Decentralized Model Predictive Control of a Multiple Evaporator HVAC System

摘要

Vapor compression cooling systems are the primary method used forrefrigeration and air conditioning, and as such are a major component of household andcommercial building energy consumption. Application of advanced control techniquesto these systems is still a relatively unexplored area, and has the potential to significantlyimprove the energy efficiency of these systems, thereby decreasing their operating costs.This thesis explores a new method of decentralizing the capacity control of amultiple evaporator system in order to meet the separate temperature requirements oftwo cooling zones. The experimental system used for controller evaluation is a custombuilt small-scale water chiller with two evaporators; each evaporator services a separatebody of water, referred to as a cooling zone. The two evaporators are connected to asingle condenser and variable speed compressor, and feature variable water flow andelectronic expansion valves. The control problem lies in development of a controlarchitecture that will chill the water in the two tanks (referred to as cooling zones) to adesired temperature setpoint while minimizing the energy consumption of the system. A novel control architecture is developed that relies upon time scale separation ofthe various dynamics of the system; each evaporator is controlled independently with amodel predictive control (MPC) based controller package, while the compressor reactsto system conditions to supply the total cooling required by the system as a whole.MPC?s inherent constraint-handling capability allows the local controllers to directlytrack an evaporator cooling setpoint while keeping superheat within a tight band, ratherthan the industrially standard approach of regulating superheat directly. The compressorresponds to system conditions to track a pressure setpoint; in this configuration, pressureserves as the signal that informs the compressor of cooling demand changes. Finally, aglobal controller is developed that has knowledge of the energy consumptioncharacteristics of the system. This global controller calculates the setpoints for the localcontrollers in pursuit of a global objective; namely, regulating the temperature of acooling zone to a desired setpoint while minimizing energy usage.