Prediction, One of the Key Points in the Development of Electric Vehicles

With the increasing adoption of electromobility, it has become crucial to balance the consumer demand and offer from electric vehicle charging points. To improve end-users’ electromobility experience and access to related services, the NeMO project developed a Hyper-Network of tools and services. As a service, this paper describes the artificial neural network (ANN) models that are built to predict the occupancy statuses of electric vehicle charging points in Barcelona. The models are designed to do both short- and long-term predictions of the next 2 h and next week, respectively, considering the different power levels. We propose to combine similar charging points by behavior with no geolocational information to reduce the computational cost by considering the high number of charging stations in the future.