Building stock energy modelling in the UK: the 3DStock method and the London Building Stock Model. Issue 1 (20th May 2020)

• Record Type: Journal Article
• Authors: Steadman, Philip; Evans, Stephen; Liddiard, Rob; Godoy-Shimizu, Daniel; Ruyssevelt, Paul; Humphrey, Dominic
• Is Part Of: Buildings & cities. Volume 1:Issue 1(2020)
• Page Start: 100
• Page End: 119
• Publication Date: 2020-05-20
• Subjects: big data -- building stock -- built form -- cities -- digital twin -- energy model -- geospatial -- urban data -- London; City planning -- Periodicals; Urban policy -- Periodicals; Sustainable development -- Periodicals; 307.76
• DOI: 10.5334/bc.52
• Languages: English
• ISSNs: 2632-6655

Abstract

A brief history is provided of models of energy use in the UK building stock, with the focus on the non-domestic sector. This history leads to an account of the development, since 2009, of the 3DStock method for modelling complete building stocks, both domestic and non-domestic. The paper explains how 3DStock models are built and the data sources used. Special emphasis is placed on the relationship of premises (the floorspace occupied by organisations) to buildings. Energy use may be metered at the level of premises, buildings or groups of buildings. Representing the patterns in which premises relate to buildings is therefore crucial to the modelling process, and in particular to the precise measurement of energy intensities. Applications of 3DStock models in building science and policy tools are reviewed, including the London Building Stock Model (LBSM), delivered to the Greater London Authority (GLA) in 2020. This 'digital twin' can be used for the monitoring, simulation and analysis of the building stock. Implications for research and policy are discussed, particularly for energy epidemiology, density, high-rise buildings, retrofit potential, energy-use intensity and benchmarking. Data are in place to extend 3DStock modelling to the whole of England and Wales. Policy and practice relevance: The models can be used to assess energy demand in large numbers of buildings in relation to a range of variables, including built form, age, construction and activities. Poorly performing buildings can be identified, and the potential for retrofit—including renewable technology installations—evaluated using the same variables plus information contained in Energy Performance Certificates (EPCs). Policies for addressing fuel poverty can be evaluated by making links to confidential socioeconomic data on occupants. In conjunction with a dynamic building energy-simulation tool, scenarios can be investigated for retrofit, the potential for renewables and issues in demand-side management. Additional uses are in the precise measurements of density and of the three-dimensional character of the urban fabric. There could be applications in public health, the modelling of indoor and outdoor air pollution, and the tracking of material flows. 3DStock models might also be integrated with digital twins of infrastructure systems and networks.