Supervisory model predictive controller (MPC) for residential HVAC systems: Implementation and experimentation on archetype sustainable house in Toronto

Abstract Residential heating, ventilation and air conditioning (HVAC) systems usually employ on/off controllers to regulate the temperature. Generally, there is no supervisory controller which can use the weather forecast and electricity time of use (TOU) price information to reduce the overall operating cost of the equipment. Lack of a supervisory controller results in higher operating costs of the HVAC system. In this paper, a model predictive control (MPC) based supervisory controller is designed to shift the heating and cooling load of a house to off-peak hours. Supervisory MPC generates the temperature set-points trajectory for on/off controllers. The approach was verified through extensive experiments in an experimental archetype house. By employing the supervisory controller with variable set-points 16% cost savings were obtained when compared to the fixed zone temperature set-points at 25 °C. More significant savings of about 50% were seen when MPC-based centralized controller was compared with the fixed zone temperature set-points of 24 °C.

[1]  Francisco Rodríguez,et al.  Thermal comfort control using a non-linear MPC strategy: A real case of study in a bioclimatic building , 2014 .

[2]  Hl Henk Schellen,et al.  Simulation of the climate system performance of a museum in case of failure events , 2010 .

[3]  Alan S. Fung,et al.  The Archetype Sustainable House: Investigating its potentials to achieving the net-zero energy status based on the results of a detailed energy audit , 2010 .

[4]  Simeng Liu,et al.  Experimental Analysis of Model-Based Predictive Optimal Control for Active and Passive Building Thermal Storage Inventory , 2005 .

[5]  António E. Ruano,et al.  Neural networks based predictive control for thermal comfort and energy savings in public buildings , 2012 .

[6]  Alan S. Fung,et al.  Comparative thermal performances of a ground source heat pump and a variable capacity air source heat pump systems for sustainable houses , 2015 .

[7]  Francesco Borrelli,et al.  Implementation of model predictive control for an HVAC system in a mid-size commercial building , 2014 .

[8]  Manfred Morari,et al.  Model Predictive Climate Control of a Swiss Office Building: Implementation, Results, and Cost–Benefit Analysis , 2016, IEEE Transactions on Control Systems Technology.

[9]  David E. Culler,et al.  Reducing Transient and Steady State Electricity Consumption in HVAC Using Learning-Based Model-Predictive Control , 2012, Proceedings of the IEEE.

[10]  Alan S. Fung,et al.  Modeling, simulation and feasibility analysis of residential BIPV/T+ASHP system in cold climate—Canada , 2014 .

[11]  Farrokh Janabi-Sharifi,et al.  Theory and applications of HVAC control systems – A review of model predictive control (MPC) , 2014 .

[12]  Alan S. Fung,et al.  Heating and cooling performance characterisation of ground source heat pump system by testing and TRNSYS simulation , 2015 .

[13]  Joseph Andrew Clarke,et al.  Simulation-assisted control in building energy management systems , 2002 .

[14]  Philip Haves,et al.  Model predictive control for the operation of building cooling systems , 2010, Proceedings of the 2010 American Control Conference.

[15]  Farrokh Janabi-Sharifi,et al.  Gray-box modeling and validation of residential HVAC system for control system design , 2015 .

[16]  Farrokh Janabi-Sharifi,et al.  Black-box modeling of residential HVAC system and comparison of gray-box and black-box modeling methods , 2015 .

[17]  Keith J. Burnham,et al.  Modelling of an Air Handling Unit: A Hammerstein-bilinear Model Identification Approach , 2011, 2011 21st International Conference on Systems Engineering.

[18]  Alan S. Fung,et al.  Performance of two-stage variable capacity air source heat pump: Field performance results and TRNSYS simulation , 2015 .

[19]  Bing Dong,et al.  Non-linear optimal controller design for building HVAC systems , 2010, 2010 IEEE International Conference on Control Applications.

[20]  Alan S. Fung,et al.  Experimental and numerical investigation of the thermal impact of defrost cycle of residential heat and energy recovery ventilators , 2015 .

[21]  Frauke Oldewurtel,et al.  Experimental analysis of model predictive control for an energy efficient building heating system , 2011 .

[22]  Arthur L. Dexter,et al.  An Inferential Model-Based Predictive Control Scheme for Optimizing the Operation of Boilers in Building Space-Heating Systems , 2010, IEEE Transactions on Control Systems Technology.