A Dynamic Prediction Tool for Vehicle-to-Grid Operation and Planning
Babak Ravanbach (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
Elif Turhan (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
Niklas Wulff (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
S. Orfanoudakis (TU Delft - Intelligent Electrical Power Grids)
P.P. Vergara (TU Delft - Intelligent Electrical Power Grids)
Vahid Vahidinasab (Nottingham Trent University)
Luiz Dias (EDP – Energias de Portugal)
G Mendes (Lappeenranta University of Technology)
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Abstract
Under new EU regulation, as of 2035 all new cars and vans registered in the EU are set to be zero-emission. This ambitious target will be an important driver for a large-scale rollout of e-mobility across European cities. To ensure the successful planning of the energy infrastructure and optimized operation of the expanding e-mobility systems, smart and robust tools will be in high demand for various stakeholders, such as industry, city planners, or researchers. As part of the EU-funded research and innovation project DriVe2X, an interactive open-source prediction tool for Vehicle-to-Grid (V2G) operation and planning has been conceptualized and is under development. The main functions of this tool are the prediction of energy balance and flexibility at the public charging station level for a day-ahead operation and providing useful customized analytics for long-term planning purposes.