Dynamic building stock modelling: General algorithm and exemplification for Norway

• Published in: Energy and buildings Vol. 132; pp. 13 - 25
• Main Authors: Sartori, Igor, Sandberg, Nina Holck, Brattebø, Helge
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 15.11.2016; Elsevier BV
• Subjects: Algorithms; Building construction; Building stock model; Construction; Demolition; Dwelling stock; Dwellings; Dynamic material flow analysis; Emissions; Energy; Energy demand; Greenhouse effect; Greenhouse gases; Housing; Incentives; Probability; Renovation rate; Statistical analysis; Norway; Dynamic material flow analysis; Building stock model; Renovation rate; Dwelling stock
• ISSN: 0378-7788; 1872-6178; 1872-6178
• DOI: 10.1016/j.enbuild.2016.05.098

•A dwelling stock model relying on population statistics in principle available for any country.•The core algorithm is provided in pseudo-code.•Results are: construction, demolition and renovation flows in a long term development, i.e. 1800–2100.•The natural renovation rates, as a result of the need for maintenance of an ageing stock, will increase in future decades but slowly.•The model provides a sound basis for energy and climate impact analysis of a dwelling stock. This paper presents a model based on dynamic material flow analysis, general in its principles and applied to the dwelling stock of Norway for exemplification. The algorithm at the core of the model is presented in the form of a pseudo-code and is described in detail. The driving force in the model is a population’s need for housing and the necessary input are retrievable from national statistics on population, often dating back to around 1800, and its prognoses up to 2050 or beyond. Technical parameters such as the dwellings’ lifetime and the renovation cycles are expressed by probability functions. Outputs of the model are the flows of construction, demolition and renovation; analysis of the renovation activity is given particular attention. The model shows how the renovation rates are a result of the need for maintenance of an ageing stock, and provides quantitative estimates of the present and future natural renovation rates, i.e. without specific incentives. The paper shows how to validate the model against statistics and other data sources, and how to use the model’s future projections on construction, demolition and renovation activities in scenario based analyses of dwelling stocks’ energy demand and greenhouse gases emissions.