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Study on matching characteristics of photovoltaic disturbance and refrigeration compressor in solar photovoltaic direct-drive air conditioning system

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Listed:
  • Li, Guoliang
  • Han, Youhua
  • Li, Ming
  • Luo, Xi
  • Xu, Yongfeng
  • Wang, Yunfeng
  • Zhang, Ying

Abstract

This paper presents a 3 HP solar direct-drive photovoltaic air conditioning system which operates without batteries, ice thermal storage is used to store solar energy. The refrigeration compressor will suffer from loss of power even cannot startup or shut down if the PV power generation suddenly fluctuates. In the case of the solar radiation fluctuations to keep the system running continuously and steadily, that requires a proper system design to match the power consumption of solar air conditioning system with a proper PV capacity, matching an adaptive controller and a suited compressor simultaneously. Solar air conditioners with different capacity of PV panel, with and without MPPT controller and different types compressors were built and tested outdoors to experimentally investigate the matching characteristics of photovoltaic disturbance and refrigeration compressor. The experimental results of the system with a variable speed compressor and a MPPT controller have shown good ice-making performance and reliable operation as well as a great improvement in the available solar energy. Finally, the highest system COP reached 0.289 when the cumulative daily total radiation was 18.2 MJ/m2 in Kunming, China. The research work shows that the direct drive ice storage by solar photovoltaic system has a certain application prospect in the regions where the electricity is tight but requiring cooling.

Suggested Citation

  • Li, Guoliang & Han, Youhua & Li, Ming & Luo, Xi & Xu, Yongfeng & Wang, Yunfeng & Zhang, Ying, 2021. "Study on matching characteristics of photovoltaic disturbance and refrigeration compressor in solar photovoltaic direct-drive air conditioning system," Renewable Energy, Elsevier, vol. 172(C), pages 1145-1153.
    • Handle: RePEc:eee:renene:v:172:y:2021:i:c:p:1145-1153
    DOI: 10.1016/j.renene.2021.03.110
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    References listed on IDEAS

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    Cited by:

    1. Zhou, Xiaoyan & Zhang, Ying & Ma, Xun & Li, Guoliang & Wang, Yunfeng & Hu, Chengzhi & Liang, Junyu & Li, Ming, 2022. "Performance characteristics of photovoltaic cold storage under composite control of maximum power tracking and constant voltage per frequency," Applied Energy, Elsevier, vol. 305(C).
    2. Li, Houpei & Li, Jun & Li, Sihui & Peng, Jinqing & Ji, Jie & Yan, Jinyue, 2023. "Matching characteristics and AC performance of the photovoltaic-driven air conditioning system," Energy, Elsevier, vol. 264(C).
    3. Gao, Fang & Hu, Rongzhao & Yin, Linfei, 2023. "Variable boundary reinforcement learning for maximum power point tracking of photovoltaic grid-connected systems," Energy, Elsevier, vol. 264(C).

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