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http://dx.doi.org/10.6110/KJACR.2014.26.10.467

Developing Optimal Pre-Cooling Model Based on Statistical Analysis of BEMS Data in Air Handling Unit  

Choi, Sun-Kyu (Green Business Team, SK telecom)
Kwak, Ro-Yeul (Department of Architectural engineering, Hannam University)
Goo, Sang-Heon (Department of Architectural Technology Team, SK E&C)
Publication Information
Korean Journal of Air-Conditioning and Refrigeration Engineering / v.26, no.10, 2014 , pp. 467-473 More about this Journal
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.
Keywords
BEMS; AHU; Pre-Cooling; MRA Method; On-going commissioning;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
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