Adaptive building envelopes can dynamically adapt to environmental changes, often supported by a control system. While building performance simulation (BPS) tools can be employed to test different design alternatives, representing control strategies within current BPS tools can be challenging, especially for systems with a fast, dynamic response. Another challenge in current BPS tools is the ability to tune and select parameters for the particular use case. In this study, a modelling approach is presented for the integrated analysis of control strategies of adaptive building envelopes linking thermal performance and control with an optimisation algorithm. The proposed modelling approach was evaluated using a case study with an automated motorised blind with two distinct control strategies. Simulation results suggest that the window heat gains were 72.7 % lower when the controller model was coupled with an optimiser to identify optimised controller parameters compared to a baseline control strategy. The results of this study are suggestive of the benefits that can be obtained from adjusting the dynamic aspects of the building envelope. The results support the thesis of using optimisation as standard building envelope design practice in the future.

Adaptive building envelopes can dynamically adapt to environmental changes to improve thermal building performance. To predict the performance of design proposals with adaptive building envelopes, Building Performance Simulation (BPS) tools can be employed. However, one shortcoming of existing tools is their limited extensibility, which implies that accurately predicting adaptive building envelope performance remains a challenge and requires ad hoc approaches. This challenge has made practitioners reticent in considering adaptive building envelopes, which in turn has led to a slow uptake of them in the built environment. This study seeks to advance the understanding of the limitations of adaptive building envelope simulation in current design practice and to suggest implications for future tool developments. To this aim, the study adopts a user-centred perspective through interviews with experts in the field. Findings suggest that current BPS tools hinder the reliable prediction of adaptive building envelope performance, as accurately representing the level of detail of the building envelope is challenging. The subsequent workarounds applied are either time-and cost-intensive or do not consider the dynamic building envelope components. More flexible modelling approaches that allow for rapid prototyping and easy integration are required to enable designers to take full advantage of adaptive building envelopes.

The thermal performance of adaptive building envelopes can be evaluated using building performance simulation tools. Simulation capabilities and accuracy in predicting the dynamic behaviour of adaptive building envelopes can be enhanced through co-simulation. However, it is unclear how accurately co-simulation can predict the performance of adaptive building envelopes and how the accuracy of adaptive building envelope models created in co-simulation setups can be assessed and validated. Therefore, this study presents new evidence on the empirical validation of co-simulation setups for adaptive building envelopes by establishing an assessment framework to determine the extent to which they can accurately represent the real world. The framework was applied to a case study to validate a co-simulation setup for a blind automation system using monitored data from MATELab, a full-scale outdoor test facility with realistic indoor and outdoor conditions. The validation of the co-simulation model of MATELab resulted in a median CV-RMSE index, a measure of model accuracy, of 5.9%. This indicates that the simulated data points have a small variance relative to the measured data points, showing a good model fit. In the future, modellers from the façade community can use the assessment framework for their co-simulation setups.