Parked electric vehicles (EVs) are a promising resource for storing fluctuating renewable energy. Smart bidirectional charging (SBC) – the exchange of relevant information via data connections between the vehicle, charging station, and the local energy network – opens up the possibility in this context to control the entire network locally, so that by using the vehicle battery, on the one hand, peak loads at the consumer level (and indirectly at the conventional energy generation level) can be avoided, and on the other hand, „surplus, available“ renewable energy can be optimally utilized.
Within the scope of DIVERGENT, we are researching decentralized decision-making methods and algorithms to support the intelligent, bidirectional charging of electric vehicles. Both classical decision algorithms and approaches based on Multi-Agent Reinforcement Learning (MARL) and/or other machine learning methods will serve as the basis for researching our decision-making methods. In the context of considering a comprehensive decision basis, DIVERGENT will further address the areas of vehicle usage simulation, EV user behavior modeling, and energy management, in order to realistically and effectively represent and evaluate particularly relevant and crucial stakeholder requirements.
Based on our results, an AC-SBC laboratory demonstrator will be developed, built, and evaluated, simulating the bidirectional energy and data flow between the EV battery, the OBC (On-Board Charger), the automated AC (Alternating Current) charging technology, and the local (household) grid.
In summary, the following results are to be achieved in the course of DIVERGENT:
- Decision-making methods that support bidirectional and dynamic control of the charging profile and, consequently
- optimize the energy consumption patterns of households/buildings equipped with bidirectional chargers and
- Avoid peak loads caused by simultaneous charging and discharging of electric vehicles.
- Methods for estimating battery health status and forecasting remaining battery service life to enable evaluation and prediction of the impacts of bidirectional charging on the battery.
- Development of a laboratory demonstrator for the integration and evaluation of software prototypes for (a) the Electric Vehicle Communication Controller (EVCC) and (b) the Supply Equipment Communication Controller (SECC).
This research project is funded by the Zero Emission Mobility program of the Climate- and Energy funds owned by the Republic of Austria, operated by the Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology.
More information: Zero Emission Mobility | FFG
