Bottom-Up Modeling of Building Stock Dynamics - Investigating the Effect of Policy and Decisions on the Distribution of Energy and Climate Impacts in Building Stocks over Time
Doktorsavhandling, 2019
Building stock models (BSMs) have long been used to assess the current and future energy demand and GHG emissions of building stocks. Most common BSMs characterize the building stock through the use of archetype buildings, which are taken to be representative of large segments of the stock. The increasing availability of disaggregated datasets—such as building registries, 3D city models, and energy performance certificates—has given rise to building-specific BSMs focusing on describing the status quo as an input to energy planning, primarily on the urban scale. Owing to the availability of building-level data, BSMs can be extended beyond policy advice and urban planning, to the assessment of large building portfolios. Thus far, the advances made in building-specific BSMs on the urban scale have not been transferred to the national scale, where such datasets are often not available. Moreover, the focus on an increasingly detailed description of the existing stock has left approaches for modeling stock dynamics without much development. Stock dynamics, therefore, are still primarily modeled through exogenously defined retrofit, demolition, and new construction rates. This limits the applicability and reliability of model results, as the influence of economic, environmental, or policy factors on stock development is not considered.
This thesis addresses these shortcomings and advances modeling practices in BSMs. The thesis with appended papers provides a methodology for how the modeling of national building stock can be further developed in terms of building stock characterization through synthetic building stocks as well as stock dynamics through the use of agent-based modeling. Furthermore, the thesis extends BSM applications to inform the strategic planning of large building portfolios through the integration of a maintenance and renovation scheduling method to project the future development of building portfolios.
synthetic building stock
agent-based modeling
Building stock modeling
renewable energy
building stock dynamics
energy efficiency
GHG emissions
Författare
Claudio Nägeli
Chalmers, Arkitektur och samhällsbyggnadsteknik, Byggnadsteknologi
A service-life cycle approach to maintenance and energy retrofit planning for building portfolios
Building and Environment,;Vol. 160(2019)
Artikel i vetenskaplig tidskrift
Synthetic building stocks as a way to assess the energy demand and greenhouse gas emissions of national building stocks
Energy and Buildings,;Vol. 173(2018)p. 443-460
Artikel i vetenskaplig tidskrift
Towards agent-based building stock modeling: Bottom-up modeling of long-term stock dynamics affecting the energy and climate impact of building stocks
Energy and Buildings,;Vol. 211(2020)
Artikel i vetenskaplig tidskrift
Policies to decarbonize the Swiss residential building stock: An agent-based building stock modeling assessment
Energy Policy,;Vol. 146(2020)
Artikel i vetenskaplig tidskrift
Styrkeområden
Building Futures (2010-2018)
Energi
Ämneskategorier
Miljöanalys och bygginformationsteknik
Annan samhällsbyggnadsteknik
Husbyggnad
ISBN
978-91-7905-212-6
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4679
Utgivare
Chalmers
room SB-H7, Sven Hultins Gata 6, Göteborg
Opponent: Prof. Daniel Beat Müller, Norwegian University of Science and Technology, Norway