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An artificial neural network for predicting domestic hot water characteristics

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  • Christian Barteczko-Hibbert
  • Mark Gillott
  • Graham Kendall

Abstract

Domestic hot water (DHW) in the UK accounts for ∼7.5% of all energy use. For manufacturers of heating and hot water appliances to be in a position to respond to patterns of demand a full understanding of the effect of user-defined DHW profiles, different DHW systems and heating technologies are essential. This paper presents the prediction of the temperature characteristics of drawn DHW using artificial neural networks (NNs). We demonstrate whether, based on one NN model, different hot water system temperature loads can be accurately predicted. Two NN models were constructed and examined on a total of three systems. Both models trained on their associated systems produced errors of <11%; however, both NN models, when presented with unseen systems, produced large single errors. NN model 2 gave the lowest error when compared with NN model 1. Copyright The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

Suggested Citation

  • Christian Barteczko-Hibbert & Mark Gillott & Graham Kendall, 2009. "An artificial neural network for predicting domestic hot water characteristics," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 4(2), pages 112-119, April.
    • Handle: RePEc:oup:ijlctc:v:4:y:2009:i:2:p:112-119
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctp010
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    Cited by:

    1. Meireles, I. & Sousa, V. & Bleys, B. & Poncelet, B., 2022. "Domestic hot water consumption pattern: Relation with total water consumption and air temperature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    2. Bo Lin & Shuhui Li & Yang Xiao, 2017. "Optimal and Learning-Based Demand Response Mechanism for Electric Water Heater System," Energies, MDPI, vol. 10(11), pages 1-17, October.
    3. Linas Gelažanskas & Kelum A. A. Gamage, 2015. "Forecasting Hot Water Consumption in Residential Houses," Energies, MDPI, vol. 8(11), pages 1-16, November.
    4. Wojciech Rzeźnik & Ilona Rzeźnik & Paweł Hara, 2022. "Comparison of Real and Forecasted Domestic Hot Water Consumption and Demand for Heat Power in Multifamily Buildings, in Poland," Energies, MDPI, vol. 15(19), pages 1-17, September.

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