Developing a simplified model for evaluating chiller-system configurations

Optimizing system configuration is always an interest of building designers. By statistical analysis of the design data of 50 commercial buildings in Hong Kong and the performance data of 186 chiller models, it is ascertained that the chiller capacity and the fraction of full-load capacity have little influence on the system's energy performance. Following on this, this paper presents an evaluation of the energy performance of a multiple-chiller system consisting of 2-10 equally sized chillers. Such an analysis was based on performance data from three major manufacturers. It is found that the energy efficiency of multiple-chiller system improves with a higher number of chillers, and the maximum saving is estimated to be 9.5%. Based on the results of the study, a simplified model relating energy use with number of chillers has been established. The model can help designers more quickly determine how the energy efficiency can be weighted against other factors, such as the additional plant room space and the financial implications.

[1]  F. W. Yu,et al.  Thermodynamic-behaviour model for air-cooled screw chillers with a variable set-point condensing temperature , 2006 .

[2]  Jeffrey M. Gordon,et al.  Thermodynamic modeling of reciprocating chillers , 1994 .

[3]  F. W. Yu,et al.  An alternative approach for the performance rating of air-cooled chillers used in air-conditioned buildings , 2006 .

[4]  Guoliang Ding,et al.  Performance analysis and improvement of air-to-water chiller for application in wide ambient temperature range , 2005 .

[5]  Jan F. Kreider,et al.  Heating and Cooling of Buildings: Design for Efficiency , 1994 .

[6]  Jeffrey M. Gordon,et al.  Centrifugal chillers: Thermodynamic modelling and a diagnostic case study , 1995 .

[7]  Shiming Deng,et al.  An Evaluation of the Rules of Thumb for Estimating Cooling Load for Office Buildings , 2001 .

[8]  Richard L. Scheaffer,et al.  Elementary Survey Sampling , 1971 .

[9]  Yung-Chung Chang,et al.  Optimal chiller loading by genetic algorithm for reducing energy consumption , 2005 .

[10]  W. L. Lee,et al.  Energy saving by realistic design data for commercial buildings in Hong Kong , 2001 .

[11]  Collin J. Watson,et al.  Statistics for Management and Economics , 1991 .

[12]  W. L. Lee,et al.  Simplifying energy performance assessment in the Hong Kong Building Environmental Assessment Method , 2001 .

[13]  J. Hair.  Multivariate data analysis , 1972 .

[14]  Deng Shiming,et al.  Sizing Replacement Chiller Plants , 2002 .

[15]  Jeffrey M. Gordon,et al.  How varying condenser coolant flow rate affects chiller performance: thermodynamic modeling and experimental confirmation , 2000 .

[16]  Fariborz Haghighat,et al.  Correlation based models for the simulation of energy performance of screw chillers , 2003 .

[17]  J Burnett BEng PhD CEng Rpe Fcibse Fhkie Fiee,et al.  Chiller Plant Sizing by Cooling Load Simulation as a Means to Avoid Oversized Plant , 1999 .

[18]  F. W. Yu,et al.  Applying condensing-temperature control in air-cooled reciprocating water chillers for energy efficiency , 2002 .

[19]  Yung-Chung Chang,et al.  A novel energy conservation method—optimal chiller loading , 2004 .