Empirical modeling of the impacts of faults on water-cooled chiller power consumption for use in building simulation programs

Abstract Empirical models of four chiller faults that can be applied within existing building models to study overall impacts are developed in this paper. The faults include overcharging, excess oil, non-condensables in refrigerant and water-side condenser fouling. A single generalized model structured was developed for these faults that forces predicted fault impacts to be zero with no fault and increase with increasing fault level. The models were trained and tested using available laboratory data for a water-cooled centrifugal chiller where all four faults were artificially introduced. The fault model behavior was studied and then they were integrated in hospital models from DOE commercial reference building models (Deru et al., 2011) and simulations were performed in different climates. The simulation results showed maximum increases of building electricity consumption, electricity peak demand and water consumption of the hospitals due to faults of 4.7%, 7.8% and 1.8% respectively. The fault impacts were found to be more severe in hotter and more humid climates.

[1]  James E. Braun,et al.  Decoupling features and virtual sensors for diagnosis of faults in vapor compression air conditioners , 2007 .

[2]  T. Agami Reddy,et al.  Evaluation of the Suitability of Different Chiller Performance Models for On-Line Training Applied to Automated Fault Detection and Diagnosis (RP-1139) , 2003 .

[3]  Frédéric Magoulès,et al.  Development of an RDP neural network for building energy consumption fault detection and diagnosis , 2013 .

[4]  Bing Liu,et al.  U.S. Department of Energy Commercial Reference Building Models of the National Building Stock , 2011 .

[5]  Joaquín Navarro-Esbrí,et al.  A vapour compression chiller fault detection technique based on adaptative algorithms. Application to on-line refrigerant leakage detection , 2006 .

[6]  Piotr A. Domanski,et al.  Normalized performance parameters for a residential heat pump in the cooling mode with single faults imposed , 2014 .

[7]  Xinhua Xu,et al.  A supervisory control strategy for building cooling water systems for practical and real time applications , 2008 .

[8]  Natascha S. Milesi-Ferretti.  Performance Evaluation of a Reciprocating Chiller Using Experimental Data and Model Predictions for Fault Detection and Diagnosis | NIST , 2002 .

[9]  Mo Yang,et al.  A virtual condenser fouling sensor for chillers , 2012 .

[10]  Qiang Zhou,et al.  A model‐based fault detection and diagnosis strategy for HVAC systems , 2009 .

[11]  T. Agami Reddy,et al.  Application of a Generic Evaluation Methodology to Assess Four Different Chiller FDD Methods (RP-1275) , 2007 .

[12]  Piotr A. Domanski,et al.  Effect of heat pump commissioning faults on energy use in a slab-on-grade residential house , 2015 .

[13]  Leon S. Lasdon,et al.  Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming , 1978, TOMS.

[14]  W. Wagner,et al.  The IAPWS Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use , 2002 .

[15]  Ting Wang,et al.  Important sensors for chiller fault detection and diagnosis (FDD) from the perspective of feature selection and machine learning , 2011 .