Abstract
Artificial neural network (ANN) is used as prediction tool in various solar systems for predicting the various performance parameters. In this paper ANN is used to predict the outlet water temperature of the water in tube type evacuated solar collectors. The ANN model is trained and tested for single collector and two collectors connected in series. The ANN model is trained by providing time of the day, solar radiation, relative humidity and air temperature as the input parameters and experimentally measured outlet water temperature as the target value. The error analysis shows lower RMSE and MAE value for the developed ANN model. For the case of single collector RMSE and MAE is 2.00 and 1.63 while for the case of two collectors in series, it is 1.04 and 0.80, respectively. This shows the good agreement between the predicted and experimental values. The developed ANN model helps in determining the outlet water temperature at different locations having different climate and ambient parameter than the place where collector is manufactured and tested.
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Singh, P., Gaur, M.K. (2023). Application of ANN to Predict Outlet Water Temperature of Evacuated Water in Tube Type Solar Collector. In: Kumar, S., Hiranwal, S., Purohit, S.D., Prasad, M. (eds) Proceedings of International Conference on Communication and Computational Technologies . Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-3951-8_12
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DOI: https://doi.org/10.1007/978-981-19-3951-8_12
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