Assessment of building stock impact on global energy system optimization

This project falls within the framework of a Master Thesis at the Industrial Processes and Energy Systems Engineering (IPESE) laboratory of Ecole Polytechnique Fédérale de Lausanne (EPFL). With the aim of assessing the building stock impact on global energy system and its sensitivity to renovation and climatic conditions, a tool is designed from three models of energy system, each having a particular scope and interesting potential contribution to the project. The objective is to make it as automatized, independent and adaptable as possible in order to allow any individual working on one of these models to integrate the approach, use different inputs and methods and easily generate results for various conditions. The tool takes as input a building stock clustering and characterization (Paul Stadler’s Database (PSD)) that allows to scale up to the national level the results from individual buildings optimization, performed with a second model (Smart Building Designer (SBD)) under several scenarios and conditions. The resulting options are then integrated into a global energy system optimization model (EnergyScope (ES)). It is then applied to a pre-defined specific case study of Switzerland in 2050 to generate and analyze results under several conditions, in order to understand the building stock behavior and impact within national energy system optimization. The separate optimization of the building stock, even though limiting the flexibility of the global energy system optimization, allows not only to assess its considerable impact on the national system, but also highlights conflicts of interest between the different scopes as well as the importance of the definition of the different costs. Indeed, the resources costs appear to have a significant impact on the resulting expenditures, emissions and energy mix, but the consideration of the different layers and scales, from individuals to intermediaries, private/public companies and governments, is also crucial. The building stock granularity per typical buildings and geographical regions allows to grasp examples of such disparities, as well as the impact of climatic conditions variation, on the different regions, the total building stock and the national energy system. It also allows the integration of a renovation option, which is analyzed as well and appears to have very little impact on the total building stock. Several sensitivity analysis are performed to assess the considerable impact of resourcespecific costs and carbon emissions, as well as the use of several scenario options for the integration of the building stock in the global energy system with a reasonable impact on the computational time. In the end, the designed tool allows to generate various results to address the research questions and better understand the behavior and impact of building stock within global energy system optimization. And it also leaves room for later improvement such as consideration of district interaction during the separate building stock optimization, or a deeper analysis on climate change with the addition of cooling technologies.