| dc.description.abstract | Vapor compression cooling systems are the primary method used for
refrigeration and air conditioning, and as such are a major component of household and
commercial building energy consumption. Application of advanced control techniques
to these systems is still a relatively unexplored area, and has the potential to significantly
improve the energy efficiency of these systems, thereby decreasing their operating costs.
This thesis explores a new method of decentralizing the capacity control of a
multiple evaporator system in order to meet the separate temperature requirements of
two cooling zones. The experimental system used for controller evaluation is a custom
built small-scale water chiller with two evaporators; each evaporator services a separate
body of water, referred to as a cooling zone. The two evaporators are connected to a
single condenser and variable speed compressor, and feature variable water flow and
electronic expansion valves. The control problem lies in development of a control
architecture that will chill the water in the two tanks (referred to as cooling zones) to a
desired temperature setpoint while minimizing the energy consumption of the system. A novel control architecture is developed that relies upon time scale separation of
the various dynamics of the system; each evaporator is controlled independently with a
model predictive control (MPC) based controller package, while the compressor reacts
to 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 directly
track an evaporator cooling setpoint while keeping superheat within a tight band, rather
than the industrially standard approach of regulating superheat directly. The compressor
responds to system conditions to track a pressure setpoint; in this configuration, pressure
serves as the signal that informs the compressor of cooling demand changes. Finally, a
global controller is developed that has knowledge of the energy consumption
characteristics of the system. This global controller calculates the setpoints for the local
controllers in pursuit of a global objective; namely, regulating the temperature of a
cooling zone to a desired setpoint while minimizing energy usage. | en |
