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Investigation of Heat Pump Operation Strategies with Thermal Storage in Heating Conditions

Author

Listed:
  • Wangsik Jung

    (Department of Mechanical Engineering, Graduate School, Kookmin University, Seoul 02707, Korea)

  • Dongjun Kim

    (Department of Mechanical Engineering, Graduate School, Kookmin University, Seoul 02707, Korea)

  • Byung Ha Kang

    (School of Mechanical Engineering, Kookmin University, Seoul 20707, Korea)

  • Young Soo Chang

    (School of Mechanical Engineering, Kookmin University, Seoul 20707, Korea)

Abstract

A heat pump with thermal storage system is a system that operates a heat pump during nighttime using inexpensive electricity; during this time, the generated thermal energy is stored in a thermal storage tank. The stored thermal energy is used by the heat pump during daytime. Based on a model of a dual latent thermal storage tank and a heat pump, this study conducts control simulations using both conventional and advanced methods for heating in a building. Conventional methods include the thermal storage priority method and the heat pump priority method, while advanced approaches include the region control method and the dynamic programming method. The heating load required for an office building is identified using TRNSYS (Transient system simulation), used for simulations of various control methods. The thermal storage priority method shows a low coefficient of performance (COP), while the heat pump priority method leads to high electricity costs due to the low use of thermal storage. In contrast, electricity costs are lower for the region control method, which operates using the optimal part load ratio of the heat pump, and for dynamic programming, which operates the system by following the minimum cost path. According to simulation results for the winter season, the electricity costs using the dynamic programming method are 17% and 9% lower than those of the heat pump priority and thermal storage priority methods, respectively. The region control method shows results similar to the dynamic programming method with respect to electricity costs. In conclusion, advanced control methods are proven to have advantages over conventional methods in terms of power consumption and electricity costs.

Suggested Citation

  • Wangsik Jung & Dongjun Kim & Byung Ha Kang & Young Soo Chang, 2017. "Investigation of Heat Pump Operation Strategies with Thermal Storage in Heating Conditions," Energies, MDPI, vol. 10(12), pages 1-23, December.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:2020-:d:121279
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    References listed on IDEAS

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    3. Baeten, Brecht & Rogiers, Frederik & Helsen, Lieve, 2017. "Reduction of heat pump induced peak electricity use and required generation capacity through thermal energy storage and demand response," Applied Energy, Elsevier, vol. 195(C), pages 184-195.
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    Cited by:

    1. Emanuele Bonamente & Andrea Aquino, 2019. "Environmental Performance of Innovative Ground-Source Heat Pumps with PCM Energy Storage," Energies, MDPI, vol. 13(1), pages 1-15, December.
    2. Yapeng Ren & Xinli Lu & Wei Zhang & Jiaqi Zhang & Jiali Liu & Feng Ma & Zhiwei Cui & Hao Yu & Tianji Zhu & Yalin Zhang, 2022. "Preliminary Study on Optimization of a Geothermal Heating System Coupled with Energy Storage for Office Building Heating in North China," Energies, MDPI, vol. 15(23), pages 1-23, November.
    3. Peter Sivák & Peter Tauš & Radim Rybár & Martin Beer & Zuzana Šimková & František Baník & Sergey Zhironkin & Jana Čitbajová, 2020. "Analysis of the Combined Ice Storage (PCM) Heating System Installation with Special Kind of Solar Absorber in an Older House," Energies, MDPI, vol. 13(15), pages 1-20, July.
    4. Jacek Kropiwnicki & Mariusz Furmanek & Andrzej Rogala, 2021. "Modular Approach for Modelling Warming up Process in Water Installations with Flow-Regulating Elements," Energies, MDPI, vol. 14(15), pages 1-17, July.

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