| Title |
Developing Optimal Pre-Cooling Model Based on Statistical Analysis of BEMS Data in Air Handling Unit |
| Authors |
최선규(Sun-Kyu Choi) ; 곽노열(Ro-Yeul, Kwak) ; 구상헌(Sang-Heon Goo) |
| DOI |
http://dx.doi.org/10.6110/KJACR.2014.26.10.467 |
| Keywords |
건물 에너지관리시스템 ; 공기조화기 ; 예냉 ; 다중회귀분석기법 ; 지속적 커미셔닝 BEMS ; AHU ; Pre-Cooling ; MRA Method ; On-going commissioning |
| Abstract |
Since the operating conditions of HVAC systems are different from those for which they are designed, on-going commissioning is required to optimize the energy consumed and the environment in the building. This study presents a methodology to analyze operational data and its applications. A predicted operation model is to be produced through a statistical data analysis using multiple regressions in SPSS. In this model, the dependent variable is the pre-cooling time, and the independent variables include the power output of the supply air inverter during pre-cooling, the supply air set temperature during pre-cooling, the indoor temperature-indoor set temperature just before pre-cooling, supply heat capacity, and the lowest outdoor air temperature during non-cooling/non-heating hours. The correlation coefficient R2 of the multiple regression model between the pre-cooling hour and the internal/external factors is of 0.612, and this could be used to provide information related to energy conservation and operating guidance. |