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An adaptive PID control method to improve the power tracking performance of solar photovoltaic air-conditioning systems

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  • Zhao, B.Y.
  • Zhao, Z.G.
  • Li, Y.
  • Wang, R.Z.
  • Taylor, R.A.

Abstract

In order to increase the utilization of solar energy to lower the effect of photovoltaic power output fluctuations on power grids, an adaptive PID control method to improve the power tracking performance of solar photovoltaic air-conditioners is proposed in this paper. In this method, a dynamic temperature set point of the indoor zone is generated at each control time step based on the difference between the air-conditioning load and photovoltaic generation. The theoretical analysis shows that the proposed control is essentially a feedforward feedback control where the air-conditioning system can predictably adjust the compressor frequency based on the knowledge of how the solar radiation affects the cooling load. A case study in Shanghai shows that the proposed control method is able to significantly improve the power tracking performance of the photovoltaic air-conditioner, where the Solar Fraction (SF) and the Self-Consumption Ratio (SCR) are improved from 82.74% to 88.11% and from 70.12% to 74.42% respectively, without violating the indoor thermal comfort, where Mean Absolute Error (MAE) from the temperature set point is decreased from 0.197 to 0.168. The tuning of the power difference factor ko will lead to monotonic changes of SF &SCR and a minimum MAE. When ko is well tuned, the proposed control can realize desirable system improvements of both the power tracking ability and the indoor temperature control accuracy. The idea of this paper could be easily modified to benefit other solar cooling applications and conventional air-conditioners.

Suggested Citation

  • Zhao, B.Y. & Zhao, Z.G. & Li, Y. & Wang, R.Z. & Taylor, R.A., 2019. "An adaptive PID control method to improve the power tracking performance of solar photovoltaic air-conditioning systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    • Handle: RePEc:eee:rensus:v:113:y:2019:i:c:31
    DOI: 10.1016/j.rser.2019.109250
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    References listed on IDEAS

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    Cited by:

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    2. Homod, Raad Z. & Gaeid, Khalaf S. & Dawood, Suroor M. & Hatami, Alireza & Sahari, Khairul S., 2020. "Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings," Applied Energy, Elsevier, vol. 271(C).
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    4. Jahangir Hossain & Aida. F. A. Kadir & Ainain. N. Hanafi & Hussain Shareef & Tamer Khatib & Kyairul. A. Baharin & Mohamad. F. Sulaima, 2023. "A Review on Optimal Energy Management in Commercial Buildings," Energies, MDPI, vol. 16(4), pages 1-40, February.
    5. 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).
    6. Yin, Linfei & Li, Yu, 2022. "Hybrid multi-agent emotional deep Q network for generation control of multi-area integrated energy systems," Applied Energy, Elsevier, vol. 324(C).

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