@inproceedings{3397ff3f62bf45eaa51dd96563d7828f,
title = "Artificial neural network based optimized control of condenser water temperature set-point",
abstract = "In this study, we developed an artificial neural network based real-time predictive control and optimization model to compare and analyze the difference in total energy consumption when the condenser water outlet temperature coming out of the cooling tower is fixed and when real-time control of the condenser water outlet temperature through the optimal ANN model is applied. An ANN model was developed through MATLAB's built-in neural network toolbox functionality to predict total energy consumption. The model accuracy of the ANN was examined by applying Cv(RMSE), a statistical concept that shows the overall accuracy of the predicted values, and as a result, it was found to have a Cv(RMSE) value of approximately 25%. In addition, the predictive control algorithm was able to reduce cooling energy consumption by about 5.6% compared to the conventional control strategy that fix condenser water temperature set-point to constantly 30°C. ",
keywords = "ANN (artificial neural network), BCVTB (building controls virtual test bed), Chiller, Condenser water temperature, Cooling tower, EnergyPlus, HVAC (heating, ventilation, and air conditioning) system, MATLAB",
author = "Kim, {Tae Young} and Lee, {Jong Man} and Hong, {Sung Hyup} and Choi, {Jong Min} and Lee, {Kwang Ho}",
note = "Funding Information: This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea Government(MSIT, MOE) (No. 2019M3E7A1113095) Publisher Copyright: Copyright {\textcopyright} 2021 by ASME.; ASME 2021 15th International Conference on Energy Sustainability, ES 2021 ; Conference date: 16-06-2021 Through 18-06-2021",
year = "2021",
doi = "10.1115/ES2021-63735",
language = "English",
series = "Proceedings of the ASME 2021 15th International Conference on Energy Sustainability, ES 2021",
publisher = "American Society of Mechanical Engineers (ASME)",
booktitle = "Proceedings of the ASME 2021 15th International Conference on Energy Sustainability, ES 2021",
}
