The thesis presents a methodology for supporting decision making in the energy field, specifically designed to consider uncertainties and dependencies, from modeling the initial system and alternatives to choosing the best one. The novelty of the approach is that, with respect to the most common multi-criteria decision-making methods, can consider stochastic variables during the analysis. In the thesis, the proposed methodology is applied to Politecnico di Torino university, whose thermal load is satisfied by DH, reproducing the DH system of the city in a smaller scale, with the aim to substitute peak boiler with more sustainable technologies, the analysis will be carried out considering several criteria, including economic, environmental and technical one.