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Short-Term Forecasts of DNI from an Integrated Forecasting System (ECMWF) for Optimized Operational Strategies of a Central Receiver System

Author

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  • Francis M. Lopes

    (Renewable Energy Chair, University of Évora, IIFA, Palácio do Vimioso, Largo Marquês de Marialva, Apart. 94, 7002-554 Évora, Portugal
    Institute of Earth Sciences, University of Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal)

  • Ricardo Conceição

    (Renewable Energy Chair, University of Évora, IIFA, Palácio do Vimioso, Largo Marquês de Marialva, Apart. 94, 7002-554 Évora, Portugal
    Institute of Earth Sciences, University of Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal)

  • Hugo G. Silva

    (Renewable Energy Chair, University of Évora, IIFA, Palácio do Vimioso, Largo Marquês de Marialva, Apart. 94, 7002-554 Évora, Portugal
    Institute of Earth Sciences, University of Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal)

  • Thomas Fasquelle

    (Renewable Energy Chair, University of Évora, IIFA, Palácio do Vimioso, Largo Marquês de Marialva, Apart. 94, 7002-554 Évora, Portugal)

  • Rui Salgado

    (Institute of Earth Sciences, University of Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal
    Department of Physics, School of Sciences and Technology, University of Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal)

  • Paulo Canhoto

    (Institute of Earth Sciences, University of Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal
    Department of Physics, School of Sciences and Technology, University of Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal)

  • Manuel Collares-Pereira

    (Renewable Energy Chair, University of Évora, IIFA, Palácio do Vimioso, Largo Marquês de Marialva, Apart. 94, 7002-554 Évora, Portugal
    Institute of Earth Sciences, University of Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal
    Department of Physics, School of Sciences and Technology, University of Évora, Rua Romão Ramalho 59, 7000-671 Évora, Portugal
    Portuguese Solar Energy Institute, IIFA, Palácio do Vimioso, Largo Marquês de Marialva, Apart. 94, 7002-554 Évora, Portugal)

Abstract

Short-term forecasts of direct normal irradiance (DNI) from the Integrated Forecasting System (IFS) and the global numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF) were used in the simulation of a solar power tower, through the System Advisor Model (SAM). Recent results demonstrated that DNI forecasts have been enhanced, having the potential to be a suitable tool for plant operators that allows achieving higher energy efficiency in the management of concentrating solar power (CSP) plants, particularly during periods of direct solar radiation intermittency. The main objective of this work was to assert the predictive value of the IFS forecasts, regarding operation outputs from a simulated central receiver system. Considering a 365-day period, the present results showed an hourly correlation of ≈0.78 between the electric energy injected into the grid based on forecasted and measured data, while a higher correlation was found for the daily values (≈0.89). Operational strategies based on the forecasted results were proposed for plant operators regarding the three different weather scenarios. Although there were still deviations due to the cloud and aerosol representation, the IFS forecasts showed a high potential to be used for supporting informed energy dispatch decisions in the operation of central receiver units.

Suggested Citation

  • Francis M. Lopes & Ricardo Conceição & Hugo G. Silva & Thomas Fasquelle & Rui Salgado & Paulo Canhoto & Manuel Collares-Pereira, 2019. "Short-Term Forecasts of DNI from an Integrated Forecasting System (ECMWF) for Optimized Operational Strategies of a Central Receiver System," Energies, MDPI, vol. 12(7), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1368-:d:221263
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    References listed on IDEAS

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    Cited by:

    1. Andrea Salimbeni & Mario Porru & Luca Massidda & Alfonso Damiano, 2020. "A Forecasting-Based Control Algorithm for Improving Energy Managment in High Concentrator Photovoltaic Power Plant Integrated with Energy Storage Systems," Energies, MDPI, vol. 13(18), pages 1-20, September.
    2. Lopes, Francis M. & Conceição, Ricardo & Silva, Hugo G. & Salgado, Rui & Collares-Pereira, Manuel, 2021. "Improved ECMWF forecasts of direct normal irradiance: A tool for better operational strategies in concentrating solar power plants," Renewable Energy, Elsevier, vol. 163(C), pages 755-771.
    3. David Borge-Diez & Enrique Rosales-Asensio & Ana I. Palmero-Marrero & Emin Acikkalp, 2022. "Optimization of CSP Plants with Thermal Energy Storage for Electricity Price Stability in Spot Markets," Energies, MDPI, vol. 15(5), pages 1-25, February.
    4. Segarra-Tamarit, Jorge & Pérez, Emilio & Moya, Eric & Ayuso, Pablo & Beltran, Hector, 2021. "Deep learning-based forecasting of aggregated CSP production," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 184(C), pages 306-318.
    5. Lopes, Telma & Fasquelle, Thomas & Silva, Hugo G., 2021. "Pressure drops, heat transfer coefficient, costs and power block design for direct storage parabolic trough power plants running molten salts," Renewable Energy, Elsevier, vol. 163(C), pages 530-543.
    6. Alberto Boretti & Jamal Nayfeh & Wael Al-Kouz, 2020. "Validation of SAM Modeling of Concentrated Solar Power Plants," Energies, MDPI, vol. 13(8), pages 1-25, April.
    7. Norambuena-Guzmán, Valentina & Palma-Behnke, Rodrigo & Hernández-Moris, Catalina & Cerda, Maria Teresa & Flores-Quiroz, Ángela, 2024. "Towards CSP technology modeling in power system expansion planning," Applied Energy, Elsevier, vol. 364(C).
    8. Kahvecioğlu, Gökçe & Morton, David P. & Wagner, Michael J., 2022. "Dispatch optimization of a concentrating solar power system under uncertain solar irradiance and energy prices," Applied Energy, Elsevier, vol. 326(C).

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