Predictive HVAC control using a Markov occupancy model

This paper presents a model predictive control (MPC) technique for building heating, ventilation, and air conditioning (HVAC) systems. It incorporates the building's thermal dynamics, local weather predictions, and a stochastic occupancy model to reduce energy consumption while maintaining occupant comfort. Using approximate dynamic programming and a cost function weighted by expected occupancy, the scheme extends the capability of conventional model predictive control by pre-conditioning thermal zones before occupancy begins and reducing conditioning before occupancy ends. The resulting control law may be synthesized step-wise using an on-line optimization or may be periodically synthesized off-line and downloaded into an embedded controller. Simulation results demonstrate the efficacy of both approaches.

[1]  Brandon Hencey,et al.  A comparison of thermal zone aggregation methods , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[2]  Rui Zhang,et al.  Occupancy detection through an extensive environmental sensor network in an open-plan office building , 2009 .

[3]  Darren Robinson,et al.  A generalised stochastic model for the simulation of occupant presence , 2008 .

[4]  Sean P. Meyn,et al.  A sensor-utility-network method for estimation of occupancy in buildings , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[5]  P. Haves.  Model Predictive Control of HVAC Systems: Implementation and Testing at the University of California, Merced , 2010 .

[6]  Manfred Morari,et al.  Use of model predictive control and weather forecasts for energy efficient building climate control , 2012 .

[7]  Donald P. Greenberg,et al.  Sustain: An experimental test bed for building energy simulation , 2013 .

[8]  Prabir Barooah,et al.  Occupancy-based zone-climate control for energy-efficient buildings: Complexity vs. performance , 2013 .

[9]  Prabir Barooah,et al.  Agent-based and graphical modelling of building occupancy , 2012 .

[10]  Bing Dong,et al.  A real-time model predictive control for building heating and cooling systems based on the occupancy behavior pattern detection and local weather forecasting , 2013, Building Simulation.

[11]  Gregor P. Henze,et al.  Building occupancy detection through sensor belief networks , 2006 .

[12]  Miguel Á. Carreira-Perpiñán,et al.  OBSERVE: Occupancy-based system for efficient reduction of HVAC energy , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.

[13]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[14]  Alberto Cerpa,et al.  Occupancy based demand response HVAC control strategy , 2010, BuildSys '10.

[15]  Alberto Bemporad,et al.  The explicit linear quadratic regulator for constrained systems , 2003, Autom..