Energy and Thermal Comfort Optimization in Building Performance Design
It is estimated that heating and cooling systems of buildings nowadays are a major part of the overall energy consumption (ca. 30%). To reduce this consumption, modifications of build environments are needed, ideally without deteriorating other performance criteria, such as thermal comfort and health. To contribute to this multiobjective design task we develop multiobjective optimization algorithms based on building performance simulation.
Building performance simulation (BPS) is a powerful tool to predict and analyze the dynamic behavior of indicators such as energy consumption and thermal comfort in building. In this project we hypothesize that introducing a design optimization capability to BPS tools can provide valuable support in decision making. Advanced algorithms for multiobjective optimization are assessed for their future integration in building performance tools.
A particular emphasize is the handling of uncertainties. Robustness of solutions is needed, as buildings have to perform well under fluctuating and unpredictable environmental conditions. However, the assessment of robustness comes with a massive computational cost. To reduce this cost, we develop metamodel-assisted multi-criterion optimization techniques that allow to combine virtual evaluations with precise evaluations.
The validation of our research is focused on office buildings, but the developed methodology can be applied to a broader range of building types.
This research is in collaboration with the Building Performance Research Group (Prof. Jan Hensen) of the TU/e and Deerns consulting engineers, Rijkswijk, The Netherlands.