Achieving net zero goals by 2050 is driving an energy transition towards clean electrical energy. Consequently, many initiatives have been proposed aiming to reduce carbon emissions in the building and transportation sectors, focusing, for instance, on the implementation of efficient heating and cooling systems based on heat pumps and the use of electric planes. Microgrids can effectively integrate thermal and electrical energy resources and loads to satisfy customer demands while providing technical, economic, and environmental benefits. Thus, this paper proposes the implementation of a model of a hangar microgrid and its Energy Management System to optimize the dispatch of resources of such thermo-electrical airport grid, using a Model Predictive Control approach to address uncertainties, and including a detailed building thermal model, heat pump modeling for the heating and cooling systems, and battery degradation. The proposed mathematical model of the Energy Management System is applied to a model of a microgrid being developed for a hangar at the Waterloo Wellington Flight Centre in Ontario, Canada, taking into account the specific characteristics of the microgrid's components, the expected energy consumption of the equipment and the electric plane used for pilot training based on field measurements, and multi-room temperature control requirements, seeking to ensure a reliable and cost-effective operation, while considering the occupants' comfort in different spaces. The results indicate that the proposed Energy Management System model, featuring multi-room temperature control through multiple thermal resources, can achieve significant savings in operational costs and CO2 emissions compared to a scenario where the microgrid is not deployed and another where a single-room building thermal model with a single heat pump is included.

One of the pivotal strategies for achieving net-zero aviation emissions is the replacement of conventional jet fuel with Sustainable Aviation Fuels (SAF). The very limited availability of SAF necessitates strategic allocation to flight routes to optimize costs and emission reduction. Addressing this challenge, this paper introduces an innovative adaptive robust optimization framework for the distribution of SAF to flight routes in Canada based on a range of domestic production scenarios, fuel transportation costs, and jurisdictional carbon prices. The objective is to identify the optimal location of potential SAF distribution centers and allocate SAF to flight routes over a 25-year period. This complex problem incorporates flight data from the International Civil Aviation Organization (ICAO) and uncertain projections for SAF production. Leveraging a column and constraint algorithm, the paper achieves global optimality in solving the problem. The findings reveal using the proposed robust model leads to a 8.06% decrease in emission cost, compared to the deterministic model, with an optimized SAF supply chain for Canadian domestic flights. This underscores the effectiveness of the proposed approach in efficiently distributing the available SAF under uncertainties of SAF production.