Predictive control of polymer dispersed liquid crystal glazing for smart façade applications

This study investigates the development of a model-based predictive control strategy for polymer dispersed liquid crystal (PDLC) glazing in office buildings, addressing the lack of advanced control applications in existing literature, which are predominantly rule-based and reactive. The aim is to enhance building performance by dynamically managing solar and visible light transmission through PDLC glazing, thereby improving energy efficiency, occupant comfort, and visual quality. A simulation-based methodology was implemented using TRNSYS 18 for a case study office in Bolzano, Italy. The control framework employs a “controller and worker” configuration, where the controller represents the building and the workers simulate potential control actions. These actions are evaluated using a cost function that integrates key performance indicators (KPIs): total energy consumption, thermal comfort under direct solar exposure, and visual contact with the exterior. Three control modes were defined by adjusting cost function weights to prioritize energy savings, view quality, or thermal comfort. Glare was mitigated by excluding PDLC states exceeding a predefined daylight glare probability (DGP) threshold. Sensitivity analyses were conducted on prediction horizon, DGP threshold, and cost weights. Compared to baseline and rule-based controls, the predictive control demonstrated superior performance in balancing competing objectives. In energy mode, cooling season energy use was reduced by approximately 10 %, while view mode maintained high visual contact with a 5 % energy saving. This research contributes a novel, multi-objective predictive control approach for PDLC glazing, offering enhanced adaptability and performance in dynamic building environments, and advancing the integration of smart façade technologies in sustainable building design.