IDEAS home Printed from https://ideas.repec.org/p/enp/wpaper/eprg2018.html
   My bibliography  Save this paper

Developing a generic System Dynamics model for building stock transformation towards energy efficiency and low-carbon development

Author

Listed:
  • Wei Zhou

    (Department of Engineering, University of Cambridge)

  • Alice Moncaster

    (Department of Engineering, University of Cambridge)

  • David Reiner

    (EPRG, CJBS, University of Cambridge)

  • Peter Guthrie

    (Department of Engineering, University of Cambridge)

Abstract

A Promoting the decarbonisation of buildings requires effective policy measures. An integral part of policy design is ex-ante evaluation of possible policy options and effects. System Dynamics, one of a range of potential modelling paradigms, emphasises the dynamic complexity arising from stock-and-flow structures, feedbacks, non-linearities and time lags of the system in question. It is therefore well placed to model building stock turnover dynamics and the associated energy use and carbon emissions, in order to conduct scenario analysis for policy evaluation. Previous efforts to employ System Dynamics models in buildings in various national contexts are found to have some common fundamental structural and behavioural limitations. We present an improved formulation that includes both building stock disaggregation and dynamics of energy-related retrofits. The model is characterised by greater transparency facilitating reproducibility and further improvements, high structural and functional flexibility for either extensions or reductions depending upon needs, and high generality and adaptability in diverse applications. It can be used as a stand-alone model or as part of a larger model for policy evaluation and scenario analysis exploring the transformation of building stock from improving energy efficiency and shifting towards low-carbon development.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Wei Zhou & Alice Moncaster & David Reiner & Peter Guthrie, 2020. "Developing a generic System Dynamics model for building stock transformation towards energy efficiency and low-carbon development," Working Papers EPRG2018, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
  • Handle: RePEc:enp:wpaper:eprg2018
    as

    Download full text from publisher

    File URL: https://www.jbs.cam.ac.uk/wp-content/uploads/2023/12/eprg-wp2018.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
    2. Andrea Herbst & Felipe Andrés Toro & Felix Reitze & Eberhard Jochem, 2012. "Introduction to Energy Systems Modelling," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 148(II), pages 111-135, June.
    3. Lopes, M.A.R. & Antunes, C.H. & Martins, N., 2012. "Energy behaviours as promoters of energy efficiency: A 21st century review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4095-4104.
    4. van Vuuren, Detlef P. & Hoogwijk, Monique & Barker, Terry & Riahi, Keywan & Boeters, Stefan & Chateau, Jean & Scrieciu, Serban & van Vliet, Jasper & Masui, Toshihiko & Blok, Kornelis & Blomen, Eliane , 2009. "Comparison of top-down and bottom-up estimates of sectoral and regional greenhouse gas emission reduction potentials," Energy Policy, Elsevier, vol. 37(12), pages 5125-5139, December.
    5. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    6. S. Scrieciu & A. Rezai & R. Mechler, 2013. "On the economic foundations of green growth discourses: the case of climate change mitigation and macroeconomic dynamics in economic modeling," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 2(3), pages 251-268, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huo, Tengfei & Xu, Linbo & Liu, Bingsheng & Cai, Weiguang & Feng, Wei, 2022. "China’s commercial building carbon emissions toward 2060: An integrated dynamic emission assessment model," Applied Energy, Elsevier, vol. 325(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    2. Silva, Felipe L.C. & Souza, Reinaldo C. & Cyrino Oliveira, Fernando L. & Lourenco, Plutarcho M. & Calili, Rodrigo F., 2018. "A bottom-up methodology for long term electricity consumption forecasting of an industrial sector - Application to pulp and paper sector in Brazil," Energy, Elsevier, vol. 144(C), pages 1107-1118.
    3. Fattahi, A. & Sijm, J. & Faaij, A., 2020. "A systemic approach to analyze integrated energy system modeling tools: A review of national models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    4. da Silva, Felipe L.C. & Cyrino Oliveira, Fernando L. & Souza, Reinaldo C., 2019. "A bottom-up bayesian extension for long term electricity consumption forecasting," Energy, Elsevier, vol. 167(C), pages 198-210.
    5. Teotónio, Carla & Fortes, Patrícia & Roebeling, Peter & Rodriguez, Miguel & Robaina-Alves, Margarita, 2017. "Assessing the impacts of climate change on hydropower generation and the power sector in Portugal: A partial equilibrium approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 788-799.
    6. Raventós, Oriol & Dengiz, Thomas & Medjroubi, Wided & Unaichi, Chinonso & Bruckmeier, Andreas & Finck, Rafael, 2022. "Comparison of different methods of spatial disaggregation of electricity generation and consumption time series," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    7. Salari, Mahmoud & Javid, Roxana J., 2017. "Modeling household energy expenditure in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 822-832.
    8. Prina, Matteo Giacomo & Nastasi, Benedetto & Groppi, Daniele & Misconel, Steffi & Garcia, Davide Astiaso & Sparber, Wolfram, 2022. "Comparison methods of energy system frameworks, models and scenario results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    9. Belaïd, Fateh & Garcia, Thomas, 2016. "Understanding the spectrum of residential energy-saving behaviours: French evidence using disaggregated data," Energy Economics, Elsevier, vol. 57(C), pages 204-214.
    10. Buso, Tiziana & Corgnati, Stefano Paolo, 2017. "A customized modelling approach for multi-functional buildings – Application to an Italian Reference Hotel," Applied Energy, Elsevier, vol. 190(C), pages 1302-1315.
    11. Malla, Sunil, 2022. "An outlook of end-use energy demand based on a clean energy and technology transformation of the household sector in Nepal," Energy, Elsevier, vol. 238(PB).
    12. Siala, Kais & Mier, Mathias & Schmidt, Lukas & Torralba-Díaz, Laura & Sheykhha, Siamak & Savvidis, Georgios, 2022. "Which model features matter? An experimental approach to evaluate power market modeling choices," Energy, Elsevier, vol. 245(C).
    13. Martínez-Gordón, R. & Morales-España, G. & Sijm, J. & Faaij, A.P.C., 2021. "A review of the role of spatial resolution in energy systems modelling: Lessons learned and applicability to the North Sea region," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    14. Šćepanović, Sanja & Warnier, Martijn & Nurminen, Jukka K., 2017. "The role of context in residential energy interventions: A meta review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1146-1168.
    15. Rhodes, Ekaterina & Hoyle, Aaron & McPherson, Madeleine & Craig, Kira, 2022. "Understanding climate policy projections: A scoping review of energy-economy models in Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    16. Eggimann, Sven & Hall, Jim W. & Eyre, Nick, 2019. "A high-resolution spatio-temporal energy demand simulation to explore the potential of heating demand side management with large-scale heat pump diffusion," Applied Energy, Elsevier, vol. 236(C), pages 997-1010.
    17. Small, Mitchell J. & Wong-Parodi, Gabrielle & Kefford, Benjamin M. & Stringer, Martin & Schmeda-Lopez, Diego R. & Greig, Chris & Ballinger, Benjamin & Wilson, Stephen & Smart, Simon, 2019. "Generating linked technology-socioeconomic scenarios for emerging energy transitions," Applied Energy, Elsevier, vol. 239(C), pages 1402-1423.
    18. Olegs Krasnopjorovs & Daniels Jukna & Konstantins Kovalovs, 2022. "On the Use of General Equilibrium Model to Assess the Impact of Climate Policy in Latvia," Post-Print hal-03861139, HAL.
    19. Prina, Matteo Giacomo & Manzolini, Giampaolo & Moser, David & Nastasi, Benedetto & Sparber, Wolfram, 2020. "Classification and challenges of bottom-up energy system models - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
    20. Crow, Daniel J.G. & Giarola, Sara & Hawkes, Adam D., 2018. "A dynamic model of global natural gas supply," Applied Energy, Elsevier, vol. 218(C), pages 452-469.

    More about this item

    Keywords

    building stock; System Dynamics; disaggregation; aging chain; energy retrofit;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:enp:wpaper:eprg2018. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ruth Newman (email available below). General contact details of provider: https://edirc.repec.org/data/jicamuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.