Beskrivelse

Energy policy is often being made on the basis of building stock models. Most of these models presently rely solely on building component characteristics and standard assumptions. This means that the current, theoretically-based models often ignore the complex interactions between technological, social, economic, behavioural and physical factors; factors which influence the energy consumption in buildings significantly.
Moreover, present building stock models often lack the ability to evaluate the effect of implementing new technologies, as well as the ability to evaluate the effect of past policy interventions, due to inadequate data. As a consequence, many policy interventions do not deliver the anticipated impact on the energy consumption. Likewise, misleading building stock models and hence policies may cause companies to make poor investments and focus on products that may not perform as intended, due to the lack of reliable evaluation.

Present models may be improved, if real building energy use data were available. Such data are already being collected in many countries; however, access to these data is often limited for privacy reasons. Moreover, different building stock models may require different data. Therefore, there is a need for a systematic approach to collecting and analysing real building energy use data, which takes privacy concerns into consideration. This could be done, by considering how the collected data can be aggregated, in appropriately sized segments, while preserving the necessary data integrity.
In Denmark, both building component data and data on energy consumption are being collected. Whether the data collection and storage process is optimal may be assessed by evaluating it against that used in other countries. In any case, the Danish data may be used as a significant contribution to the project.
Present day technologies, such as smart meters, allow for high resolution monitoring of the energy consumption in buildings. Thus these technologies offer a huge potential in relation to building stock modelling. However, it must be assessed how these technologies can best be used in the data collection process.
StatusIgangværende
Effektiv start/slut dato01/11/201631/10/2020

Samarbejdspartnere

  • Aalborg Universitet
  • University College London (Projektpartner) (leder)
  • University of Wollongong (Projektpartner)
  • Austrian Society for Environment and Technology (Projektpartner)
  • AEE – Institute for Sustainable Technologie (Projektpartner)
  • Technical University of Vienna (Projektpartner)
  • University of Ghent (Projektpartner)
  • KU Leuven (Projektpartner)
  • Tsinghua University (Projektpartner)
  • Stuttgart Technology University of Applied Sciences (Projektpartner)
  • German Aerospace Centre – Energy Research (Projektpartner)
  • International Energy Research Centre (Projektpartner)
  • Waseda University (Projektpartner)
  • Chalmers University of Technology (Projektpartner)
  • Delft University of Technology (Projektpartner)
  • United States Department of Energy (Projektpartner)
  • Lawrence Berkeley National Laboratory (Projektpartner)
  • University of California, CA (Projektpartner)
ID: 265489616