Optimal operation of sector-coupled energy communities leveraging plug-in electric vehicle flexibility under different PV installation scenarios

Integrated Local Energy Communities (ILECs) may collectively operate renewable generation, combined heat and power (CHP) units, heat pumps, storage systems, and plug-in electric vehicles (PEVs) to meet multi-energy demands, thereby enabling sector coupling at the local level. PEVs can operate as loads in grid-to-vehicle (G2V) mode and as distributed storage via vehicle-to-grid (V2G) technology, improving economic and environmental performance by coordinated scheduling. This paper proposes a multi-objective optimization framework for the optimal operation of sector-coupled ILECs, where PEVs are explicitly modeled as a flexible resource in the community energy balance. The formulation is based on mixed-integer linear programming (MILP) and uses a weighted-sum approach to simultaneously minimize daily operating costs and CO₂ emissions. The model includes a detailed representation of CHP units, boilers, heat pumps, thermal and electrical storage, and constraints on PEV charging and discharging that are linked to user mobility patterns and grid import/export tariffs. Sector coupling is captured through power-to-heat interactions and PV-to-load/PEV allocation, while time coupling is represented via state-of-charge dynamics of stationary and mobile storage. The framework is applied to an ILEC serving 100 apartments in Torino (Italy) under different PV penetration levels and PEV numbers. Results demonstrate that doubling the PV surface from 700 m² to 1400 m² reduces daily operating costs by 12% and CO₂ emissions by 11%. Doubling the number of PEVs from 15 to 30 lowers the minimum daily operating cost to €200 under cost-optimal operation and the minimum daily emissions to 814 kgCO₂ under emission-optimal operation, corresponding to reductions of 53% and 44% with respect to the reference scenario. Under economic optimization, PEVs primarily provide V2G energy during peak-price hours, whereas under environmental optimization, they prioritize vehicle-to-ILEC self-consumption. In addition, the economic feasibility analysis confirms that, despite the additional capital investment, expanding the PV surface from 700 m² to 1400 m² yields a lower total daily cost under both optimization weights.