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Predicting central plant HVAC equipment performance using neural networks: laboratory system test results.

Author(s) : MASSIE D. D., CURTISS P. S., KREIDER J. F.

Summary

Adaptive and predictive neural network models have been developed for a chiller and ice thermal storage tank of a central plant HVAC system. With relatively few input parameters, equipment performance is modeled without the use of first principles. Once trained, the models quickly predict output with relatively few calculations and self-calibrate, making them ideal for use with real systems that use adaptive and predictive controllers.

Details

  • Original title: Predicting central plant HVAC equipment performance using neural networks: laboratory system test results.
  • Record ID : 1999-2933
  • Languages: English
  • Source: ASHRAE Transactions. 1998 Winter Meeting, San Francisco, CA.
  • Publication date: 1998
  • Document available for consultation in the library of the IIR headquarters only.

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