Fusion of redundant measurements for enhancing the reliability of total cooling load based chiller sequencing control |
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| Authors: | Gongsheng Huang Yongjun Sun Peng Li |
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| Affiliation: | aDivision of Building Science & Technology, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong;bDepartment of Building Services Engineering, the Hong Kong Polytechnic University, Kowloon, Hong Kong;cInstitute of Refrigeration and Thermal Engineering, Tongji University, Shanghai, China |
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| Abstract: | Total cooling load based chiller sequence in multiple-chiller plants is essentially the best approach to stage a chiller on or off in order to satisfy thermal comfort requirement and achieve energy efficiency simultaneously. In practice, however, this approach cannot be reliably implemented. The reason is the measurement of the cooling load of multiple-chiller plants is not always consistent enough for staging chillers on or off appropriately. Measurement uncertainties, including noises, outliers and biases, have a significant influence on the performance of the sequencing operation. This paper develops a strategy of fusing available redundant measurements to reduce the measurement uncertainties. With a moving window, the proposed strategy can (i) remove measurement outliers according to a calibrated Moffat distance between redundant measurements; (ii) reduce the influence of measurement noises by merging redundant measurements; and (iii) calibrate the bias of the merged measurements. Simulation studies are represented to show the merits of the proposed strategy for improving the reliability of the total cooling load based chiller sequencing control. |
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| Keywords: | Data fusion Chiller sequencing control Operation reliability Moffat distance Bias calibration |
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