The development of electric mobility offers new perspectives in the energy sector and improves resource efficiency and sustainability. This paper proposes a new strategy for synchronizing the energy requirements of home, commercial, and vehicle mobility, with a focus on the batteries of electric cars. In particular, this paper describes the coordination between a battery management algorithm that optimally assigns its capacity so that at least a part is reserved for mobility and a vehicle-to-building (V2B) service algorithm that uses a share of EV battery energy to improve user participation in renewable energy exploitation at home and at work. The system offers the user the choice of always maintaining a minimum charge for mobility or providing more flexible use of energy for business needs while maintaining established vehicle autonomy. Suitable management at home and at work allows always charging the vehicle to the required level of charge with renewable power excess, highlighting how the cooperation of home and work charging may provide novel frameworks for a smarter and more sustainable integration of electric mobility, reducing energy consumption and providing more effective energy management. The effectiveness of the proposed solution is demonstrated in a realistic configuration with real data and an experimental setup.

Increasing attention to sustainable energy solutions has rekindled the focus on microgrids integrated with Vehicle-to-Building (V2B) technologies, which enable bidirectional energy exchange between electric vehicles and the building grid. This paper presents a model for optimizing energy exchange in the LAMBDA lab's microgrid, consisting of photovoltaic panels, an energy storage system and a V2B-enabled charging station. After a short review of the state of the art on V2B, including operating principles and practical applications, an innovative algorithm was developed, specifically designed to optimize building's energy flows, with the target of increasing its efficiency and promoting its energy self-sufficiency. The microgrid is managed by a Programmable Logic Controller (PLC) with the suggested algorithm implemented in a Python model, under different operational scenarios. The simulations use realistic PV generation and consumption profiles of lab loads, randomly varying vehicle parameters such as parking duration and charge levels. The paper ends with a real implementation of the algorithm on the microgrid, analysis of the results obtained, highlighting opportunities for improving the model.