Modern HVAC systems are typically designed serially. First, the system type is chosen and the equipment is sized. Second, the control strategy is developed. Finally, sensing is added to support the control strategy. This serial approach can result in sub-optimal operation.
This project will develop a framework and methodology for designing commercial building HVAC systems that have enhanced energy use flexibility with capability to shed and shift load in response to grid needs. The proposed approach be based on concurrent system design and control design. The system design parameters (e.g. number of equipment, equipment type, equipment capacity, equipment performance parameters, number and location of sensors) and the parameters of the controller (e.g. sampling rates, prediction horizons) will be adjusted simultaneously to optimize metrics such as system efficiency, load flexibility, total energy cost, fault detectability and diagnosis, and system life-cycle cost. The methodology will account for uncertainty associated with the building loads and model approximations will deliver solutions that have high likelihood to achieve maximal performance in real operational contexts.
The project will initially address an HVAC system retrofit use case that incorporates renewable energy generation and energy storage.