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Real-time prediction intervals for intra-hour DNI forecasts

Author

Listed:
  • Chu, Yinghao
  • Li, Mengying
  • Pedro, Hugo T.C.
  • Coimbra, Carlos F.M.

Abstract

We develop a hybrid, real-time solar forecasting computational model to construct prediction intervals (PIs) of one-minute averaged direct normal irradiance for four intra-hour forecasting horizons: five, ten, fifteen, and 20 min. This hybrid model, which integrates sky imaging techniques, support vector machine and artificial neural network sub-models, is developed using one year of co-located, high-quality irradiance and sky image recording in Folsom, California. We validate the proposed model using six-month of measured irradiance and sky image data, and apply it to construct operational PI forecasts in real-time at the same observatory. In the real-time scenario, the hybrid model significantly outperforms the reference persistence model and provides high performance PIs regardless of forecast horizon and weather condition.

Suggested Citation

  • Chu, Yinghao & Li, Mengying & Pedro, Hugo T.C. & Coimbra, Carlos F.M., 2015. "Real-time prediction intervals for intra-hour DNI forecasts," Renewable Energy, Elsevier, vol. 83(C), pages 234-244.
    • Handle: RePEc:eee:renene:v:83:y:2015:i:c:p:234-244
    DOI: 10.1016/j.renene.2015.04.022
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    References listed on IDEAS

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