Multiplexed real-time optimization of HVAC systems with enhanced control stability

In a central heating, ventilation, and air conditioning (HVAC) system, the set-points for several local control loops have a significant influence on the overall energy performance of the system. Real-time optimization (RtOpt) of those set-points has therefore been widely studied. However, due to the nonlinear dynamics of the HVAC system as well as the constraints associated with the system operation, real-time optimization always suffers from a heavy on-line computational load when those set-points are optimized simultaneously. To overcome this problem, multiplexed real-time optimization (MRtOpt) has been developed, which optimizes only one set-point at a time but with a faster optimization frequency. Because frequently resetting the set-points introduces artificial disturbances into the local control loops and may deteriorate the system stability, this paper presents a study to enhance the system stability of the multiplexed real-time optimization by integrating a degree of freedom (DOF) based set-point reset to renew the set-points instead of the conventional step-change set-point reset. The control performance of the integrated strategy was investigated using case studies. The results showed that around 10% of the energy saving was achieved by the proposed method compared with a method without real-time optimization. When compared with the conventional real-time optimization method, the proposed method resulted in around 70% computational load reduction, and over 26% reduction in the tracking errors of the local control loops.

[1]  Pedro J. Mago,et al.  Combined cooling, heating and power: A review of performance improvement and optimization , 2014 .

[2]  Zhengwei Li,et al.  Multiplexed optimization for complex air conditioning systems , 2013 .

[3]  Mahdi Shahbakhti,et al.  Optimal exergy control of building HVAC system , 2015 .

[4]  Miao Li,et al.  Optimization and analysis of CCHP system based on energy loads coupling of residential and office buildings , 2014 .

[5]  Robert Sabourin,et al.  Optimization of HVAC Control System Strategy Using Two-Objective Genetic Algorithm , 2005 .

[6]  Andrew Kusiak,et al.  Minimization of energy consumption in HVAC systems with data-driven models and an interior-point method , 2014 .

[7]  Xing Fang,et al.  A dual-benchmark based energy analysis method to evaluate control strategies for building HVAC systems , 2016 .

[8]  Lihua Xie,et al.  Global optimization for overall HVAC systems––Part II problem solution and simulations , 2005 .

[9]  V. Zavala.  Real-Time Optimization Strategies for Building Systems† , 2013 .

[10]  Jan M. Maciejowski,et al.  Predictive control : with constraints , 2002 .

[11]  Bart De Moor,et al.  A unifying theorem for three subspace system identification algorithms , 1995, Autom..

[12]  Andrew Kusiak,et al.  Modeling and optimization of HVAC energy consumption , 2010 .

[13]  Keck Voon Ling,et al.  Expert control of air-conditioning plant , 1994, Autom..

[14]  Bart De Moor,et al.  N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems , 1994, Autom..

[15]  T. I. Salsbury.  A Temperature Controller for VAV Air-Handling Units Based on Simplified Physical Models , 1998 .

[16]  Lennart Ljung,et al.  Subspace identification from closed loop data , 1996, Signal Process..

[17]  Farrokh Janabi-Sharifi,et al.  Review of modeling methods for HVAC systems , 2014 .

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

[19]  Jean Lebrun,et al.  Simplified models for direct and indirect contact cooling towers and evaporative condensers , 2004 .

[20]  Zhenjun Ma,et al.  Supervisory and optimal control of central chiller plants using simplified adaptive models and genetic algorithm , 2011 .

[21]  Si-Zhao Joe Qin,et al.  An overview of subspace identification , 2006, Comput. Chem. Eng..

[22]  Gongsheng Huang,et al.  Degree of freedom based set-point reset scheme for HVAC real-time optimization , 2016 .

[23]  Zhenjun Ma,et al.  An optimal control strategy for complex building central chilled water systems for practical and real-time applications , 2009 .

[24]  Luis Pérez-Lombard,et al.  A review on buildings energy consumption information , 2008 .

[25]  Lihua Xie,et al.  Global optimization for overall HVAC systems––Part I problem formulation and analysis , 2005 .

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