Parametric Assessment of Building Heating Demand for Different Levels of Details and User Comfort Levels: A Case Study in London, UK

Athanasia Apostolopoulou (), Mingyu Zhu and Jiayi Jin
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Athanasia Apostolopoulou: Nottingham Geospatial Institute, Nottingham University, Nottingham NG7 2TU, UK
Mingyu Zhu: School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
Jiayi Jin: Department of Architecture and Built Environment, Northumbria University, Newcastle upon Tyne NE1 8ST, UK

Sustainability, 2023, vol. 15, issue 10, 1-29

Abstract: The Level of Detail (LoD), a parameter used to define the information contained in building models, is an important factor to consider in modeling building energy at the urban scale. In this research, we conducted a parametric study regarding the data requirements for the estimation of the annual residential heat demand in London. More particularly, the requirement of the observation of the actual roof type (LoD2) and the window-to-wall ratio (LoD3) was examined in two different case study areas. Meanwhile, an adaptive comfort level study was implemented using LoD5 models, and its results were assessed holistically with the heat demand to reveal the energy performance of the buildings. The results showed that there was a minor difference in the upgrade of a lower to higher LoD regarding these parameters. At an urban scale, the energy demand of buildings could be estimated using an assumption of archetypes and building ages. However, with a scalable parametric script developed in places, models with a high LoD could provide more detailed insights in the energy performance assessment without generating excessive workload.

Keywords: Level of Detail (LoD); parametric study; London dwelling stock; adaptive comfort (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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