Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25237
Title: Building instantaneous cooling load fused measurement : multiple-sensor-based fusion versus chiller-model-based fusion
Authors: Huang, G
Sun, Y
Wang, S 
Issue Date: 2013
Source: Building services engineering research and technology, 2013, v. 34, no. 2, p. 177-194
Abstract: Building instantaneous cooling load is an essential variable for the optimisation and supervisory control of chiller plants, which can be estimated according to the measurements of the chilled water flow rate and the chilled water temperature drop through the chiller plants. Since the measurements of the flow rate and the temperature drop suffer from measurement uncertainties, two different fusion approaches have been developed to improve the measurement accuracy of the cooling load. One is the chiller-model-based fusion (CMF) approach and the other is the multiple-sensor-based fusion (MSF) approach. The two approaches use different disciplines to fuse available measurements. This paper describes a comparison study of the two fusion approaches, which analyses the influences of cooling load conditions of chiller plants on the performance of the two approaches. A case study based on computer simulation shows that the CMF approach is able to produce a better result when the cooling load condition is relatively stable and redundant measurements of the chilled water temperature and flow rate are deficient; while when the redundant measurements are abundant the MSF approach can produce a better result.Practical applications: The study aims to identify the advantage/disadvantage of two fusion approaches proposed for improving the accuracy of building cooling load measurement under different load conditions. For practical applications, results may be used as a guideline for selecting a proper fusion approach for a particular chiller plant according to the characteristics of its actual load condition.
Keywords: Building instantaneous cooling load
data fusion
measurement uncertainty
redundant measurement
Publisher: SAGE Publications
Journal: Building services engineering research and technology 
ISSN: 0143-6244
EISSN: 1477-0849
DOI: 10.1177/0143624411432651
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