Innovation for smallest mass flow rates
Together with nine partners, Landshut University of Applied Sciences is developing a data-based concept to expand the charging infrastructure for electromobility and relieve the strain on Europe’s traffic and electricity networks. The German Federal Ministry of Digital Affairs and Transport is funding the project with a total of almost 4.2 million euros.
The expansion of electromobility and the necessary charging infrastructure is one of the European Union’s core objectives. Fast charging and network stability are the main issues here. The concepts for this require comprehensive data, on the basis of which the effects on grid stability, sustainability and the potential for optimization can be assessed. However, since hardly any studies have been carried out on this so far, the data situation is very limited. This is where the new Open Mobility Electric Infrastructure (OMEI) research project led by Landshut University of Applied Sciences comes in.
The project team, which consists of a total of ten institutions and companies, wants to create a freely available data basis for planning a sustainable, regional charging infrastructure and evaluating concepts for the intelligent use of e-vehicles. Based on this, the consortium will also develop optimal ecological, economic and technical solutions for charging infrastructures in the European transport network that combine regional renewable energies with sustainable energy storage. The consortium thus aims to create a data-based concept transferable to Europe on how electromobility can be expanded sustainably and economically. The German Federal Ministry of Digital Affairs and Transport is funding the project with a total of almost 4.2 million euros.
Strain on European transport networks
“The necessary expansion of electric charging infrastructure is placing an enormous burden on European transport and electricity networks; to meet the power demand, we need fast-charging systems on the main transport routes throughout Europe.”
– Prof. Dr. Karl-Heinz Pettinger, Scientific Director at the Energy Technology Center
Such a grid expansion, however, is very resource-intensive, he said. Therefore, it is important to create sustainable and grid-friendly charging infrastructures and to use more regional renewable energies for this purpose.
Intelligent charging infrastructure with the help of AI
The researchers therefore want to collect charging, user, energy and traffic data as a first step in order to calculate the effects of a smart charging infrastructure on the energy transition. To this end, the team is setting up demonstration facilities in two model regions along a major European arterial road (e.g., along the A3 highway) that combine a fast-charging station with a hybrid energy storage system. This would allow more regional energy to be used to charge e-cars, with the energy storage serving as a power buffer.
This would put less strain on the European supply network and save costs in expanding supraregional charging infrastructure. In addition, the team is planning a third end-user facility that is bidirectional, meaning e-cars can be both charged and discharged. “In this vehicle-to-home variant, we want to use the potential of the available storage capacities of the stationary vehicles and thus develop grid-based charging or discharging scenarios with the help of artificial intelligence,” Prof. Pettinger said. The team’s goal is to ultimately present a holistic concept for a sustainable charging infrastructure with the help of these two approaches.
Taking the topic into society
For example, the scientists use the collected data to create simulation models in order to develop and optimize location-independent and economical operating strategies. The generated data will eventually be made accessible via open data portals. In addition, the consortium wants to take the topic into society through active citizen participation in order to generate acceptance for necessary changes. The results will therefore be published transparently in a user app.
Close cooperation of the consortium
In order to be able to implement the project as planned, the project partners are working together in close exchange: While the battery manufacturers JB, FENECON as well as the charging station operator MER are responsible for the construction and operation of the energy storage systems and fast charging stations, respectively, the TZE together with HEITEC develops the system design as well as the operating strategies of the charging infrastructure and the energy storage systems. In addition, the TZE, together with the University of Passau, is responsible for the simulation models and tests the vehicle-to-home applications. Dr. Gerl, the scientific project coordinator for the Chair of Distributed Information Systems, emphasizes that “only with an extensive and sustainably available database can it be possible to develop AI-based system simulations and optimizations for electric charging infrastructures in Europe. This is the focus of our subproject.”
The company Technagon is developing a bidirectional wallbox for vehicle-to-home applications with coordination of the technical requirements. TZE, IL and Technagon validate and test this application at the respective locations and test vehicles. Based on power grid and smart meter data, provided by EVG Perlesreut eG, these operating strategies will be validated and optimized for V2G applications. Finally, an operating concept for vehicle storage (V2G/V2H) will be developed in the consortium.
Sustainable energy supply for e-mobility
In the end, the project should help to expand electromobility, avoid grid congestion and enable citizens to use electric drives in a sustainable way. Prof. Kosch and Prof. Sauer together emphasize the project’s technological innovation. “The data-based optimization of the electric charging infrastructure as well as the realization of vehicle-to-home and vehicle-to-grid concepts in Bavaria is an important milestone for the future-capable sustainable mobility system in Germany,” Prof. Kosch elaborates. Prof. Sauer adds that “the use of AI methods to increase energy efficiency in vehicle-to-home networking has a very high potential, and the project results will be very relevant for the regional energy ecosystem.” “It is important to us to ensure a sustainable energy supply for electric mobility,” says Prof. Pettinger, “thus reducing the carbon footprint of each e-vehicle.”