A review of approaches and applications in building stock energy and indoor environment modelling

• Published in: Building services engineering research & technology Vol. 44; no. 3; pp. 333 - 354
• Main Authors: Dong, J, Schwartz, Y, Mavrogianni, A, Korolija, I, Mumovic, D
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.05.2023
• Subjects: Building performance evaluation; modelling and simulation; building stock modelling; impact of climate change
• ISSN: 0143-6244; 1477-0849
• DOI: 10.1177/01436244231163084

Current energy and climate policies are formulated and implemented to mitigate and adapt to climate change. To inform relevant building policies, two bottom-up building stock modelling approach: 1) archetype-based and 2) Building-by-building have been developed. This paper presents the main characteristics and applications of these two approaches and evaluates and compares their ability to support policy making. Because of lower data requirements and computational cost, archetype-based modelling approaches are still the mainstream approach to stock-level energy modelling, life cycle assessment, and indoor environmental quality assessment. Building-by-building approaches can better capture the heterogeneous characteristics of each building and are emerging due to the development of data acquisition and computational techniques. The model uncertainties exist in both models which may affect the reliability of outputs, while stochastic archetype models and timeless digital twin model have the potential to address the issue. System dynamics modelling approach can describe and address the dynamics and complexity of often-conflicting policies and achieve co-benefit of multiple policy objectives. Practical applications This paper aims to provide comprehensive knowledge on building stock modelling for modellers and policymakers, so they could use a building stock model with an appropriate user interface without having to fully understand the underlying algorithms or complexities.