Experimental study of a model predictive control system for active chilled beam (ACB) air-conditioning system

Abstract Active chilled beams (ACB) are gaining popularity worldwide as a potentially energy-efficient air-conditioning technology for buildings. However, the control of ACB system is challenging, as it needs to handle multiple cooling coils and the relatively slow response to cooling load dynamics. This paper reports the implementation of a model predictive control (MPC) system for an ACB system, which employs a linear white-box building model for building energy and indoor condition predictions. A multiple-objectives function is employed in the MPC controller to optimize the energy efficiency in air-conditioning system and indoor thermal comfort while fulfilling the constraints of indoor comfort range (−0.5

[1]  Kazuyuki Kamimura,et al.  Design and tuning of robust PID controller for HVAC systems , 1999 .

[2]  John Dieckmann,et al.  Chilled Beam Cooling , 2007 .

[3]  Alberto Bemporad,et al.  Model Predictive Control Toolbox™ User’s Guide , 2004 .

[4]  Nursyarizal Mohd Nor,et al.  A review on optimized control systems for building energy and comfort management of smart sustainable buildings , 2014 .

[5]  Peng Xu,et al.  Demand reduction in building energy systems based on economic model predictive control , 2012 .

[6]  Zhe Zhang,et al.  A state-space thermal model incorporating humidity and thermal comfort for model predictive control in buildings , 2018, Energy and Buildings.

[7]  Wenjian Cai,et al.  A hybrid dynamic modeling of active chilled beam terminal unit , 2014 .

[8]  Carlos F. Pfeiffer,et al.  Control of temperature and energy consumption in buildings - a review. , 2014 .

[9]  Xiufeng Pang,et al.  Testing and demonstration of model predictive control applied to a radiant slab cooling system in a building test facility , 2018, Energy and Buildings.

[10]  Cai Wenjian,et al.  Fuzzy model based predictive control for active chilled beam systems , 2017, 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA).

[11]  Youyi Wang,et al.  Performance comparison of heat exchangers with different circuitry arrangements for active chilled beam applications , 2014 .

[12]  Josh Wall,et al.  Trial results from a model predictive control and optimisation system for commercial building HVAC , 2014 .

[13]  Bing Dong,et al.  Integrated building control based on occupant behavior pattern detection and local weather forecasting , 2011 .

[14]  Xiao Chen,et al.  Model predictive control for indoor thermal comfort and energy optimization using occupant feedback , 2015 .

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

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

[17]  W. Beckman,et al.  Solar Engineering of Thermal Processes , 1985 .

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

[19]  Roberto Lamberts,et al.  A review of human thermal comfort in the built environment , 2015 .

[20]  José Domingo Álvarez,et al.  Optimizing building comfort temperature regulation via model predictive control , 2013 .

[21]  Man Pun Wan,et al.  An adaptive robust model predictive control for indoor climate optimization and uncertainties handling in buildings , 2019, Building and Environment.

[22]  Xiao Chen,et al.  Occupant feedback based model predictive control for thermal comfort and energy optimization: A chamber experimental evaluation , 2016 .

[23]  Darren Alexander.  Design Considerations For Active Chilled Beams , 2008 .

[24]  T. Muneer,et al.  Models for estimating solar radiation and illuminance from meteorological parameters , 2000 .

[25]  Thomas F. Edgar,et al.  Building energy model reduction for model predictive control using OpenStudio , 2013, 2013 American Control Conference.

[26]  Siaw Kiang Chou,et al.  Achieving better energy-efficient air conditioning - A review of technologies and strategies , 2013 .

[27]  Lukas Ferkl,et al.  Model-based energy efficient control applied to an office building , 2014 .

[28]  Chang-Hoon Kim,et al.  Optimized operation method for an active chilled beam with VAV system , 2016 .

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