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Data-driven modeling approach for performance analysis and optimal operation of a cooling tower

Authors :
Shi-Shang Jang
Chan-Wei Wu
Shyan-Shu Shieh
Jian-Guo Wang
David Shan-Hill Wong
Source :
Journal of the Taiwan Institute of Chemical Engineers. 45:180-185
Publication Year :
2014
Publisher :
Elsevier BV, 2014.

Abstract

This paper proposes a data-driven adaptive modeling approach to investigate the performance and optimal operation of a cooling tower for energy conservation. To achieve this aim, the cooling tower process was first characterized by an adaptive model with nonnegative garrote (NNG) variable selection procedure, which ensured a compact and robust input–output relation. Owing to the high accuracy of the obtained model, implementing the optimal operation strategy for energy saving became readily practicable. Subsequently, on the basis of the statistical results of NNG variable selection, the effects of ambient air temperature and humidity on the cooling capacity of the tower were investigated by principal component analysis (PCA). Finally, the optimal strategy of fan operation was proposed and its implementation was virtually studied based on data from the actual operation of a cooling tower, which showed that there was considerable room for energy conservation. This is the first attempt to use the NNG variable selection method for developing model for cooling tower and to propose a model-based control scheme for operating a cooling tower.

Details

ISSN :
18761070
Volume :
45
Database :
OpenAIRE
Journal :
Journal of the Taiwan Institute of Chemical Engineers
Accession number :
edsair.doi...........292b3da14c6fcb78a91855179975d4f6