Distributed model predictive control with priority coordination for limited supply multi-zone HVAC systems

Abstract

The conventional multi-zone HVAC (Heating Ventilation and Air Conditioning) system includes a lot of Variable Air Volume (VAV) boxes to regulate the corresponding zone temperature, and centralized equipment (air supply fans and ducts, etc.) to supply conditioned air in the air-side. With the limitation of the total supply air mass rate in centralized equipment and the priority of zones’ requirement, it becomes a question of resource allocation and schedule on how to coordinate air mass rate to each zone. It is also intricate to control each zone’s temperature in a fully distributed fashion due to this global constraint. In this paper, a distributed model predictive control (DMPC) with priority coordination is proposed for multi-zone HVAC systems. This strategy is composed of a priority coordinated layer and a lower DMPC layer. In the coordinated layer, a thermal bound calculation mechanism with priority is presented to adjust thermal bounds for DMPC to resolve the resource allocation problem when the subsystems are competing for the resource. In DMPC, an operational cost-saving controller is put forward, and the global resource limit is guaranteed by transforming the optimization problem into a consensus problem, which is running in a fully distributed way. In this control scheme, the original infeasible DMPC problem is relaxed, and the entire system is functioning well with specified performance compromise. The effectiveness of the proposed scheme is proved by simulation examples.