Variability of building energy performance at a scale: conformity of predictive and synthesis with explanatory modelling practices

• Main Author: Zhuravchak, Ruslan
• Format: Dissertation
• Language: English

Throughout its existence, humankind invented countless means and practices to design, construct and equip buildings. The number of ways to use these buildings, with or without strictly following their initially intended purpose, is even more significant. The historical and the anticipated future evolution of buildings at a varying pace further amplifies their diversity. An already complex phenomenon of building energy use is hence further entangled. Substantial variations also stem from you, my reader, whose lifestyle and occupancy patterns often cause a logical nightmare for the energy analysts like myself. These are some of the challenges in large-scale building energy research. This discipline intends to mediate the transition to a more sustainable built environment with the associated energy supply systems. Since the discipline's inception, the inherent modelling practices follow either a bottom-up or top-down approach. These two seemingly incompatible paradigms not only address the subject matter in a radically distinct manner but differ substantially in their accuracy, sensitivity, transferability, versatility, computability and usability. So far, both approaches have been used independently, concerned with leveraging their advantages and, generally, overlooking the limitations of one or another. It was, however, expected that the best interests of practice and policymaking necessitate a synergy or a combination of approaches rather than their application individually. Seeking ways to complement bottom-up and top-down approaches laid the foundation for the thesis you are holding. The analysis of modelling purposes, targeted system's complexities, model's characteristics and the associated uncertainties were expected to provide meaningful answers. It was also understood that, under the discipline's quest for accurate prediction, explanatory modelling had been largely overlooked. Formulating and testing the causal theories can improve the understanding of building energy performance, the means to mediate it and aid with developing better predictive models. Therefore, examining the interplay of explanatory and predictive modelling, bottom-up and top-down, is another objective of this thesis. It does so through: i) four research papers that attempt to answer why and to which extent the phenomenon varies beyond its best estimates; ii) a case study that exemplifies and examines the conformity of the modelling results obtained with bottom-up and top-down re