A Novel SW Tool for the Evaluation of Expected Benefits of V2H Charging Devices Utilization in V2B Building Contexts

Energy systems need a complete decarbonization within the next 20–30 years, calling for introduction of CO2-free renewable energy sources (RES). All final uses must face this challenge, now finally including transportation sector which should mostly be electrified. This option could constitute both challenge and an opportunity electric grid. In fact, connection to grid all vehicles (EVs) together with their electricity storage (ESSs) reduce issues due nonprogrammable use RES in production; aim, sufficiently smart bi-directional vehicle-to-grid technologies (V2G) have designed widely installed. Parallelly, capabilities become fully bidirectional nodes, physically terms ICT (so-called paradigm). meanwhile, some those V2G may already locally implemented individual home contexts. Following previous research activity about identification potential users most promising V2H on evaluation expected benefits local auto-consumption and/or consumption auto-feeding performance, author aims his attention numerical further obtainable through combined utilization number acting same “building” node; approach is normally referred literature as vehicle-to-building (V2B) application. The SW tool was developed aim consistent, scalable, modular, open-source, user-friendly, it can distributed under request other groups. simulations performed, devices used controlling approach, but offered services community, defined by instantaneous sum behaviors users. simulation results show that building environments make possible intersect fluxes far beyond single user expectation, leading very performances. particular, ratios higher than 50%, almost fed grid-connected vehicular ESSs (100% ratio). limits building–grid interactions much more predictable residual ESS charging phases, well sale PV panel overproduction. performance simulated V2B proved grids (which were estimated study group), ranging from 25% 69% (with values only “nocturnal workers”, living during daytime); moreover, poor recorded auto-feeding, 27% 81% inhabiting night-time).