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The Operational Efficiency of Commercial Food Refrigeration Systems: A Data Mining Approach

This work aims to enhance the existing fault-finding methodologies employed by a global multichannel retail organization, by enabling the identification of events that cause an increase in electricity demand of the refrigeration systems. This paper presents a methodology that analyzes data from refr...

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Bibliographic Details
Published in:ASHRAE transactions 2015-01, Vol.121, p.1C-1C
Main Authors: Spyrou, Maria S, Cook, Malcolm J, Mardaljevic, John, McMullen, Andrew, Lee, Richard, Pitcher, James
Format: Article
Language:English
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Summary:This work aims to enhance the existing fault-finding methodologies employed by a global multichannel retail organization, by enabling the identification of events that cause an increase in electricity demand of the refrigeration systems. This paper presents a methodology that analyzes data from refrigeration systems and enables a more straightforward identification of faults. This includes data for electricity consumption, compressor run times, percentage of refrigerant in the receiver, temperature of air on and off the evaporator, discharge and suction pressures, etc. Control strategies and maintenance schedules as well as meteorological data for each site were also collected and analyzed. Data mining methods were employed to remove known operational patterns and seasonal variations. Events that have had an effect on the electricity consumption of the system were highlighted and faults that have been identified by the existing methodology were filtered out. The resulting data set was then analyzed further to understand the events that increase the electricity demand of the systems in order to create an automatic identification method.
ISSN:0001-2505