Sensitivity analysis for hydrogen end-use technologies through Energy System Optimization Models: an application to TEMOA-Italy
This repository includes input data and results of my Master's Thesis.
The increasing global focus on hydrogen as a pivotal means to achieve decarbonization objectives prompts a critical inquiry into its future economic viability. Addressing this uncertainty necessitates using powerful analytical instruments, among which Energy System Optimization Models. Given the foundation of such models on the detailed techno-economic characterization of technologies composing the energy system, they are inherently data-driven and possibly subject to a notable degree of uncertainty concerning input parameters and, consequently, output results. For this reason, sensitivity analysis is commonly used to assess the robustness of the technology characterization. The objective of this thesis is to evaluate the sensitivity to some key parameters of the possible future hydrogen end-use technologies penetration in the energy system, according to alternative scenarios. The study is focused on the TEMOA-Italy model, an energy system model based on the open-source platform TEMOA and developed by MAHTEP Group at PoliTO. A comprehensive description of each subsector under investigation is presented, highlighting notable updates in the technological characterizations with respect to the previous version of the model. A technique based on the "one at a time" sensitivity analysis method is implemented to examine a spectrum of transportation and industrial technologies, including fuel cell vehicles, hydrogen-powered aircraft, and hydrogen-based direct reduction of iron for steel production. The sensitivity analysis in this study focused on two crucial parameters: technology efficiency and investment cost. These parameters were selected due to their significant influence on model optimization process. The analysis was conducted within the context of a decarbonization scenario. The results of the analysis highlighted the heavy-duty and automotive sectors as the most sensitive to the characterization of end-use technologies. Additionally, the aviation sector displayed a high degree of dependence on the carbon dioxide storage capacity of the model. In general, the analysis indicated that the model exhibited greater sensitivity to changes in efficiency rather than variations in investment costs.
The developing team wishes to receive help form the users in the definition and test of new test cases, in the benchmark against other established software, in the inclusion of other functionalities. To contribute please refer to contribution.
The developing team agreed to embrace the 
TEMOA-Italy is licensed under 