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Optimal building retrofit pathways considering stock dynamics and climate change impacts

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  • Streicher, Kai Nino
  • Berger, Matthias
  • Panos, Evangelos
  • Narula, Kapil
  • Soini, Martin Christoph
  • Patel, Martin K.

Abstract

Deep energy retrofit across the European building stock would require decades during which boundary conditions will change. This study identifies a range of retrofit pathways, using a dynamic stock model, a bottom-up energy model and an optimization model for different climate scenarios. We consider 1.1 million different retrofit options in the Swiss residential building stock for different economic/environmental objectives until 2060. Despite the replacement of old by new buildings, energy demand and greenhouse gas (GHG) emissions in the reference scenario without deep energy retrofitting are likely to decrease by only about 25%, while accounting for investments of 2–3 billion CHF/a. Partial energy retrofitting or an investment-minimized pathway are neither cost-effective nor sufficient to get close to the net zero targets. In contrast, the highest GHG-saving pathway leads to very high emission reduction of 90%, but requires investment cost of 9 billion CHF/a, which leads to specific cost of 180 CHF/t CO2eq. The cost-optimal pathway shows moderate trade-offs for investment cost and could reach GHG savings of 77% with specific cost of −140 CHF/t CO2eq. Hence, early and deep energy retrofit is cost-effective and allows deep GHG emission reductions by making full use of the synergies between GHG and cost savings.

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  • Streicher, Kai Nino & Berger, Matthias & Panos, Evangelos & Narula, Kapil & Soini, Martin Christoph & Patel, Martin K., 2021. "Optimal building retrofit pathways considering stock dynamics and climate change impacts," Energy Policy, Elsevier, vol. 152(C).
    • Handle: RePEc:eee:enepol:v:152:y:2021:i:c:s0301421521000896
    DOI: 10.1016/j.enpol.2021.112220
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    4. De Masi, Rosa Francesca & Gigante, Antonio & Ruggiero, Silvia & Vanoli, Giuseppe Peter, 2021. "Impact of weather data and climate change projections in the refurbishment design of residential buildings in cooling dominated climate," Applied Energy, Elsevier, vol. 303(C).
    5. Chambers, Jonathan & Zuberi, M.J.S. & Streicher, K.N. & Patel, Martin K., 2021. "Geospatial global sensitivity analysis of a heat energy service decarbonisation model of the building stock," Applied Energy, Elsevier, vol. 302(C).
    6. Petkov, Ivalin & Mavromatidis, Georgios & Knoeri, Christof & Allan, James & Hoffmann, Volker H., 2022. "MANGOret: An optimization framework for the long-term investment planning of building multi-energy system and envelope retrofits," Applied Energy, Elsevier, vol. 314(C).
    7. Thrampoulidis, Emmanouil & Hug, Gabriela & Orehounig, Kristina, 2023. "Approximating optimal building retrofit solutions for large-scale retrofit analysis," Applied Energy, Elsevier, vol. 333(C).

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