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Predictive control of refrigerated facilities for improved energy management. 2.

Author(s) : WALL J. R., BRASLAVSKY J. H., WARD J. K.

Type of article: Article, Case study

Summary

This article presents preliminary results from a real-world case study of predictive refrigeration control technology being developed by the CSIRO. The technology is designed to intelligently alter the operation of a refrigeration system by dynamically determining optimal operating temperature set-points and run-time schedules to reduce energy consumption and operating costs, while maintaining local constraints such as capacity control, defrost cycles, product quality and safety. Utilising “self-learning” model predictive control (MPC) techniques from control theory and computer science domains, the technology makes use of forecasting to move away from a reactionary control philosophy. By taking into account anticipated external conditions, electricity tariffs, and adaptively learning the thermal response of the system, more optimal control and pre-cooling strategies can be employed tailored to operating objectives, including minimizing operating cost and reducing energy consumption, while ensuring internal temperature conditions are satisfied.

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Format PDF

Pages: 32-35

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Details

  • Original title: Predictive control of refrigerated facilities for improved energy management. 2.
  • Record ID : 30014798
  • Languages: English
  • Source: EcoLibrium - vol. 14 - n. 3
  • Publication date: 2015/04

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