Energy efficient model predictive building temperature control

• Published in: Chemical engineering science Vol. 69; no. 1; pp. 45 - 58
• Main Authors: Wallace, Matt, McBride, Ryan, Aumi, Siam, Mhaskar, Prashant, House, John, Salsbury, Tim
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 13.02.2012; Elsevier
• Subjects: air conditioning; Applied sciences; Building control; buildings; Chemical engineering; computer simulation; cooling; economics; energy efficiency; Energy efficient control; energy requirements; EnergyPlus; Exact sciences and technology; heat; linear models; Model predictive control; temperature; Temperature control; Vapor compression cycle; vapors; EnergyPlus; Model predictive control; Energy efficient control; Vapor compression cycle; Temperature control; Building control; Closed loop; Compression; Cooling; Computer simulation; Buildings; Compressor; Modeling; Linear model; Heating; Energetic efficiency; Numerical simulation; Valve; Conditioning; Objective function; Expansion; Refrigerant fluid; Predictive control
• ISSN: 0009-2509; 1873-4405
• DOI: 10.1016/j.ces.2011.07.023

Many systems used in buildings for heating, ventilating, and air-conditioning waste energy because of the way they are operated or controlled. This paper explores the application of model predictive control (MPC) to air-conditioning units and demonstrates that the closed-loop performance and energy efficiency can be improved over conventional approaches. This work focuses on the problem of controlling the vapor compression cycle (VCC) in an air-conditioning system, containing refrigerant which is used to provide cooling. The VCC considered in this work has two manipulated variables that affect operation: compressor speed and the position of an electronic expansion valve. The system is subject to constraints, such as the range of permissible superheat, and also needs to regulate temperature variables to set points. An MPC strategy is developed for this type of system based on linear models identified from data obtained from a first-principles model of the VCC. The MPC strategy incorporates economic measures in the objective function as well as control objectives. Tests are carried out on a simulated VCC system that is linked to a simulation of a realistic building that is developed in the U.S. Department of Energy Computer Simulation Program, EnergyPlus. The MPC demonstrated significantly better tracking control relative to conventional approaches (a reduction of 70% in terms of the integral of squared error for step changes in the temperature set-point), while reducing the VCC energy requirements by 16%. The paper describes the control approach in detail and presents results from the tests. ► A model predictive controller was designed for controlling a model of a vapor compression cycle connected to a building. ► A suitable input-disturbance-output model was identified from simulation data. ► Simulation results demonstrate the improved energy efficiency achievable through advanced control approaches.