The main issue addressed in the OASIS project is the environmental impact of road transportation due to air pollution and carbon emissions. The project’s primary objective is to develop a decisional algorithm for optimizing the location and sizing of electric vehicle (EV) charging stations to promote the transition to clean energy sources.
Atlante, a company focused on building an EV fast-charging network in Southern Europe, is the key stakeholder with requirements for an easy-to-use, automated, and revenue-maximizing solution.
The project employs a Geographic Information System (GIS)-based approach, dividing the area into hexagonal cells and assigning suitability scores for charging station installation. Data collection includes traffic data, points of interest (POIs), costs, revenues, and information about existing EV charging stations.
In the testing phase with data from cities like Madrid, Rotterdam, and London, the algorithm successfully balances parameters, identifying high-potential peripheral points and achieving excellent economic performance. Future improvements could include incorporating demographic data and refining the economics of the algorithm to account for price fluctuations in energy and installation costs.
ASP projects