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An Analysis Method for Operations of Hot Water Heaters by Artificial Neural Networks
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Authors tried to apply an Artificial Neural Network (ANN) to estimation of state of building systems. The systems used in this study were gas combustion water heaters. Empirical equations to estimate gas consumption from measureble properies such as exhaust gas temperature and electric current were obtained from experiments. Some operational modes, which were hot water supply, additional combustion to keep water temperature in bathtub, and anti-frozen heater for plumbing, were needed to be identified. Electric currents, temperature of supply water and exhaust gas had been measured as operational indices. ANN was applied to identify modes automatically using learning algorism. The modes were porperly identified and gas consumption was estimated in practical accuracy.
Yamaha, M.; Takahashi, M. (2004). An Analysis Method for Operations of Hot Water Heaters by Artificial Neural Networks. Energy Systems Laboratory (http://esl.tamu.edu); Texas A&M University (http://www.tamu.edu). Available electronically from