Building HVAC systems consist of chillers, cooling towers, air handling units (AHU), variable air volume systems (VAVs), fan coil units (FCU), makeup air units (MAU), and their associated components (e.g., compressor, condenser, and evaporator in a chiller). These systems and their
components have various operational and safety constraints and are interconnected via different electrical, mechanical, hydraulic or pneumatic connections along with various control loops; thus making the overall system complex. This complexity along with uncertain operating conditions such as time-varying cooling loads, dynamic weather patterns, and growth of faults makes the energy optimization of chiller plants by near-optimal control a challenging problem. In this regard, the proposed research aims to design supervisory control architecture for energy efficient and resilient chiller plants in accordance to the needs of the UTC.diagram

The key novelty of the proposed approach is a scalable optimization-based supervisory control scheme for energy savings and resilience at the chiller as well as chiller plant level. The supervisory controller will generate near-optimal set-points of different performance variables in the chiller and chiller plant for efficiency maximization under various operational, safety, and computational cost constraints. The supervisor will also target resilient operation of chiller plant in the presence of faults in order to prevent further degradation of the faulty component while meeting the desired performance. The supervisor will be designed to deliver robustness against parametric variability, operational stability, minimum energy consumption, resilience, and minimization of the transient behavior between different set-points and will adapt to predicted cooling load patterns based on history and forecasts of weather, occupancy, etc.