A neural network controller for hydronic heating systems of solar buildings

Argiriou, A.A. and Bellas-Velidis, I. and Kummert, M. and Andre, P. (2004) A neural network controller for hydronic heating systems of solar buildings. Neural Networks, 17 (3). pp. 427-440. ISSN 0893-6080

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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.

  • Item type:Article
    ID code:5073
    Dates:
    Date
    Event
    April 2004
    Published
    Keywords:Artificial Neural Networks, Heating System Control, Hydronic Systems, Neural Controller, Energy Savings, Thermal Simulation, Mechanical engineering and machinery, Artificial Intelligence, Cognitive Neuroscience
    Subjects:Technology > Mechanical engineering and machinery
    Department:Faculty of Engineering > Mechanical and Aerospace Engineering
    Depositing user: Strathprints Administrator
    Date deposited:07 Jan 2008
    Last modified:20 Jan 2021 17:22
    URI:https://strathprints.strath.ac.uk/id/eprint/5073
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