| 논문명 |
인공지능 기반 사무소 건물의 직팽식 AHU-수랭식 VRF 시스템의 최적 제어 / Artificial Neural Network based Model Predictive Control for Optimization of Direct Expansion AHU-Water Source VRF System / 4-D 최상홍 인재상 수상자 특별세션 |
| 저자명 |
연상훈 ; 서병모 ; 이제헌 ; 문진우 ; 최종민 ; 이광호 |
| 수록사항 |
대한설비공학회 동계학술발표회 논문집 (2017-11) |
| 주제어 |
; Model Predictive Control ; Artificial Neural Network ; DX AHU-Water Source VRF |
| 요약2 |
ANN model is applied in this study for the optimized control of an advanced direct expansion (DX) air handling unit (AHU)-water source VRF system. After the development process of the ANN model, it was validated against the measured data and its performance along with MPC based optimization technique was evaluated. As a result, the cooling energy saving by 29% can be achieved by implementing ANN and MPC optimization, compared to conventionally controlled system. |
