Development and calibration of an online energy model for campus buildings

Abstract Previous studies show that building HVAC systems can consume greater than 20% more electrical energy than was the design intent largely because of equipment performance degradation, equipment failures, or detrimental interactions among subsystems. A key barrier is the lack of sufficient and detailed information to isolate abnormal changes in load conditions or anomalous equipment operations. One of the solutions is to develop model-based diagnostic methods. Hence, developing a calibrated energy performance model becomes a key component. In this paper, an integrated energy model for campus buildings was developed based on a Reduced-Order Model (ROM), which includes building envelope model, and HVAC primary and secondary system models. The integrated model was validated against real-time measured data within the ±15% error in terms of the load differences.

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

[2]  T. Agami Reddy,et al.  Calibrating Detailed Building Energy Simulation Programs with Measured Data—Part I: General Methodology (RP-1051) , 2007 .

[3]  David E. Claridge.  USING SIMULATION MODELS FOR BUILDING COMMISSIONING , 2004 .

[4]  Sanjay Kumar,et al.  Online fault detection and diagnosis in VAV air handling unit by RARX modeling , 2001 .

[5]  Simeng Liu,et al.  Experimental Analysis of Model-Based Predictive Optimal Control for Active and Passive Building Thermal Storage Inventory , 2005 .

[6]  Philip Haves,et al.  Condition monitoring in HVAC subsystems using first principles models , 1996 .

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

[8]  Steven B. Leeb,et al.  Detection and Diagnosis of HVAC Faults via Electrical Load Monitoring , 2002 .

[9]  Xiufeng Pang,et al.  REAL TIME MODEL-BASED ENERGY DIAGNOSTICS IN BUILDINGS , 2011 .

[10]  James E. Braun,et al.  A Methodology for Diagnosing Multiple Simultaneous Faults in Vapor-Compression Air Conditioners , 2007 .

[11]  Sunil Ahuja,et al.  Scalable Deployment of Advanced Building Energy Management Systems , 2013 .

[12]  Zheng O'Neill,et al.  MODEL-BASED THERMAL LOAD ESTIMATION IN BUILDINGS , 2010 .

[13]  Refrigerating.  ASHRAE handbook and product directory /published by the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc , 1977 .

[14]  Philip Haves,et al.  Analysis of an information monitoring and diagnostic system to improve building operations , 2001 .

[15]  Frank Painter.  Whole-Building Commercial HVAC System Simulation for Use in Energy Consumption Fault Detection , 2007 .

[16]  H. C. Peitsman,et al.  Application of black-box models to HVAC systems for fault detection , 1996 .

[17]  Vice President,et al.  AMERICAN SOCIETY OF HEATING, REFRIGERATION AND AIR CONDITIONING ENGINEERS INC. , 2007 .