T-ROBUST METHOD. Robustness-based multi-criteria decision-making methodology: Description and example of application
Research report
Published version
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https://hdl.handle.net/11250/3160884Utgivelsesdato
2024Metadata
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Sammendrag
The focus on performance robustness has become paramount in the context of buildings and neighbourhoods, where uncertainties from variables like occupancy and weather scenarios significantly impact their performance.
Selecting a building/neighbourhood design that excels in both performance and robustness poses a challenge, particularly when multiple performance criteria must be met. In general, this requires a three stages process involving performance evaluation, robustness assessment, and multi-criteria decision-making.
This report introduces a novel robustness-based decision-making approach, which integrates robustness assessment and decision-making steps, offering greater transparency compared to existing methodologies. The developed approach has been previously described and applied in scientific dissemination, while this report strives to simplify the communication for a slightly broader audience than the scientific community, while alsoproviding practical guidance and instructions for implementing the method.
This approach has been tested for assessing different responsive building envelope (RBE) technologies within a Norwegian zero-emission building (ZEB lab). The approach evaluates five competitive RBE designs (including building integrated photovoltaics, phase change material, and electrochromic windows) across eight occupancy and climate scenarios, considering three performance indicators, i.e., energy use, thermal comfort, and load matching.
Results show that the suggested approach can effectively support the choice of a building/-neighbourhood design that is both high-performing and robust, requiring less analysis effort. Moreover, the proposed approach exhibits a high level of reliability, by selecting solutions in alignment with defined targets and demonstrating less dependency on scenario conditions.