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Refrigerant amount detection algorithm for a ground source heat pump unit

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  • Choi, Hangseok
  • Cho, Honghyun
  • Choi, Jong Min

Abstract

To make an energy efficient GSHP system, the heat pump unit should have high efficiency and be optimized well with other parts such as ground heat exchangers and pumps. The amount of refrigerant charge in the heat pump unit is one of the primary parameters influencing system performance. In the present study, the effects of off-design charge on the performance of a ground source heat pump unit are investigated by varying refrigerant charge amount, and the algorithm to predict refrigerant charge amount in the heat pump unit was developed. Undercharge or overcharge of refrigerant into the ground source heat pump unit degraded performance and deteriorated system reliability. Refrigerant flow control by an EEV compensated for refrigerant undercharge or overcharge fault. However, refrigerant charge amount should be detected to optimize the heat pump unit performance. In the first step to develop the algorithm of refrigerant amount detection, the subcooling and superheat at the adjusted EEV conditions are determined as recommended parameters, because they are not sensitive to the EWT of the OD HX. Finally, the subcooling is selected as a fault detection and diagnosis parameter about the refrigerant charge amount in the second screening analysis, because it is properly sensitive to charge amount. The algorithm to predict the refrigerant amount detection in the ground source heat pump unit was developed based on the test data and analysis. The refrigerant amount detection algorithm gave relatively good predictions within a relative deviation of 8.0%.

Suggested Citation

  • Choi, Hangseok & Cho, Honghyun & Choi, Jong Min, 2012. "Refrigerant amount detection algorithm for a ground source heat pump unit," Renewable Energy, Elsevier, vol. 42(C), pages 111-117.
  • Handle: RePEc:eee:renene:v:42:y:2012:i:c:p:111-117
    DOI: 10.1016/j.renene.2011.08.055
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    References listed on IDEAS

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    1. Hwang, Yujin & Lee, Jae-Keun & Jeong, Young-Man & Koo, Kyung-Min & Lee, Dong-Hyuk & Kim, In-Kyu & Jin, Sim-Won & Kim, Soo H., 2009. "Cooling performance of a vertical ground-coupled heat pump system installed in a school building," Renewable Energy, Elsevier, vol. 34(3), pages 578-582.
    2. Richard J. Green and Michael G. Pollitt, 2008. "Introduction," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 1-2.
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    Cited by:

    1. Jun Kwon Hwang & Patrick Nzivugira Duhirwe & Geun Young Yun & Sukho Lee & Hyeongjoon Seo & Inhan Kim & Mat Santamouris, 2020. "A Novel Hybrid Deep Neural Network Model to Predict the Refrigerant Charge Amount of Heat Pumps," Sustainability, MDPI, vol. 12(7), pages 1-23, April.
    2. Samuel Boahen & Kwang Ho Lee & Jong Min Choi, 2019. "Refrigerant Charge Fault Detection and Diagnosis Algorithm for Water-to-Water Heat Pump Unit," Energies, MDPI, vol. 12(3), pages 1-25, February.
    3. Samuel Boahen & Kwesi Mensah & Yujin Nam & Jong Min Choi, 2020. "Fault Detection Methodology for Secondary Fluid Flow Rate in a Heat Pump Unit," Energies, MDPI, vol. 13(11), pages 1-17, June.
    4. Hongzeng Ji & Jinchen Pei & Jingyang Cai & Chen Ding & Fen Guo & Yichun Wang, 2023. "Review of Recent Advances in Transcritical CO 2 Heat Pump and Refrigeration Cycles and Their Development in the Vehicle Field," Energies, MDPI, vol. 16(10), pages 1-21, May.

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