the right locations.
The platform integrates the demand and location models to provide a webtool that allows the authorities to enter location-specific data and interact with the tool by adjusting parameters for different simulations.
Technologies:
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- Battery swapping stations for LEV’s
- ISO15118 Plug and Charge
- Multi-outlet V2G-enabled charging stations
- User-friendly and modular high-power charging stations
Services:
- Route Planner
- Booking Service
- Smart Charging
Decision Tools:
- Charging Points Location Planning Tool and pricing for sustainable e-mobility growth
The platform supports local authorities and other stakeholders by producing relevant information on:
forecasted coverage of charging infrastructure towards the needs of users of electric vehicles.
allows to plan the way the forecasted growth of electric vehicle usage will be covered.
required investment budgets, and, thus, it supports in decision-making.
The tool integrates big data analytics using real-time usage data from CPOs, eMSPs and parking operators. It is composed of different elements that are integrated in a web-based, user-friendly tool, accessible to users via a graphical user interface.
Demand model: historical charging data and socio-demographics, mobility and environmental activity indicators provided by different locations (12 countries).
ML algorithm: Regression model fits the data to forecast the expected demand at a location (amount of kWh charged per day).
The demand model uses available geographic and demographic information of a chosen geographical area, including available information on existing charging infrastructure and its usage. Via the user interface, a user can upload information and adjust parameters, such as e.g., the forecasted timeframe to be analysed and the EV stock growth assumptions to be used. With this input, the model then calculates energy demand distributed over the chosen area.
This demand is then further used by the location planning and optimisation algorithm to calculate required future charging point locations.
Data
Data sources we used to design the predictive model include:
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- Geometry of the area and subareas
- Socio-demographic data for each subarea
- Existing charging points
- Planned charging points
- Candidate charging points
- Historic charging sessions data
Results
The tool has been developed and tested towards 3 different locations at different geographical scales:
- country of Luxembourg,
- city of Barcelona,
- and a town in the mountainous Northern Italy (Val Trompia).
By using 3 quite different areas, both in terms of geography, demography, and maturity of electric vehicle usage, we have been able to design a tool that is flexible for replicability to different sorts of locations.
The tool allows city planners and CPOs visualise in a map the optimal location to add new charging points considering the cost and the coverage of the demand studied in each area.
Access the LPT here: https://echarge4drivers.web.app/
Media repercussion to date: https://echarge4drivers.eu/news-events/
