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Short-term forecast of solar irradiance components using an alternative mathematical approach for the identification of cloud features

Author

Listed:
  • Peña-Cruz, Manuel I.
  • Díaz-Ponce, Arturo
  • Sánchez-Segura, César D.
  • Valentín-Coronado, Luis
  • Moctezuma, Daniela

Abstract

Solar energy technologies require precise solar forecasting to reduce power generation losses and protect equipment from irradiance fluctuations. This study introduces an alternative methodology for short-term forecasting of direct normal irradiance (DNI) and global horizontal irradiance (GHI) utilizing ground-based sky images captured by a single device. A low-cost all-sky imager (ASI) was developed, which implements an angular transformation and an optical flow technique to extract cloud features such as shape and velocity. A mathematical model calculates cloud transmittance based on pixel intensity, eliminating complex training steps. Results from a 30-day experimental campaign, incorporating diverse meteorological conditions, were compared against a secondary standard solarimetric station, a smart persistence model, and state-of-the-art approaches. The DNI forecast achieved an RMSE (relative error) of 46.79 W/m2 (11.99%) for 1-min intervals and 90.21 W/m2 (17.54%) for 10-min intervals, while GHI ranged from 31.73 W/m2 (4.68%) to 75.02 W/m2 (13.63%). Pearson correlation coefficients exceeded 0.9 overall, reaching 0.98 and 0.99 for the 1-min DNI and GHI forecasts, and 0.91 and 0.96 for the 10-min DNI and GHI forecasts, respectively, underscoring the system’s accuracy and robustness in complex meteorological scenarios.

Suggested Citation

  • Peña-Cruz, Manuel I. & Díaz-Ponce, Arturo & Sánchez-Segura, César D. & Valentín-Coronado, Luis & Moctezuma, Daniela, 2024. "Short-term forecast of solar irradiance components using an alternative mathematical approach for the identification of cloud features," Renewable Energy, Elsevier, vol. 237(PC).
    • Handle: RePEc:eee:renene:v:237:y:2024:i:pc:s0960148124017592
    DOI: 10.1016/j.renene.2024.121691
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    References listed on IDEAS

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