| 논문명 |
인공지능을 활용한 Internet Data Centre의 제어조건별 에너지사용량 예측 모델 개발 / Development of IDC Energy Consumption Predicted Model by Control Conditions using AI |
| 저자명 |
고수민(Go, Su-Min) ; 박형은(Park, Hyung-Eun) ; 송영학(Song, Young-Hak) |
| 수록사항 |
한국건축친환경설비학회 논문집, Vol.18 No.5 (2024-10) |
| 주제어 |
인공지능; 예측 모델; Water-side Economizer; 데이터센터; PCC ; AI (Artificial Intelligence); Predicted Model; Water-side Economizer; Data Centre; PCC (Pearson Correlation Coefficient) |
| 요약2 |
Currently, most of the fluid-related elements such as chilled water, condensing water, and air volume of the internet data centre HVAC system are operated at fixed values annually or seasonally, which causes a decrease in energy efficiency. Therefore, it is necessary to establish a control method that minimizes energy usage by controlling the chilled water and condensing water temperature according to the outdoor air temperature. A model to predict energy usage was developed for efficient control of the entire system. Through PCC (Pearson Correlation Coefficient) analysis, elements affecting energy usage were selected as control variables, and energy usage at each temperature was derived by varying the chilled and condensing water temperature. Afterwards, a prediction model was developed using the results, and it was confirmed that the reliability was secured as CV (RMSE) was 2.19%, NMBE was 0.024%, MAPE was 0.72%, and R2 was 0.885. |
