Research on operating parameters and energy consumption of cold store based on rough set theory

  • Authors:

  • Jianyi Zhang;Ying Xu;Fei Chen

  • Affiliations:

  • College of Mechanical Engineering, Jimei University, Xiamen, China;College of Food Science, Shanghai Ocean University, Shanghai, China and College of Mechanical Engineering, Jimei University, Xiamen, China;College of Mechanical Engineering, Jimei University, Xiamen, China

  • Venue:
  • FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
  • Year:
  • 2009

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Abstract

Rough set theory is applied to analyze the energy consumption of an industrial cold storage facility for the first time. The features of rough set theory in data extraction are analyzed. The operating parameters collected in a sample refrigerating plant between 2003 and 2007 are used to build an effective sample database. The minimal attribute set is obtained by extracting key attributes from the database, based on rough set theory. From the case study, it is found that rough set theory can be used for the data mining of refrigerating plants and the knowledge rules are discovered from the database. Based on the rules and knowledge of refrigeration, mathematical models are constructed. The rules will establish the best operating conditions for industrial refrigerating plants to improve energy efficiency. Some suggestions for energy conservation are proposed.