Total and Peak Energy Consumption Minimization of Building HVAC Systems Using Model Predictive Control

This article addresses the challenge of realizing the building automation and control system using a distributed network of embedded computers. A specification methodology and design space exploration framework are proposed to raise the level of abstraction at which building control systems are designed, to reduce design effort, and to lower implementation cost.

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

[2]  R. Snyder.  California Irrigation Management Information System , 1984, American Potato Journal.

[3]  J. Lofberg,et al.  YALMIP : a toolbox for modeling and optimization in MATLAB , 2004, 2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508).

[4]  Технология,et al.  National Climatic Data Center , 2011 .

[5]  Prahlad Patel,et al.  Modeling and optimal control algorithm design for HVAC systems in energy efficient buildings , 2013 .

[6]  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.

[7]  Alberto Sangiovanni-Vincentelli,et al.  Model-Based Hierarchical Optimal Control Design for HVAC Systems , 2014 .

[8]  Markus Gwerder,et al.  PREDICTIVE CONTROL FOR INTEGRATED ROOM AUTOMATION , 2005 .

[9]  M Morari,et al.  Energy efficient building climate control using Stochastic Model Predictive Control and weather predictions , 2010, Proceedings of the 2010 American Control Conference.

[10]  Mehdi Maasoumy,et al.  Optimal Control of Building HVAC Systems in the Presence of Imperfect Predictions, ASME Dynamic System Control Conference , 2012 .

[11]  C. N. Jones,et al.  Use of Weather and Occupancy Forecasts for Optimal Building Climate Control (OptiControl) , 2009 .

[12]  Sean P. Meyn,et al.  Building thermal model reduction via aggregation of states , 2010, Proceedings of the 2010 American Control Conference.

[13]  Francesco Borrelli,et al.  Model Predictive Control of thermal energy storage in building cooling systems , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.