In 2024, the global average temperature exceeded 1.5°C above pre-industrial levels for the first time, underscoring the urgent need to tackle climate change. Buildings, which account for nearly one-third of global greenhouse gas emissions, must play a pivotal role in the solution. Reducing these emissions requires understanding how buildings consume energy and how occupants interact with them. This is particularly challenging for single-family houses (SFHs) due to their significant variety. New, detailed data from smart meters can provide valuable insights. This thesis investigates how data from smart heat and smart water meters, in conjunction with building and socio-economic information, can enhance our understanding of energy use and occupancy in Danish SFHs. It demonstrates how this data can be employed at scale to analyse energy use, differentiate space heating from domestic hot water usage, and detect non-intrusively when occupants are home. Additionally, it analyses the temporal changes over time in the EPC data of Danish SFHs. The data processing and methods established in this thesis lay the foundation for future research.

For a copy of the thesis, please email inst.build.phd@build.aau.dk