Abstract
To decrease greenhouse gas emissions of the Swiss building stock, effective retrofit strategies are necessary. Due to the long-term operation of buildings, future developments and uncertainties need to be considered, which calls for assessing the robustness of retrofit decisions. Existing studies propose robustness metrics for decisions under deep uncertainty to be coupled with a scenario-based simulation approach. We review these metrics and present a simulation approach that includes current and future operational energy, emissions, and costs. We apply the seven identified metrics to retrofit decisions of a multifamily house located in Zurich, where future scenarios in terms of climate, occupancy, decarbonization, and cost development are included. The metrics are based on different assumptions and positions towards risk. We further find that the discriminatory power is different, confirming the Minimax Regret metric to be most suitable for the building context when looking at individual buildings. For the case study, we find that deep retrofit seems to be a robust decision from an environmental perspective. From a cost perspective, the electrification of the heating system with heat pumps and the installation of PV without a complete envelope retrofit proves to be most robust.
Highlights
Reaching Swiss greenhouse gas emission reduction goals for the building sector requires effective renovation strategies [1]
We further find that the discriminatory power is different, confirming the Minimax Regret metric to be most suitable for the building context when looking at individual buildings
Comparison of Robustness Metrics If we only look at the single most robust choice according to each metric, we can see that they mostly agree with some minor deviations
Summary
Reaching Swiss greenhouse gas emission reduction goals for the building sector requires effective renovation strategies [1]. Due to the energy performance gap (EPG), the building stock might not be decarbonised as expected [2]. Uncertain boundary conditions such as occupant behaviour, climatic conditions, and characteristics of energy system components lead to inaccurate predictions of operational emissions and decarbonization pathways. To account for such uncertainties, robustness assessment in the design stage is required. In the context of deep uncertainty, where probability distributions of future developments are unknown, a non-probabilistic, scenario-based approach is preferable [5]. This article aims to summarize and discuss the current state of scenario-based robustness assessment of buildings, identify suitable metrics, and present a case study where those metrics are applied
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