A methodology for digitally optimising energy consumption in buildings dataset

Globally, the building sector accounts for 40% of the total energy consumption and directly contributes to climate change. In Australia, the building sector contributes up to 20% of its total energy consumption, thus emphasising the relevance of efficient energy management. For this reason, the optimisation of energy consumption in buildings has received considerable attention in recent times. Notwithstanding, the available works in the literature on energy consumption optimisation have considered the building a static object neglecting its constant interactions with occupants. These building-occupants interactions present the structure as a dynamic object and thus, should be considered in improving the energy consumption. As a result of the static consideration of buildings, the majority of the works have experienced gaps between the predicted and the actual energy consumption resulting in inadequate energy improvements. Thus, the dynamic nature of buildings should be considered to adequately manage energy consumption and improve occupants’ comfort. To address this gap, this study aimed at developing a methodology for digitally optimising energy consumption and indoor environmental parameters (heat, light, and air quality) of buildings using digital twin (DT) technology for dynamic occupant interactions 1. Stakeholder Interviews: This folder contains the verbatim interview transcripts with the stakeholders of the library, analysis and results. The transcripts contain sensitive information. 2. Expert Interviews: This folder contains the verbatim interview transcripts, completed Likert scale questionnaire and results of the expert interviews. The transcripts contain sensitive information. 3. Living Lab Data: This folder contains the exported sensors data on the indoor conditions (temperature, relative humidity, illumination, carbon dioxide and total volatile organic compounds concentration) of the group study rooms on level 01 of the Kingswood library. This data is not available for open publication due to ethics restrictions. To discuss the data, please contact the creator De-Graft Joe Opoku ORCID 0000-0003-2557-5268.