Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77459
Title: Probabilistic and electricity saving analyses of Mist Coolers for Chiller System in a Hotel
Authors: Yu, FW 
Ho, WT 
Chan, KT 
Sit, RKY 
Keywords: Air-cooled chiller
Coefficient of performance
Genetic algorithm
Mist cooler
Random forest
Issue Date: 2017
Publisher: Elsevier
Source: Energy procedia, 2017, v. 143, p. 154-160 How to cite?
Journal: Energy procedia 
Abstract: This study investigates the optimization and electricity savings of an air-cooled chiller system with mist coolers. An air-cooled screw chiller having a nominal capacity of 282 kW was retrofitted with a mist cooler and dual condenser fan controls: fixed head pressure with constant speed and floating condensing temperature with variable speed. Comprehensive operating data logged at 5-min intervals were used to develop chiller models by random forest. The models served as a fitness function for genetic algorithm to predict the maximum coefficient of performance (COP) with optimal controlled variables under various operating conditions. Scatter plots of the optimal variables against the actual variables showed that to achieve the maximum COP, the set point of condensing temperature should be adjusted based on its measured value and the variation of heat rejection airflow rate. The probability of applying mist cooling was identified to be 70.91 - 78.33% for the simulated cooling load distribution of a hotel in a subtropical climate. Mist coolers with the optimal control brought electricity savings of 2.28 - 8.16%, depending on system configurations and condenser fan control modes. Fewer chillers in a system would result in more electricity savings from the optimal control while mist coolers complement the frequent full load operation of chillers to enhance electricity savings.
Description: 1st Joint Conference on World Engineers Summit - Applied Energy Symposium and Forum: Low Carbon Cities and Urban Energy, WES-CUE 2017, Singapore, 19-21 2017
URI: http://hdl.handle.net/10397/77459
EISSN: 1876-6102
DOI: 10.1016/j.egypro.2017.12.664
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