Prediction of thermal storage loads using a neural network

Frank J. Ferrano, Kaufui Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Citations (Scopus)

Abstract

The objective of the present 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 the ice thermal storage system to maximize off-peak utility rates and minimize mechanical system operation. The management system is designed to be used by mechanical engineers in the field of air-conditioning control and maintenance. The computer program is written with the aid of commercially available neural network computer software. The temperature data base includes hourly ambient temperature values for a typical year in Miami, Florida. The technique used to predict the required ice production of the thermal storage system is conducted by training a neural network with the use of definition, fact, and training network files. Once the network is trained, any temperature pattern for a 24-hour period can be used to calculate the required next-day cooling load. Neural network training included unique temperature patterns for 'cold' and 'warm' weather fronts, as well as seasonally adjusted 'normal' temperature patterns. The resulting cold thermal storage prediction is then entered into a real-time expert system for the control of the overnight chiller operation and ice storage production.

Original languageEnglish (US)
Title of host publicationASHRAE Transactions
Editors Anon
PublisherPubl by ASHRAE
Pages723-726
Number of pages4
Editionpt 2
StatePublished - 1990
Event1990 Annual Meeting of the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Technical and Symposium Papers - St. Louis, MO, USA
Duration: Jun 10 1990Jun 13 1990

Other

Other1990 Annual Meeting of the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Technical and Symposium Papers
CitySt. Louis, MO, USA
Period6/10/906/13/90

Fingerprint

Neural networks
Ice
Cooling
Expert systems
Computer program listings
Temperature
Air conditioning
Hot Temperature
Engineers

ASJC Scopus subject areas

  • Fluid Flow and Transfer Processes

Cite this

Ferrano, F. J., & Wong, K. (1990). Prediction of thermal storage loads using a neural network. In Anon (Ed.), ASHRAE Transactions (pt 2 ed., pp. 723-726). Publ by ASHRAE.

Prediction of thermal storage loads using a neural network. / Ferrano, Frank J.; Wong, Kaufui.

ASHRAE Transactions. ed. / Anon. pt 2. ed. Publ by ASHRAE, 1990. p. 723-726.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ferrano, FJ & Wong, K 1990, Prediction of thermal storage loads using a neural network. in Anon (ed.), ASHRAE Transactions. pt 2 edn, Publ by ASHRAE, pp. 723-726, 1990 Annual Meeting of the American Society of Heating, Refrigerating and Air-Conditioning Engineers, Technical and Symposium Papers, St. Louis, MO, USA, 6/10/90.
Ferrano FJ, Wong K. Prediction of thermal storage loads using a neural network. In Anon, editor, ASHRAE Transactions. pt 2 ed. Publ by ASHRAE. 1990. p. 723-726
Ferrano, Frank J. ; Wong, Kaufui. / Prediction of thermal storage loads using a neural network. ASHRAE Transactions. editor / Anon. pt 2. ed. Publ by ASHRAE, 1990. pp. 723-726
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