Simulation-based comparison of robustness assessment methods to identify robust low-energy building designs

Uncertainties in occupant behaviour and climate change can have a large influence on future building performance, especially in low-energy buildings. These uncertainties cause performance variations resulting in deviations between actual operation compared to the predicted performance in the design phase. Therefore, performance robustness assessment of these buildings should consider uncertainties and should be included in the design phase to ensure the intended performance in the future. The probability of occurrences of these uncertainties are usually unknown and hence, scenarios are essential to assess the performance robustness of buildings. However, studies on robustness assessment using scenarios in the building performance context are limited. Therefore, in this work, scenario analysis is combined with various robustness assessment methods from other fields, and these methods are compared using a case study for different decision makers such as homeowners and policymakers.

The max-min and the best-case and worst-case methods lead to conservative robust designs and can be used when a risk-free approach is indispensable in decision-making. The minimax regret method leads to less conservative robust designs and can be used where a decision maker can accept a certain range of performance variation.