Bernhard Schätz

The evolution of the electricity grid towards the smart grid paradigm is fostering the integration of distributed renewable energy sources in smart buildings: a combination of local power generation, battery storage and controllable loads can greatly increase the energetic self-sufficiency of a smart building, enabling it to maximize the self-consumption of photovoltaic electricity and to participate in the energy market, thus taking advantage of time-variable tariffs to achieve economic savings. This paper proposes an energy management infrastructure specifically tailored for a smart office building, which relies on measured data and on forecasting algorithms to predict the future patterns of both local energy generation and power loads. The performance is compared to the optimal energy usage scheduling, which would be obtained assuming the exact knowledge of the future energy production and consumption trends, showing gaps below 10% with respect to the optimum.

In domains like automotive, safety-critical features are increasingly realized by software. Some features might even require fail-operational behavior, so that they must be provided even in the presence of random hardware failures. A new fault-tolerant SW/HW architecture for electric vehicles provides inherent safety capabilities that enable fail-operational features. In this paper we introduce a formal model of this architecture and an approach to calculate valid deployments of mixed-critical software-components to the execution nodes, while ensuring fail-operational behavior of certain components. Calculated redeployments cover the cases in which faulty execution nodes have to be isolated. This allows to formally analyze which set of features can be provided under decreasing available execution resources.