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  • Open Access

Spectral analysis of solar-irradiance fluctuations

G. Bel1,2,* and M.M. Bandi3

  • 1Department of Environmental Physics, Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus 84990, Israel
  • 2Department of Physics, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
  • 3Nonlinear and Non-equilibrium Physics Unit, OIST Graduate University, 1919-1 Tancha, Onna-son, Okinawa 904-0495, Japan

  • *bel@bgu.ac.il

Phys. Rev. Applied 21, 034019 – Published 12 March, 2024

DOI: https://doi.org/10.1103/PhysRevApplied.21.034019

Abstract

Solar-irradiance fluctuations possess a power-law spectrum with two different slopes in the intermediate (1/day <f<1/h) and high [1/h <f<1/(2 min)] frequency (f) regimes. This spectrum is a combination of a deterministic (latitude-dependent) variation of daylight duration and a stochastic component arising from various environmental attenuation factors. We propose a principled approach to decompose the solar-irradiance time series into the deterministic location-dependent clear sky and the stochastic environmental attenuation signals. Such decomposition permits one to systematically analyze the solar photovoltaic power-fluctuation spectra after accounting for the strong geographic dependence, failing which no baseline standard exists with which to compare spectra between disparate geographic locations. Our analysis for two different locations shows that the stochastic environmental factors determine the spectral power-law slope in the high-frequency range, while the deterministic clear-sky signal plays a role in the intermediate frequency range. We close by discussing its implications for solar photovoltaic power production, in particular, for the geographic smoothing of fluctuations.

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References (37)

  1. J. Apt and P. Jaramillo, Variable Renewable Energy and the Electricity Grid (Routledge, New York, USA, 2014).
  2. Ottmar Edenhofer, R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen, S. Schlömer, et al., Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN) (IPCC, Cambridge University Press, Cambridge, UK and New York, USA, 2011).
  3. M. D. Shafiullah, S. D. Ahmed, and F. A. Al-Sulaiman, Grid integration challenges and solution strategies for solar PV systems: A review, IEEE Access 10, 52233 (2022).
  4. O. Gandhi, D. S. Kumar, C. D. Rodrigues-Gallegos, and D. Srinivasan, Review of power system impacts at high PV penetration part I: Factors limiting PV penetration, Sol. Energy 210, 181 (2020).
  5. M. Anvari, G. Lohmann, M. Wächter, P. Milan, E. Lorenz, D. Heinemann, M. Reza Rahimi Tabar, and Joachim Peinke, Short term fluctuations of wind and solar power systems, New J. Phys. 18, 063027 (2016)..
  6. Aimee E. Curtright and Jay Apt, The character of power output from utility-scale photovoltaic systems, Prog. Photovolt.: Res. Appl. 16, 241 (2008).
  7. G. Bel, C. P. Connaughton, M. Toots, and M. M. Bandi, Grid-scale fluctuations and forecast error in wind power, New J. Phys. 18, 023015 (2016).
  8. J. Apt, The spectrum of power from wind turbines, J. Power Sources 169, 369 (2007).
  9. P. Milan, M. Wächter, and J. Peinke, Turbulent character of wind energy, Phys. Rev. Lett. 110, 138701 (2013).
  10. M. M. Bandi, Spectrum of wind power fluctuations, Phys. Rev. Lett. 118, 028301 (2017).
  11. R. Calif, R. Schmitt, and Y. Huang, Multifractal description of wind power fluctuations using arbitrary order Hilbert spectral analysis, Phys. A 392, 4106 (2013).
  12. R. Perez, M. David, T. E. Hoff, M. Jamaly, S. Kivalov, J. Kleissl, P. Lauret, and M. Perez, Spatial and temporal variability of solar energy, Found. Trends Renew. Energy 1, 1 (2016).
  13. Javier Marcos, Luis Marroyo, Eduardo Lorenzo, David Alvira, and Eloisa Izco, From irradiance to output power fluctuations: The PV plant as a low pass filter, Prog. Photovolt: Res. Appl. 19, 505 (2011).
  14. J. Marcos, I. de la Parra, M. Garcia, and L. Marroyo, Simulating the variability of dispersed large PV plants, Prog. Photovolt: Res. Appl. 24, 680 (2016).
  15. K. Klima and J. Apt, Geographic smoothing of solar PV: Results from Gujarat, Environ. Res. Lett. 10, 104001 (2015).
  16. K. Klima, J. Apt, M. M. Bandi, P. Happy, C. Loutan, and R. Young, Geographic smoothing of solar photovoltaic electric power production in the western USA, J. Renew. Sustain. Energy 10, 053504 (2018).
  17. G. Bel and M. M. Bandi, Geographic dependence of the solar irradiance spectrum at intermediate to high frequencies, Phys. Rev. App. 12, 024032 (2019).
  18. C. J. T. Spitters, H. A. J. M. Toussaint, and J. Goudriaan, Separating the diffuse and direct component of global radiation and its implications for modeling canopy photosynthesis. Part I. Components of incoming radiation, Agri. For. Meteorol. 38, 217 (1986).
  19. A. A. El-Sebaii, F. S. Al-Hazmi, A. A. Al-Ghamdi, and S. J. Yaghmour, Global, direct and diffuse solar radiation on horizontal and tilted surfaces in Jeddah, Saudi Arabia, Appl. Energy 87, 568 (2010).
  20. Muhammad Iqbal, An Introduction to Solar Radiation (Academic Press, Ontario, Canada, 2012).
  21. D. H. W. Li, S. W. Lou, and J. C. Lam, An analysis of global, direct and diffuse solar radiation, Energy Procedia 75, 388 (2015).
  22. B. Y. H. Liu and R. C. Jordan, The interrelationship and characteristic distribution of direct, diffuse and total solar radiation, Sol. Energy 4, 1 (1960).
  23. X. Zhang, S. Liang, and G. Wang, Comprehensive Remote Sensing, Vol. 5: Earth’s Energy Budget Chapter 5: Surface Incident Shortwave Radiation (Elsevier Inc., Amsterdam, 2018).
  24. R. Calif, F. G. Schmitt, Y. Huang, and T. Soubdhan, Intermittency study of high frequency global solar radiation sequences under a tropical climate, Sol. Energy 98, 349 (2013).
  25. M. Reza Rahimi Tabar, M. Anvari, G. Lohmann, D. Heinemann, M. Wächter, P. Milan, E. Lorenz, and Joachim Peinke, Kolmogorov spectrum of renewable wind and solar power fluctuations, Eur. Phys. J. Spec. Top. 223, 2637 (2014).
  26. B. Haurwitz, Insolation in relation to cloudiness and cloud density, J. Meteorol. 2, 154 (1945).
  27. B. Haurwitz, Insolation in relation to cloud type, J. Meteorol. 3, 123 (1946).
  28. Joshua S. Stein, Clifford W. Hansen, and Matthew J. Reno, Global Horizontal Irradiance Clear Sky Models: Implementation and Analysis, Technical Report (Institution Sandia National Laboratories, Albuquerque, NM USA, 2012).
  29. Shlomo Kabalo, Solar-irradiation data for MBG, Local measurements. The data will be made available upon reasonable request.
  30. NOAA, Buoy data, https://tao.ndbc.noaa.gov/tao/data_download/search_map.shtml, last accessed on August 14, 2023.
  31. G. M. Lohmann, Irradiance variability quantification and small-scale averaging in space and time: A short review, Atmosphere 9, 264 (2018).
  32. Private Communication, J. Apt and J. Sardonia.
  33. Nailya Maitanova, Sunke Schlöters, Benedikt Hanke, Karsten von Maydell, and Carsten Agert, Quantifying power and energy fluctuations of photovoltaic systems, Energy Sci. Eng. 10, 4496 (2022).
  34. A. Curtright and J. Apt, The character of power output from utility-scale photovoltaic systems, Prog. Photovolt: Res. Appl. 16, 241 (2007).
  35. P. Ineichen and R. Perez, A new airmass independent formulation for the Linke turbidity coefficient, Sol. Energy 73, 151 (2002).
  36. R. Perez, et al., A new operational model for satellite-derived irradiances: Description and validation, Sol. Energy 73, 307 (2002).
  37. Karel De Brabandere, Artefact in Ineichen clearsky model for sun close to horizon, https://github.com/pvlib/pvlib-python/issues/435, last accessed on August 14, 2023.

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