컨테인먼트형 데이터센터 최적 제어 알고리즘을 위한 열환경 예측모델 개발

• Published in: KIEAE Journal Vol. 20; no. 5; pp. 159 - 164
• Main Authors: 최영재(Young Jae Choi), 박보랑(Bo Rang Park), 조지현(Ji Hyeon Cho), 문진우(Jin Woo Moon)
• Format: Journal Article
• Language: Korean
• Published: 한국생태환경건축학회 01.10.2020
• Subjects: 건축공학; 기계학습; 데이터센터; Data Center; Machine Learning; 최적 제어알고리즘; Optimal Control Algorithm
• ISSN: 2288-968X; 2288-9698
• DOI: 10.12813/kieae.2020.20.5.159

Purpose: This study aimed at developing a temperature prediction model for a containment data center. The predictive model must be guaranteed with stability and accuracy in order to be used for real-time control. Therefore, statistical evaluation was conducted to verify the prediction performance of the proposed model. Method: The predictive models were developed using four representative machine learning algorithms. A thermodynamic based containment data center and cooling system were modeled by MATLAB & Simulink software. The initial and optimized models were evaluated by R2 and Cv(RMSE), and the model with the highest performance was applied to the simulation. Result: In the initial models, RF and ANN presented highest accuracy on R2 (0.89) and Cv(RMSE) (17.85%), respectively. After the optimization, ANN presented the best prediction performance on both R2 (0.99) and Cv(RMSE) (0.94%). The result supports the accuracy and stability of the ANN model to be used for real-time control, and based on which the optimal control algorithm will be developed on further study. KCI Citation Count: 3