Elsevier

Energy Policy

Volume 152, May 2021, 112220
Energy Policy

Optimal building retrofit pathways considering stock dynamics and climate change impacts

https://doi.org/10.1016/j.enpol.2021.112220Get rights and content
Under a Creative Commons license
Open access

Highlights

Indicator-based optimization of retrofit pathways based on 1.1 million retrofit options.

Dynamic building stock development and climate change scenarios.

Technical GHG abatement potential of −90% in 2060 with 182 CHF/t CO2eq.

Cost-optimal GHG abatement potential of 77% in 2060 with −138 CHF/t CO2eq.

Early energy retrofit is cost effective and allows deep GHG emission reduction.

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.

Keywords

Deep energy retrofit pathways
Energy efficiency
Dynamic building stock model
Indicator-based optimization
Climate change scenarios