A neural network controller for hydronic heating systems of solar buildings

A.A. Argiriou, I. Bellas-Velidis, M. Kummert, P. Andre

Research output: Contribution to journalArticle

67 Citations (Scopus)

Abstract

An artificial neural network (ANN)-based controller for hydronic heating plants of buildings is presented. The controller has forecasting capabilities: it includes a meteorological module, forecasting the ambient temperature and solar irradiance, an indoor temperature predictor module, a supply temperature predictor module and an optimizing module for the water supply temperature. All ANN modules are based on the Feed Forward Back Propagation (FFBP) model. The operation of the controller has been tested experimentally, on a real-scale office building during real operating conditions. The operation results were compared to those of a conventional controller. The performance was also assessed via numerical simulation. The detailed thermal simulation tool for solar systems and buildings TRNSYS was used. Both experimental and numerical results showed that the expected percentage of energy savings with respect to a conventional controller is of about 15% under North European weather conditions.
LanguageEnglish
Pages427-440
Number of pages13
JournalNeural Networks
Volume17
Issue number3
DOIs
Publication statusPublished - Apr 2004

Fingerprint

Solar buildings
Hot water heating
Solar System
Heating
Neural networks
Controllers
Temperature
Water Supply
Weather
Office buildings
Solar system
Backpropagation
Water supply
Hot Temperature
Energy conservation
Computer simulation

Keywords

  • Artificial Neural Networks
  • Heating System Control
  • Hydronic Systems
  • Neural Controller
  • Energy Savings
  • Thermal Simulation

Cite this

Argiriou, A. A., Bellas-Velidis, I., Kummert, M., & Andre, P. (2004). A neural network controller for hydronic heating systems of solar buildings. Neural Networks, 17(3), 427-440. https://doi.org/10.1016/j.neunet.2003.07.001
Argiriou, A.A. ; Bellas-Velidis, I. ; Kummert, M. ; Andre, P. / A neural network controller for hydronic heating systems of solar buildings. In: Neural Networks. 2004 ; Vol. 17, No. 3. pp. 427-440.
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Argiriou, AA, Bellas-Velidis, I, Kummert, M & Andre, P 2004, 'A neural network controller for hydronic heating systems of solar buildings' Neural Networks, vol. 17, no. 3, pp. 427-440. https://doi.org/10.1016/j.neunet.2003.07.001

A neural network controller for hydronic heating systems of solar buildings. / Argiriou, A.A.; Bellas-Velidis, I.; Kummert, M.; Andre, P.

In: Neural Networks, Vol. 17, No. 3, 04.2004, p. 427-440.

Research output: Contribution to journalArticle

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AU - Bellas-Velidis, I.

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AB - An artificial neural network (ANN)-based controller for hydronic heating plants of buildings is presented. The controller has forecasting capabilities: it includes a meteorological module, forecasting the ambient temperature and solar irradiance, an indoor temperature predictor module, a supply temperature predictor module and an optimizing module for the water supply temperature. All ANN modules are based on the Feed Forward Back Propagation (FFBP) model. The operation of the controller has been tested experimentally, on a real-scale office building during real operating conditions. The operation results were compared to those of a conventional controller. The performance was also assessed via numerical simulation. The detailed thermal simulation tool for solar systems and buildings TRNSYS was used. Both experimental and numerical results showed that the expected percentage of energy savings with respect to a conventional controller is of about 15% under North European weather conditions.

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KW - Heating System Control

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