The Human Element: Integrating socio-economic variables in physics-based energy demand models

By Krijn Horstmanshoff

Abstract
Housing is one of the largest contributors to CO2 emissions. Currently, the average household uses 21% of their CO2 emissions for their heating needs. For policy-making, it is therefore crucial to develop strategies to reduce these emissions. In order to develop such strategies, access to accurate information on where energy is used is vital. Energy demand models can help provide this information. However, in existing research a strong dichotomy exists between physics-based models, that primarily focus on the thermodynamics of buildings, and socio-economic models, that primarily focus on the people that live in the buildings. This division results in a degree of unexplained variation in model predictions. This thesis aims to incorporate socio-economic principles into a physics-based energy demand model. Results do not show a significant improvement in model performance. This is possibly due to the fact that socio-economic data is only available at a relatively high spatial level, as it would pose ethical concerns otherwise.