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Impact of DNI forecasting on CSP tower plant power production

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  • Alonso-Montesinos, J.
  • Polo, Jesús
  • Ballestrín, Jesús
  • Batlles, F.J.
  • Portillo, C.

Abstract

In the context of energy policies focusing on minimizing power plant emissions, concentrating solar power (CSP) technology plays an important role in the energy mix. These plants require a high level of direct normal irradiance to work properly and profitably. Over-sizing of plant capacity is frequently employed in order to store part of the energy produced, to extend the operating time throughout the day, and also to manage cloud transients. Forecasting the energy delivered by the plant is very important in plant operational strategies to ensure dispatchability as much as possible. This work presents an analysis of energy forecasting in solar tower plants by combining a short-term solar irradiation forecasting scheme with a solar tower plant model using the System Advisor Model (SAM), as the modeling tool for computing plant production throughout the year. Satellite images were used to predict Direct Normal Irradiance (DNI) on an intra-hour time-scale (up to three hours). The predictions were introduced into SAM to simulate the behavior of the Gemasolar and Crescent Dunes plants, placed on Spain and Nevada, respectively). The results show that the best outcomes appear for the 90-mins horizon, where the Mean Bias was about −10% and the RMSE near to 23%.

Suggested Citation

  • Alonso-Montesinos, J. & Polo, Jesús & Ballestrín, Jesús & Batlles, F.J. & Portillo, C., 2019. "Impact of DNI forecasting on CSP tower plant power production," Renewable Energy, Elsevier, vol. 138(C), pages 368-377.
    • Handle: RePEc:eee:renene:v:138:y:2019:i:c:p:368-377
    DOI: 10.1016/j.renene.2019.01.095
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    References listed on IDEAS

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    1. Alonso-Montesinos, J. & Monterreal, R. & Fernández-Reche, J. & Ballestrín, J. & Carra, E. & Polo, J. & Barbero, J. & Batlles, F.J. & López, G. & Enrique, R. & Martínez-Durbán, M. & Marzo, A., 2019. "Intra-hour energy potential forecasting in a central solar power plant receiver combining Meteosat images and atmospheric extinction," Energy, Elsevier, vol. 188(C).
    2. Rodríguez-Benítez, Francisco J. & López-Cuesta, Miguel & Arbizu-Barrena, Clara & Fernández-León, María M. & Pamos-Ureña, Miguel Á. & Tovar-Pescador, Joaquín & Santos-Alamillos, Francisco J. & Pozo-Váz, 2021. "Assessment of new solar radiation nowcasting methods based on sky-camera and satellite imagery," Applied Energy, Elsevier, vol. 292(C).
    3. Mathieu David & Joaquín Alonso-Montesinos & Josselin Le Gal La Salle & Philippe Lauret, 2023. "Probabilistic Solar Forecasts as a Binary Event Using a Sky Camera," Energies, MDPI, vol. 16(20), pages 1-18, October.
    4. Lin, Xiaoxia & He, Caitou & Huang, Wenjun & Zhao, Yuhong & Feng, Jieqing, 2022. "GPU-based Monte Carlo ray tracing simulation considering refraction for central receiver system," Renewable Energy, Elsevier, vol. 193(C), pages 367-382.
    5. Salmon, Aloïs & Marzo, Aitor & Polo, Jesús & Ballestrín, Jesús & Carra, Elena & Alonso-Montesinos, Joaquín, 2022. "World map of low-layer atmospheric extinction values for solar power tower plants projects," Renewable Energy, Elsevier, vol. 201(P1), pages 876-888.
    6. Arias, I. & Cardemil, J. & Zarza, E. & Valenzuela, L. & Escobar, R., 2022. "Latest developments, assessments and research trends for next generation of concentrated solar power plants using liquid heat transfer fluids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).

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