Korean Journal of Air-Conditioning and Refrigeration Engineering (설비공학논문집)

The Society of Air-Conditioning and Refrigerating Engineers of Korea (대한설비공학회)
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Developing Optimal Pre-Cooling Model Based on Statistical Analysis of BEMS Data in Air Handling Unit

BEMS 데이터의 통계적 분석에 기반한 공조기 최적 예냉운전 모델 개발

  • Received : 2014.05.07
  • Accepted : 2014.08.19
  • Published : 2014.10.10
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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.

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References

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Cited by

  1. Recent Progress in Air-Conditioning and Refrigeration Research: A Review of Papers Published in the Korean Journal of Air-Conditioning and Refrigeration Engineering in 2014 vol.27, pp.7, 2015, https://doi.org/10.6110/KJACR.2015.27.7.380