Electric Vehicles Turned Grid Batteries Could Slash Community Energy Costs by Half

Every evening, thousands of electric vehicles roll into driveways and parking lots across Europe, plugging in and quietly waiting for morning. For most of the energy industry, those idle hours represent nothing more than a charging schedule to be managed. For a team of researchers in Italy, they represent something far more valuable: a vast, distributed network of batteries on wheels that could transform how neighborhoods generate, store, and trade energy. A new study published in Energy Reports shows just how much value is hiding in those parked cars, and reveals a surprising tension at the heart of the vehicle-to-grid dream.

The research, led by Amin Barati, Nicola Bianco, Marialaura Di Somma, and Francesco Scognamiglio, focuses on what the authors call integrated local energy communities, or ILECs. These are clusters of buildings that coordinate electricity, heating, cooling, and mobility at the neighborhood level, combining technologies such as combined heat and power units, photovoltaic panels, heat pumps, absorption chillers, batteries, and thermal storage into a single, intelligently managed ecosystem. The European Union has thrown its weight behind this model, with the REPowerEU agenda envisioning one renewable energy community per municipality, and studies suggesting that community membership can cut household energy bills by as much as 30 percent. What has been missing, the researchers argue, is a genuinely rigorous way to operate these communities once electric vehicles enter the picture.

Most previous studies, the team found, treat electric vehicles as simple, time-varying loads, blobs of extra demand that arrive and depart on schedule. Others compress entire fleets into aggregated flexibility proxies that obscure the very constraints that matter most in practice: when a specific car actually parks, how long it stays, what state its battery is in when it arrives, and what minimum charge its owner demands before leaving. The new framework takes a fundamentally different approach. Vehicles are grouped into clusters defined by battery capacity, arrival and departure times, and state-of-charge requirements, and each cluster becomes an explicit decision variable in a mixed-integer linear programming model that simultaneously optimizes the flow of electricity, heat, and cooling across the entire community.

The mathematical machinery behind the study is substantial. The model tracks the gas consumption and electrical output of a 250-kilowatt combined heat and power unit, the thermal contribution of a 600-kilowatt auxiliary boiler, the behavior of a 540-kilowatt heat pump operating in both heating and cooling modes, and the charge-discharge cycles of a 600-kilowatt-hour battery alongside thermal storage tanks. Photovoltaic generation is calculated from hourly solar irradiance data for Turin, and electricity prices are drawn from the Italian wholesale market for January 2025, with export prices conservatively assumed at half the purchase price. Crucially, the vehicles themselves can operate bidirectionally, charging from the community in grid-to-vehicle mode or discharging back in vehicle-to-grid mode, with their state of charge constrained between 20 and 80 percent of capacity and a guaranteed minimum of 80 percent at departure so that no driver is ever stranded.

To resolve the inherent conflict between saving money and saving carbon, the researchers employed a weighted-sum multi-objective approach, sweeping a weight parameter from zero to one to trace out a complete Pareto frontier of optimal trade-offs. At one extreme lies the cheapest possible operation; at the other, the lowest possible emissions; in between, a continuum of compromise strategies. The whole problem is solved with a branch-and-cut algorithm, and the results are benchmarked against a reference scenario in which heat comes entirely from conventional gas boilers and electricity entirely from the national grid, a baseline that costs 421.97 euros per day and emits 1,463.52 kilograms of carbon dioxide on a cold January day in Turin.

The headline findings are striking. Across three photovoltaic configurations ranging from 700 to 1,400 square meters of panels serving a community of 100 apartments and 15 vehicles, the optimized energy community cut operational costs by 45 to 52 percent and carbon dioxide emissions by 41 to 48 percent compared with the reference scenario. Doubling the photovoltaic area from the smallest to the largest configuration delivered a further 12 percent reduction in operating costs and an 11 percent reduction in emissions. An investment analysis confirmed that the transition pays for itself: the daily share of the capital cost of the additional panels, roughly 20.94 euros spread over a 30-year lifetime at a 2 percent discount rate, is more than offset by the operating savings in both economic and environmental optimization modes.

But the most revealing results concern the split personality of the parked electric car. Under pure economic optimization, the energy discharged from vehicle batteries is never used to power the community at all. Instead, every kilowatt-hour flows out to the main grid during high-price hours, generating revenue that drives the community’s daily operating cost down to 203 euros in the largest photovoltaic case. Under pure environmental optimization, the strategy inverts completely: vehicle energy is discharged exclusively for local self-consumption, the combined heat and power unit sits idle, the heat pump draws low-carbon grid electricity to cover the entire thermal load, and nothing is sold back to the grid. The optimization engine, in other words, discovers two fundamentally different roles for the same fleet of cars, and the choice between them depends entirely on what the community values most.

The researchers pushed the analysis further with a scaled-up scenario featuring 30 vehicles and 2,800 square meters of photovoltaics. Here, the economic optimum fell to just over 200 euros per day, with more than 100 euros of that achieved through the sale of vehicle flexibility alone, while the environmental optimum reached 814 kilograms of carbon dioxide. Normalized comparisons showed that doubling the fleet and the solar capacity reduced emission intensity by 3.14 percent, cut the specific energy cost by 11 percent, and lifted the community’s self-sufficiency from roughly 30 percent to over 40 percent. The volume of energy exported from vehicles during high-price hours rose 89 percent, from 280 to 530 kilowatt-hours, while energy discharged for local consumption doubled from 100 to 200 kilowatt-hours.

There is an important caveat, one the authors are careful to acknowledge. Very few electric vehicle models and alternating-current chargers on the market today are actually capable of bidirectional operation, as manufacturers have prioritized direct-current fast charging over vehicle-to-grid functionality. The framework is therefore best understood as a forward-looking assessment of what becomes possible as vehicle-to-grid-ready vehicles and chargers proliferate. It is a roadmap rather than a snapshot, quantifying the flexibility prize that awaits communities willing to invest in the enabling hardware.

The implications stretch well beyond a single neighborhood in Turin. As European cities race to decarbonize heating and transport simultaneously, the study demonstrates that sector coupling at the local level is not merely a theoretical convenience but a quantifiable economic and environmental advantage, and that the humble parked car may be the most underutilized asset in the entire energy transition. The researchers plan to extend the framework to handle uncertainty in solar generation and vehicle mobility patterns, to coordinate multiple communities, and to incorporate detailed battery degradation and maintenance costs. If their projections hold, the future of community energy may be sitting in the parking lot, fully charged and waiting to be asked for help.

Subject of Research: Multi-objective optimization of sector-coupled local energy communities using plug-in electric vehicle flexibility under varying photovoltaic installation scenarios

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

Article References: Barati, A., Bianco, N., Di Somma, M., & Scognamiglio, F. (2026). Optimal operation of sector-coupled energy communities leveraging plug-in electric vehicle flexibility under different PV installation scenarios. Energy Reports, 16, Article 109701. https://doi.org/10.1016/j.egyr.2026.109701

Image Credits: AI Generated

DOI: 10.1016/j.egyr.2026.109701

Keywords: energy communities, vehicle-to-grid, electric vehicles, photovoltaics, sector coupling, mixed-integer linear programming, Pareto optimization, combined heat and power, heat pumps, decarbonization, self-consumption, demand flexibility