Analysis of Consumption Forecasting and Flexibility Utilization of an Electric Vehicle Fleet in the OPENTUNITY Project

The mobility sector is undergoing a transformation as electric vehicles (EVs) gradually replace traditional internal combustion engines. This transition is strongly supported by key European Union policies, including the ban on sales of new CO₂-emitting vehicles by 2035. In this evolving landscape, Avantcar’s electric vehicle-sharing service has become an attractive and sustainable alternative to vehicle ownership for over 50,000 users. However, the full potential of their EV fleet remains untapped, particularly in the area of energy management and, consequently, operational efficiency. New mobility infrastructure, encompassing vehicles and charging stations, presents significant additional potential in the energy sector. By forecasting consumption and utilizing the flexibility of the EV fleet, fleet managers can optimize operations, contribute to grid stability, and actively support the green transition. The OPENTUNITY project, funded by Horizon Europe, aims to support energy stakeholders, including grid operators and active consumers, using innovative methodologies and advanced, interoperable software. Part of the project focuses on leveraging flexibility from various sources, including the EV fleet. As part of this, charging stations have been integrated into an aggregation platform, and the collected data have been used for analysis, identifying consumption patterns at both individual charging locations and fleet levels. This was followed by data cleaning and preparation, and machine learning models were trained for consumption forecasting. Based on the analysis, algorithms for flexibility determination were defined. This paper presents a comprehensive analysis of the charging station data, covering the applied methodologies—from data cleaning and preparation to advanced time series forecasting methods—and the results from the predictive models used.