| Title |
Development of Performance Prediction Model for Integrated System Combining Photovoltaic-thermal and Air Source Heat Pump based on Deep Neural Network |
| Authors |
Sangmu Bae ; Hobyung Chae ; Jinhwan Oh ; Soowon Chae ; Jin Woo Moon ; Yujin Nam |
| DOI |
https://doi.org/10.6110/KJACR.2022.34.8.390 |
| Keywords |
공기열원 히트펌프; 심층신경망; 융복합 시스템; 태양광열 Air source heat pump; Deep neural network; Integrated system; Photovoltaic-thermal |
| 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. |