Control and Optimization of Vapor Compression Systems Using Recursive Estimation (ST-16-010)

Building operations account for approximately 40% of US energy use and carbon emissions, and vapor compression cycles are the primary method by which refrigeration and air-conditioning systems operate. Representing a significant portion of commercial and residential building energy consumption, vapor compression cycles are a target for improvement in efficiency and savings. This paper presents a data-driven approach to find the optimal operating conditions of single and multi-evaporator systems in order to minimize energy consumption while meeting operational requirements such as constant cooling or constant evaporator outlet temperatures. The control problem lies in the development of a control architecture that will minimize the energy consumed without requiring any models of the system or expensive mass flow sensors. The application of the presented approach improves efficiency, and is demonstrated in simulation and on an experimental system.