Urban energy planning and economic–environmental impacts assessment through spatiotemporal modeling of residential energy consumptions.

There is growing need to understand the ways in which we are using energy in our day to day lives. As urbanization is increasing, there is particular interest in urban and district level energy consumption. In this thesis, current research in the field of district level energy modeling is reviewed. While many models focus on either an analytical or statistical model, the model presented in this thesis is a hybrid spatiotemporal one looking specifically at residential energy demand. The model was applied in a case study of the 3rd district of Turin, Italy. The aim of the thesis was to develop a Geographic Information System (GIS) based hybrid urban buildings energy model as a supportive tool for energy planning and economic-environmental impacts assessment of explorative building retrofit scenarios. The final energy model is focused both on thermal and electrical consumptions. Concerning thermal energy, making use of GIS georeferenced critical data regarding building geometry and construction period, 36 building archetypes are identified and a reference building (RB, associating TABULA thermophysical properties) is defined for each. The analytical model developed is a powerful tool which allows for the calculation of thermal energy demand for reference buildings. An initial calibration of the analytical model was carried out through the use of measured data in parallel with statistical information. The calibrated model was then applied at a district level via application of the specific consumption values to each building in the district. This method provides the opportunity to see exactly where the energy is being consumed. Varied energy efficiency interventions related to the building energy systems and envelope were considered for the generation of retrofit scenarios. Expansion of district heating systems were not considered. It is known that Turin has a well-established plan to expand the district heating system, but the objective of this thesis is to be broadly applicable and to consider a scenario where the interventions are focused on electrification. Electricity consumptions at district level were calculated through a statistical model based on inhabitants’ socio-economic characteristics. With the models established, different penetration rates for the building retrofits were considered and the forecast changes in both thermal and electric demand were applied thus establishing trends through the year 2050. Based on these demands, the greenhouse gas (GHG) emissions and local air pollution reductions were calculated as well as the corresponding savings related to healthcare of local residents. The costs associated with implementing these changes were also determined. Finally, the results were reintegrated in the QGIS model to allow for district level scenarios to be observed. Indeed, spatial visualization of results could be a supportive tool for decision makers. Trafton Introduction| iv Turin is consistently ranked among the worst European cities in terms of air quality. In 2017, the city exceeded the World Health Organization’s (WHO) guideline value for concentration 66 days out of the year. This inspired the consideration of the link between retrofit interventions and local air pollution. Appropriate energy efficiency interventions alone can lead to significant reductions in energy demand. These interventions, along with increases in renewable energy shares of the power generation mix demonstrate that in the residential sector, the greenhouse gas reductions required to mitigate climate change can be obtained at competitive costs.