Schnidrig, JonasTerrier, CédricMaréchal, FrançoisChuat, Arthur2022-11-252022-11-252022-11-252022-06-20https://infoscience.epfl.ch/handle/20.500.14299/192753A proper assessment of technologies’ impact on energy consumption and GHG emissions is essential for designing an effective energy transition. In this regard, the modeling of an energy system is a great resource to identify valuable technologies. This paper falls within a larger project that aims to optimize a national scale energy system based on two encapsulated subsystems (building and district scale). The following paper presents a framework to identify typical configurations of a district energy system. The framework is composed of a two-step GSA. The first step identifies the most influential parameters on the model output using Morris method. The second allows to obtain a representative sampling of the global solution space using the variance-based Sobol method. The GSA suggests that the sensitivity of the model comes primarily from energy carrier tariffs, while the investment cost and other technology properties weigh little in the model output. Furthermore, the space of optimal district was clustered using multiple techniques. The most coherent results were obtained with a DBSCAN which allowed to identify 10 different typical configurations. The configurations heat supply is either based on electricity, using HP and electrical heater, or on NG boilers. Regarding the electricity needs, the supply strategy is identical for all configurations. They rely on a combination of PV panels and imported electricity. Finally, the HP and the water tank are coupled in all electric configurations to furnish heat where NG boilers do not require storage unit.Energy systemRenewable energy hubdistrictStochastic optimizationMorrisMonte Carlostudent work::semester or other student projects