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Development of a PV performance model for power output simulation at minutely resolution

Author

Listed:
  • Li, Y.
  • Chen, X.M.
  • Zhao, B.Y.
  • Zhao, Z.G.
  • Wang, R.Z.

Abstract

Because of the transient and non-linear characteristics of solar irradiance, simulation at sub-hourly resolution, e.g., at the order of 10 min or less, becomes more essential. In this paper, a PV performance model at sub-hourly resolution based on global horizontal irradiance is developed and validated by the minutely on-site measurements under different weather conditions. Then, a simulation at minutely resolution is carried out for the year 2015 in Zhuhai, China. The results are compared with the simulation results at hourly resolution. It is found that simulation at minutely resolution can reflect the real characteristics of power output fluctuations. The differences of daily energy output between hourly and minutely resolution are in the range of −2%∼10%, and it seems that the higher values of daily clearness index will lead to higher values of daily differences. The differences of monthly and yearly energy output are −1∼7.5% and 2.46%, respectively. The differences for different time scales indicate that for a longer time period (e.g., one year), the simulated energy output at hourly resolution will go closer with that at minutely resolution.

Suggested Citation

  • Li, Y. & Chen, X.M. & Zhao, B.Y. & Zhao, Z.G. & Wang, R.Z., 2017. "Development of a PV performance model for power output simulation at minutely resolution," Renewable Energy, Elsevier, vol. 111(C), pages 732-739.
    • Handle: RePEc:eee:renene:v:111:y:2017:i:c:p:732-739
    DOI: 10.1016/j.renene.2017.04.049
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    Citations

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    Cited by:

    1. Siwei Lou & Wenqiang Chen & Danny H.W. Li & Mo Wang & Hainan Chen & Isaac Y.F. Lun & Dawei Xia, 2019. "Tilted Photovoltaic Energy Outputs in Outdoor Environments," Sustainability, MDPI, vol. 11(21), pages 1-17, October.
    2. Sato, Daisuke & Yamagata, Yuki & Hirata, Kenji & Yamada, Noboru, 2020. "Mathematical power-generation model of a four-terminal partial concentrator photovoltaic module for optimal sun-tracking strategy," Energy, Elsevier, vol. 213(C).
    3. Giovanni Nobile & Ester Vasta & Mario Cacciato & Giuseppe Scarcella & Giacomo Scelba & Agnese Giuseppa Federica Di Stefano & Giuseppe Leotta & Paola Maria Pugliatti & Fabrizio Bizzarri, 2020. "Performance Assessment of Large Photovoltaic (PV) Plants Using an Integrated State-Space Average Modeling Approach," Energies, MDPI, vol. 13(18), pages 1-27, September.
    4. Ahn, Hyeunguk, 2024. "A framework for developing data-driven correction factors for solar PV systems," Energy, Elsevier, vol. 290(C).

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