Abstract
The purpose of this study was to develop the performance prediction model for integrated system combining photovoltaic-thermal and air source heat pump, based on a deep neural network (DNN) model. This paper describes the overall procedure of constructing the DNN model, to predict the performance of the integrated system such as data collection method, data set configuration, and the DNN model structure. To verify the reliability of the performance prediction model based on DNN model, the coefficient of variation root mean square error (CV(RMSE)) proposed by American Society of Heating, Refrigerating and Air-conditioning Engineers Guideline 14 was used. The CV(RMSE) between the predicted results of the DNN model, and the output variables was calculated as 5%. Thus, the reliability of the performance prediction model based on the DNN model was verified, and the performance prediction accuracy was similar to the energy simulation model.
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