In the context of building electrification the operation of distributed energy resources integrating multiple energy carriers poses a significant challenge. Such an operation calls for an energy management system that decides the set-points of the primary control layer in the best way possible. This is done by fulfilling user requirements, minimizing costs, and balancing local generation with energy storage. This last component is what enables building flexibility. This paper presents a novel aging-aware strategy for operating grid-connected buildings that combine multiple energy carriers (heat and electricity), storage devices (electric vehicles, batteries, and thermal storage), and power sources (solar photovoltaics, solar collectors). The novel energy management algorithm presented considers the aging of the batteries to enhance the operational differences between storage technologies, thus making explicit the trade-off between the services provided by the hybrid energy storage system and its degradation. This unlocks grid cost reductions between 20–45 % depending on the season when compared to state-of-the-art solutions.@en

This paper presents a Mix Integer Linear Programming (MILP) optimization approach to reduce peak demand and maximize revenue in a grid-connected building with a PV-equipped charging station for Shared EVs. The study investigates the impact of EV availability on the effectiveness of the system by comparing the results for different connection times of a fleet of Shared EVs, a private EV used for commuting, and a stationary battery. Results from the case study conducted in The Netherlands demonstrate that not only the duration but also the timing of EV connection significantly influence system effectiveness, emphasizing the need for accurate availability estimation. The trade-off between peak reduction and Peak-to-Average Ratio (PAR) reduction is also highlighted, underscoring the importance of considering both factors for optimizing charging station usage. These findings provide valuable insights for optimizing energy management, reducing peak loads, and increasing the utilization of renewable energy sources in the context of Shared EVs and V2G technology. @en