Optimization and multicriteria evaluation of carbon-neutral heat-only production technologies for district heating in Turin

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. The first part of the thesis analyzes the actual DH system of the cities, scaling it based on the peak power and recreating the case study. After that, a mathematical model to satisfy the heat demand while minimizing the operational cost of the system was built using the software LP2 and to validate the results, it was compared to well-known software EnergyPRO, used in the district heating field. After the analysis of the base case, a scenario analysis was carried out, selecting the best carbon-neutral technologies suitable for the case study. The simulations are re-run to consider stochastic variables as variation of fuel and electricity price and to strengthen the results from the alternatives a correlation matrix was obtained. The output of the first part can be summarized in a matrix that contains mean value and uncertainties for each criterion, and a correlation matrix that relates every alternative. The second stage aims at evaluating the best alternative between the one proposed, using SMAA method, a multicriteria decision method specifically designed to consider imprecise information. Moreover, the analysis considers decision makers preference information, dependencies between the criteria and the alternative and uncertainties related to the criteria measurements. According to preference information provided by decision makers, the most preferred alternative was the introduction of a solar heat plant coupled with an increase of daily storage, that add renewable capacity to the system while cutting the peak load.