Electromobility offers an efficient way to replace fossil fuels with renewable electricity. The necessary changes to the public and private infrastructure are associated with considerable costs. In order to enable the power that occurs when charging electric cars, the electrical grid often has to be expanded. With an intelligent load management, these costs could be reduced, which would result in a lower financial burden on the public sector and thus on taxpayers.
The pilot project in Lingenau examines the optimization possibilities of load management in a seven-party residential building. In addition to seven electric cars (EV), the system under consideration includes a 15 kW peak PV system and a battery storage. A weather forecast and user behaviour are also included in the optimization. The recharging of the EVs will be optimized with regard to three different target values: Maximization of the degree of self-sufficiency of the residential complex under grid load limits, maximization of customer satisfaction (charging as early and extensively as possible) under grid load limits, minimization of the maximum grid output while ensuring sufficient customer satisfaction. The project will also investigate which of the uncertain system parameters have the greatest effect on the optimizations.