Synergies between power-to-vehicle, smart grids and renewable energy communities: Dynamic and thermoeconomic analysis

This study investigates the synergies among renewable energy communities (RECs) powered by photovoltaic (PV) systems, electric storage units, and power-to-vehicle (PtV) strategies within a smart district located in Naples, Southern Italy. The district comprises 60 residential buildings, each equipped with a 36.4 kW rooftop PV system, and a diversified fleet of electric vehicles (EVs), including light EVs – such as e-scooters, e-bikes, electric motorcycles, and ultra-compact city cars – and conventional electric cars. The smart grid also integrates a 5 MWh lithium-ion battery system to enhance renewable electricity self-consumption. The methodology combines real traffic data from the Google Maps Distance Matrix API, representing the travel behavior of commuters, students, and local residents, with dynamic energy simulation. An in-house Python tool was developed to process these data and generate representative traffic curves for different vehicle types. The resulting profiles were incorporated into TRNSYS 18 for dynamic simulation of the entire district. All system components were modeled through detailed, time-dependent representations, while building performance was simulated based on geometric and thermo-physical characteristics of the envelopes and calibrated against measured data. The energy performance of the proposed smart district was compared with that of a conventional one powered by natural gas and grid electricity. Results indicate a 75% reduction in primary energy consumption for transportation when adopting the EV fleet, alongside a moderate increase in overall electricity demand mitigated by the use of light EVs. The economic analysis yields a Simple Payback period (SPB) of seven years for the entire system. Light EVs achieve SPB below three years – except for electric motorcycles, which reach approximately 8 years – while conventional electric cars remain less economically attractive due to higher capital costs. Overall, the findings demonstrate that integrating diverse EV fleets within RECs can significantly enhance energy independence, lower carbon emissions, and improve the economic feasibility of sustainable urban mobility.