Share

PREDICTION OF THERMAL STORAGE LOADS USING A NEURAL NETWORK.

Author(s) : FERRANO F. J. Jr, WONG K. V.

Summary

THE OBJECTIVE OF THE WORK IS TO DEVELOP A NEURAL NETWORK COMPUTER PROGRAM TO PREDICT THE NEXT-DAY COOLING LOAD AND USE THIS PREDICTION IN CONJUNCTION WITH A REAL-TIME EXPERT SYSTEM TO SIMULATE MANAGEMENT OF A COLD THERMAL STORAGE SYSTEM. THE NEXT-DAY COOLING LOAD PREDICTION ALLOWS THEICE THERMAL STORAGE SYSTEM TO MAXIMIZE OFF-PEAK UTILITY RATES AND MINIMIZE MECHANICAL SYSTEM OPERATION. THE TECHNIQUE USED TO PREDICT THE REQUIRED ICE PRODUCTION IS CONDUCTED BY TRAINING A NEURAL NETWORK WITH THE USE OF DEFINITION, FACT,AND TRAINING NETWORK FILES. THE RESULTING COLD THERMAL STORAGE PREDICTION IS ENTERED INTO A REAL-TIME EXPERT SYSTEM FOR THE CONTROL OF THE OVERNIGHT CHILLER OPERATION AND ICE STORAGE PRODUCTION.

Details

  • Original title: PREDICTION OF THERMAL STORAGE LOADS USING A NEURAL NETWORK.
  • Record ID : 1992-0859
  • Languages: English
  • Publication date: 1990
  • Source: Source: ASHRAE Trans.
    vol. 96; n. 2; 723-726; 4 fig.; 18 ref.
  • Document available for consultation in the library of the IIR headquarters only.

Indexing