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Modeling, calibration, and sensitivity analysis of direct expansion AHU-Water source VRF system

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  • Kang, Won Hee
  • Lee, Jong Man
  • Yeon, Sang Hun
  • Park, Min Kyeong
  • Kim, Chul Ho
  • Lee, Je Hyeon
  • Moon, Jin Woo
  • Lee, Kwang Ho

Abstract

The term variable refrigerant flow (VRF) refers to the ability of a system to control the amount of refrigerant flow rate, which enables the use of many evaporators (indoor units) of differing capacities and configurations connected to a single condensing unit. The feature offers individualized comfort control and simultaneous heating and cooling in different zones. In this study, a performance prediction model of a DX AHU (direct expansion air handling unit)-water source VRF heat pump system was constructed based on EnergyPlus, MATLAB and BCVTB using actual measured data. Advanced control logic using an EMS function was used in EnergyPlus for outdoor unit modeling, while prediction models for a cooling tower, boiler and pump were constructed in Matlab. In order to predict the model’s quantitative energy consumption, performance curves and power consumption were calculated. The calculations were checked by comparing them with actual data and the performance curves were then calibrated. The validity test results after the calibrations showed reliable results with a Cv(RMSE) of 14.5%. Based on these results, we performed a sensitivity analysis of the DX AHU-water source VRF system’s cooling energy according to the AHU discharge air temperature, refrigerant evaporative temperature and condenser fluid temperature and flow rate.

Suggested Citation

  • Kang, Won Hee & Lee, Jong Man & Yeon, Sang Hun & Park, Min Kyeong & Kim, Chul Ho & Lee, Je Hyeon & Moon, Jin Woo & Lee, Kwang Ho, 2020. "Modeling, calibration, and sensitivity analysis of direct expansion AHU-Water source VRF system," Energy, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:energy:v:199:y:2020:i:c:s0360544220305429
    DOI: 10.1016/j.energy.2020.117435
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    References listed on IDEAS

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    1. Yu, Xinqiao & Yan, Da & Sun, Kaiyu & Hong, Tianzhen & Zhu, Dandan, 2016. "Comparative study of the cooling energy performance of variable refrigerant flow systems and variable air volume systems in office buildings," Applied Energy, Elsevier, vol. 183(C), pages 725-736.
    2. Li, Ning & Xia, Liang & Shiming, Deng & Xu, Xiangguo & Chan, Ming-Yin, 2012. "Dynamic modeling and control of a direct expansion air conditioning system using artificial neural network," Applied Energy, Elsevier, vol. 91(1), pages 290-300.
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    Cited by:

    1. Shazia Noor & Hadeed Ashraf & Muhammad Sultan & Zahid Mahmood Khan, 2020. "Evaporative Cooling Options for Building Air-Conditioning: A Comprehensive Study for Climatic Conditions of Multan (Pakistan)," Energies, MDPI, vol. 13(12), pages 1-23, June.
    2. Je-Hyeon Lee & Young-hak Song, 2023. "Annual Effect of the VRF Control Algorithm in Response to the TOU Rate Plan," Sustainability, MDPI, vol. 15(10), pages 1-14, May.
    3. Dongsu Kim & Jongman Lee & Sunglok Do & Pedro J. Mago & Kwang Ho Lee & Heejin Cho, 2022. "Energy Modeling and Model Predictive Control for HVAC in Buildings: A Review of Current Research Trends," Energies, MDPI, vol. 15(19), pages 1-30, October.

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