Advancing urban building energy modelling through new model components and applications: A review

• Published in: Energy and buildings Vol. 266; p. 112099
• Main Authors: Dahlström, Lukas, Broström, Tor, Widén, Joakim
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 01.07.2022; Elsevier BV
• Subjects: Best practice; Bottom -up modelling; Building archetype; Climate change; Demographics; Emissions; Energy; Energy consumption; Greenhouse gases; Mathematical models; Modelling; Modelling components; Parameter identification; Socio-economic data; Urban building energy modelling; Urbanization; Building archetype; Bottom-up modelling; Modelling components; Urban building energy modelling; Socio-economic data
• ISSN: 0378-7788; 1872-6178; 1872-6178
• DOI: 10.1016/j.enbuild.2022.112099

[Display omitted] •Archetype development, model components and potential applications for UBEM are discussed.•Stochastic and dynamic occupancy models are among the most desired improvements for UBEM.•UBEM could be suitable for high accuracy predictions of future climate change scenarios.•Integration of socio-economic data in UBEM is promising but not currently applied.•Assigning value year from renovation records is tempting but could entail several pitfalls. Due to rapid urbanisation and the significant contribution of cities to worldwide energy use and greenhouse gas emissions, urban energy system planning is growing more important. Urban building energy modelling (UBEM) draws increasing attention in the energy modelling field due to its inherent capacities for modelling entire cities or building stocks, and the potential of varying data inputs, approaches and applications. This review aims to identify best practices and improvements for UBEM applications by examining previous research, with a focus on the currently least established approaches. Different archetype development procedures are analysed for common problems, six main under-developed input approaches or parameters are identified, and applications for future scenario development are surveyed. By analysing previous studies in related fields, this paper provides an overview of gaps in the published research and possible additions to future UBEM projects that can help expanding the existing modelling procedures. Comprehensive human behaviour models with additional aspects beyond occupant presence are identified as a major point of interest. Further research on socio-economic parameters, such as household income and demographics, are also suggested to further improve modelling. This study also underlines the potential for utilising UBEM as a tool for evaluating future climate change scenarios.