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A study on the impact of time resolution in solar data on the performance modelling of CSP plants

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  • Meybodi, Mehdi Aghaei
  • Ramirez Santigosa, Lourdes
  • Beath, Andrew C.

Abstract

Availability of long term solar data and the quality of available data is usually an obstacle to the development of proposals for new concentrating solar power plants. Typical or representative meteorological years using hourly solar and weather data that has been selected to match long-term averages are often used to perform the preliminary design and performance assessment of solar power plants. Although the use of this data is convenient due to the reduced computational requirements in plant optimization, it may result in a simplistic prediction of plant operations that does not reflect the real plant performance by neglecting the impact of short-term variability in solar irradiance and the variations in weather and available solar energy for different years. This study conducts a systematic analysis of the influence of multi-year data sets with a range of different time step sizes (5, 15, 30 and 60 min) and thermal storage capacities (4, 8 and 12 h) using the physical parabolic trough with molten salt storage model in NREL’s System Advisor Model. Results indicate that the appropriateness of different step sizes is likely to vary depending on the purpose of the modelling; however, sensitivity to step size is reduced for larger storage capacities.

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  • Meybodi, Mehdi Aghaei & Ramirez Santigosa, Lourdes & Beath, Andrew C., 2017. "A study on the impact of time resolution in solar data on the performance modelling of CSP plants," Renewable Energy, Elsevier, vol. 109(C), pages 551-563.
    • Handle: RePEc:eee:renene:v:109:y:2017:i:c:p:551-563
    DOI: 10.1016/j.renene.2017.03.024
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    References listed on IDEAS

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    1. Janjai, S. & Laksanaboonsong, J. & Seesaard, T., 2011. "Potential application of concentrating solar power systems for the generation of electricity in Thailand," Applied Energy, Elsevier, vol. 88(12), pages 4960-4967.
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    7. Meybodi, Mehdi Aghaei & Beath, Andrew C., 2016. "Impact of cost uncertainties and solar data variations on the economics of central receiver solar power plants: An Australian case study," Renewable Energy, Elsevier, vol. 93(C), pages 510-524.
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    Cited by:

    1. Adrian Gonzalez Gonzalez & J. Valeriano Alvarez Cabal & Vicente Rodríguez Montequin & Joaquín Villanueva Balsera & Rogelio Peón Menéndez, 2020. "CSP Quasi-Dynamic Performance Model Development for All Project Life Cycle Stages and Considering Operation Modes. Validation Using One Year Data," Energies, MDPI, vol. 14(1), pages 1-22, December.
    2. Ferdowsi, Farzad & Mehraeen, Shahab & Upton, Gregory B., 2020. "Assessing distribution network sensitivity to voltage rise and flicker under high penetration of behind-the-meter solar," Renewable Energy, Elsevier, vol. 152(C), pages 1227-1240.
    3. Laporte-Azcué, M. & Rodríguez-Sánchez, M.R. & González-Gómez, P.A. & Santana, D., 2021. "Assessment of the time resolution used to estimate the central solar receiver lifetime," Applied Energy, Elsevier, vol. 301(C).
    4. Moreno-Tejera, S. & Silva-Pérez, M.A. & Ramírez-Santigosa, L. & Lillo-Bravo, I., 2018. "Evaluation of classification methods according to solar radiation features from the viewpoint of the production of parabolic trough CSP plants," Renewable Energy, Elsevier, vol. 121(C), pages 429-440.

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