2008
DOI: 10.1016/j.apenergy.2008.02.008
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Optimization of water-cooled chiller system with load-based speed control

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Cited by 95 publications
(36 citation statements)
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“…The precise strategy sets an outlet water temperature similar to the target of 32.5°C, and the lowest energy consumption is at the expense of frequent ON/OFF switching (in this case, 34 times within a day). For the 0.5°C zone control, the outlet water temperature varies between 32.0 and 32.5°C with 16 increases sharply in the precise target scenario in Fig. 7.…”
Section: Implementation Of Temperature Zone Controlmentioning
confidence: 95%
See 1 more Smart Citation
“…The precise strategy sets an outlet water temperature similar to the target of 32.5°C, and the lowest energy consumption is at the expense of frequent ON/OFF switching (in this case, 34 times within a day). For the 0.5°C zone control, the outlet water temperature varies between 32.0 and 32.5°C with 16 increases sharply in the precise target scenario in Fig. 7.…”
Section: Implementation Of Temperature Zone Controlmentioning
confidence: 95%
“…Yu and Chan [16] used a load-based method to control the speed of cooling tower fans and condenser water pumps in order to improve the energy efficiency of a cooling tower system, and highlighted the need to widen the use of such control systems. Aha and Mitchell [17] proposed optimal supervisory control strategies for the set points (exact values) of controlled variables such as supply air, chilled water, and condenser water temperatures.…”
Section: Introductionmentioning
confidence: 99%
“…In this experiment, 25 drivers were involved in analyzing of the result. An automatic speed adapter was installed into each participant car [8]. This is meant to be used on the fuel pedal set not more than 50km/h.…”
Section: Historical Overview Of Intelligent Speed Assistance Systemmentioning
confidence: 99%
“…Larsen and Thybo (2004) Energy saving in commercial refrigeration describe a means for calculating the optimal pressure difference across the compressor in terms of energy consumption resulting in a 30 per cent decrease in energy consumption. Yu and Chan (2008) propose a model for analysing control procedures for condenser fans and extend this to provide fan control based on load which can provide performance improvements in the range of 7.8-113.2 per cent. Ghorbanian and Gholamrezaei (2009) describe the use of an artificial neural network for predicting compressor performance.…”
Section: Condition Monitoring Technologiesmentioning
confidence: 99%