EnergyPlus model-based predictive control within design–build–operate energy information modelling infrastructure

This study proposes a design–build–operate energy information modelling (DBO-EIM) infrastructure to allow users to deploy the design-stage building energy model for model predictive control (MPC) system in the building operation. A newly constructed office building is studied as a test bed. An EnergyPlus model-based predictive control (EPMPC) system is designed and simulated in the Matlab/Simulink environment within the DBO-EIM infrastructure. EPMPC aims at minimizing heating, ventilation, and air conditioning energy consumption while maintaining occupant thermal comfort. Compared to the baseline rule-based control system, EPMPC demonstrates a 28.9% energy reduction in one-week simulation in the heating season and 2.7% energy reduction in one-week simulation in the cooling season. The comfort constraint is met during more than 90% of the simulated hours. The study demonstrates one significant contribution of the DBO-EIM infrastructure that a design-stage EnergyPlus model can be integrated in an MPC system and the preliminary simulation results are satisfactory.

[1]  Edward A. Lee,et al.  Ptolemy: A Framework for Simulating and Prototyping Heterogenous Systems , 2001, Int. J. Comput. Simul..

[2]  Refrigerating 2001 ASHRAE handbook : fundamentals , 2001 .

[3]  Manfred Morari,et al.  Model predictive control: Theory and practice - A survey , 1989, Autom..

[4]  Refrigerating ASHRAE handbook of fundamentals , 1967 .

[5]  K. Yang,et al.  AN APPROACH TO BUILDING ENERGY SAVINGS USING THE PMV INDEX , 1997 .

[6]  Vivian Loftness,et al.  OCCUPANT BEHAVIOR AND SCHEDULE PREDICTION BASED ON OFFICE APPLIANCE ENERGY CONSUMPTION DATA MINING , 2013 .

[7]  Samuel Prívara,et al.  Building modeling: Selection of the most appropriate model for predictive control , 2012 .

[8]  Fariborz Haghighat,et al.  A software framework for model predictive control with GenOpt , 2010 .

[9]  Rui Zhang,et al.  Development of web-based information technology infrastructures and regulatory repositories for green building codes in China (iCodes) , 2013, Building Simulation.

[10]  Lukas Ferkl,et al.  Model predictive control of a building heating system: The first experience , 2011 .

[11]  Daniel E. Fisher,et al.  EnergyPlus: creating a new-generation building energy simulation program , 2001 .

[12]  Ardeshir Mahdavi,et al.  A model-based approach to natural ventilation , 2008 .

[13]  Nathan Mendes,et al.  Predictive controllers for thermal comfort optimization and energy savings , 2008 .

[14]  Balaji Rajagopalan,et al.  Model-predictive control of mixed-mode buildings with rule extraction , 2011 .

[15]  Lucas M Ihlein,et al.  Push and Pull , 2011 .

[16]  Ardeshir Mahdavi,et al.  An agent-based simulation-assisted approach to bi-lateral building systems control , 2003 .

[17]  George E. Kelly Control system simulation in North America , 1988 .

[18]  Vivian Loftness,et al.  Multi-structural fast nonlinear model-based predictive control of a hydronic heating system , 2013 .

[19]  Truong Nghiem,et al.  MLE+: a tool for integrated design and deployment of energy efficient building controls , 2012, SIGBED.

[20]  Shengwei Wang,et al.  Model-based optimal control of VAV air-conditioning system using genetic algorithm , 2000 .

[21]  Tamara G. Kolda,et al.  Optimization by Direct Search: New Perspectives on Some Classical and Modern Methods , 2003, SIAM Rev..

[22]  Kristie Bosko Mertz A Representational Framework for Building Systems Control , 2003 .

[23]  Michael Wetter,et al.  GenOpt(R), generic optimization program, User Manual, Version 2.0.0 , 2003 .

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

[25]  D. Kolokotsa,et al.  Predictive control techniques for energy and indoor environmental quality management in buildings , 2009 .

[26]  Moncef Krarti,et al.  Development of a Predictive Optimal Controller for Thermal Energy Storage Systems , 1997 .

[27]  Xiufeng Pang,et al.  Real-Time Building Energy Simulation Using EnergyPlus and the Building Controls Test Bed , 2013 .

[28]  Ardeshir Mahdavi Simulation-based control of building systems operation , 2001 .

[29]  Jie Zhao,et al.  Design-Build-Operate energy information modeling (DBO-EIM) for green buildings: Case study of a net , 2011 .

[30]  Gregor P. Henze,et al.  A model predictive control optimization environment for real-time commercial building application , 2013 .

[31]  Francisco Rodríguez,et al.  A comparison of thermal comfort predictive control strategies , 2011 .

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

[33]  Michael Wetter,et al.  Co-simulation of building energy and control systems with the Building Controls Virtual Test Bed , 2011 .

[34]  David Sept. Glover,et al.  Push and pull , 2008 .

[35]  Bing Dong,et al.  Integrated Building Heating, Cooling and Ventilation Control , 2010 .

[36]  Nicolas Morel,et al.  A personalized measure of thermal comfort for building controls , 2011 .

[37]  K. Lam,et al.  Influential factors analysis on LEED building markets in U.S. East Coast cities by using Support Vector Regression , 2012 .

[38]  James E. Braun,et al.  Reducing energy costs and peak electrical demand through optimal control of building thermal storage , 1990 .

[39]  村上 昌史,et al.  Field experiments on energy consumption and thermal comfort in the office environment controlled by occupants' requirements from PC terminal , 2009 .

[40]  Jlm Jan Hensen,et al.  Model based optimal control for integrated building systems , 2006 .

[41]  Benjamin Paris,et al.  Heating control schemes for energy management in buildings , 2010 .

[42]  Shui Yuan,et al.  Multiple-zone ventilation and temperature control of a single-duct VAV system using model predictive strategy , 2006 .