As reported in the “Clean energy for all Europeans package” set by the EU, a sustainable transition from fossil fuels towards cleaner energy is necessary to improve the quality of life of citizens and the livability in cities. The exploitation of renewable sources, the improvement of energy performance in buildings and the need for cutting-edge national energy and climate plans represent important and urgent topics to be faced in order to implement the sustainability concept in urban areas. In addition, the spread of polygeneration microgrids and the recent development of energy communities enable a massive installation of renewable power plants, high-performance small-size cogeneration units, and electrical storage systems; moreover, properly designed local energy production systems make it possible to optimize the exploitation of green energy sources and reduce both energy supply costs and emissions. In the present paper, a set of key performance indicators is introduced in order to evaluate and compare different energy communities both from a technical and environmental point of view. The proposed methodology was used in order to assess and compare two sites characterized by the presence of sustainable energy infrastructures: the Savona Campus of the University of Genoa in Italy, where a polygeneration microgrid has been in operation since 2014 and new technologies will be installed in the near future, and the SPEED2030 District, an urban area near the Campus where renewable energy power plants (solar and wind), cogeneration units fed by hydrogen and storage systems are planned to be installed.

Aiming at integrating different energy sectors and exploiting the synergies coming from the interaction of different energy carriers, sector coupling allows for a greater flexibility of the energy system, by increasing renewables’ penetration and reducing carbon emissions. At the local level, sector coupling fits well in the concept of an integrated local energy community (ILEC), where active consumers make common choices for satisfying their energy needs through the optimal management of a set of multi-carrier energy technologies, by achieving better economic and environmental benefits compared to the business-as-usual scenario. This paper discusses the stochastic operation optimization of the smart Savona Campus of the University of Genoa, according to economic and environmental criteria. The campus is treated as an ILEC with two electrically interconnected multi-energy hubs involving technologies such as PV, solar thermal, combined heat and power systems, electric and geothermal heat pumps, absorption chillers, electric and thermal storage. Under this prism, the ILEC can participate in the day-ahead market (DAM) with proper bidding strategies. To assess the renewables’ uncertainties, the roulette wheel method is used to generate an initial set of scenarios for solar irradiance, and the fast forward selection algorithm is then applied to preserve the most representative scenarios, while reducing the computational load of the next optimization phase. A stochastic optimization model is thus formulated through mixed-integer linear programming (MILP), with the aim to optimize the operation strategies of the various technologies in the ILEC, as well as the bidding strategies of the ILECs in the DAM, considering both energy costs and carbon emissions through a multi-objective approach. Case study results show how the optimal bidding strategies of the ILEC on the DAM allow minimizing of the users’ net daily cost, and, as in the case of environmental optimization, the ILEC operates in self-consumption mode. Moreover, in comparison to the current operation strategies, the optimized case allows reduction of the daily net energy cost in a range from 5 to 14%, and the net daily carbon emissions in a range from 6 to 18%.