Multi-priority HVAC temperature control with resource constrained based on coordinated distributed zone MPC

Abstract

The conventional HVAC system for multi-area buildings includes both centralized and in-situ equipment to collectively regulate indoor air temperature to meet the preferences of its occupants. However, due to the limited capacity of the total supply air mass rate in centralized equipment, maintaining comfortable indoor air temperature for all areas can face conflicts. The first conflict arises between satisfying diverse preferences and limited global resources, while the second conflict is between centralized air supply and distributed regulation. In this paper, a distributed zone model predictive control (DZMPC) with priority conflict resolution is proposed for the multi-area HVAC systems. This strategy is composed of a zone parameter optimization with dynamic priority as a coordinated upper layer and a lower DZMPC layer. In the upper layer, a zone parameter optimization with priority is presented to coordinate sub-controllers by adjusting variable references’ bounds for DZMPC, to solve the resource competition when it occurs. In the lower layer, model predictive control with zone control is formed to mitigate the tension of the shared resource. By integrating dual decomposition and Augmented Lagrange function to address global constraints, a distributed solvable control structure is formed. The resulting optimization can be solved using a distributed primal–dual algorithm. The effectiveness of the proposed scheme is proved by simulation examples.