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Stochastic modelling of daily global irradiation

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  • Festa, R.
  • Jain, S.
  • Ratto, C.F.

Abstract

A statistical analysis of the solar daily global irradiation for Genoa, Italy, has been carried out using a 9 year time series. The frequency distribution of the fluctuations in the daily values of the time series about the mean, normalized by the standard deviation, has been transformed into a standard Normal distribution. An Autoregressive process of order 1 has been fitted to the transformed series. The daily means and the standard deviations have been estimated by two approaches, viz. (i) Fourier expansion of the daily means and standard deviations with one and two harmonics, respectively; (ii) smoothing of the daily values of these parameters by the “monthly averages method”. For both the approaches, the Autoregressive parameter has been estimated in two ways, viz. (i) keeping it time invariant; (ii) changing it day by day during a year. The fitted model has been used to generate synthetic sequences of daily solar irradiations. All the four methods produce synthetic series which almost satisfactorily match the empirical one without showing any appreciable superiority of the one over the other method.

Suggested Citation

  • Festa, R. & Jain, S. & Ratto, C.F., 1992. "Stochastic modelling of daily global irradiation," Renewable Energy, Elsevier, vol. 2(1), pages 23-34.
    • Handle: RePEc:eee:renene:v:2:y:1992:i:1:p:23-34
    DOI: 10.1016/0960-1481(92)90056-9
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    References listed on IDEAS

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    1. Callegari, M. & Festa, R. & Ratto, C.F., 1992. "Stochastic modelling of daily beam irradiation," Renewable Energy, Elsevier, vol. 2(6), pages 611-624.
    2. Parzen, Emanuel & Pagano, Marcello, 1979. "An approach to modeling seasonally stationary time series," Journal of Econometrics, Elsevier, vol. 9(1-2), pages 137-153, January.
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    1. Kamal, Lalarukh & Jafri, Yasmin Zahra, 1999. "Stochastic modeling and generation of synthetic sequences of hourly global solar irradiation at Quetta, Pakistan," Renewable Energy, Elsevier, vol. 18(4), pages 565-572.
    2. Zervas, P.L. & Sarimveis, H. & Palyvos, J.A. & Markatos, N.C.G., 2008. "Prediction of daily global solar irradiance on horizontal surfaces based on neural-network techniques," Renewable Energy, Elsevier, vol. 33(8), pages 1796-1803.
    3. Youcef Ettoumi, F. & Mefti, A. & Adane, A. & Bouroubi, M.Y., 2002. "Statistical analysis of solar measurements in Algeria using beta distributions," Renewable Energy, Elsevier, vol. 26(1), pages 47-67.
    4. Ratto, C.F. & Festa, R., 1993. "A procedure for evaluating the influence of weather Markovianity on the storage behaviour of solar systems," Renewable Energy, Elsevier, vol. 3(8), pages 951-960.
    5. Ballestrín, Jesús & Polo, Jesús & Martín-Chivelet, Nuria & Barbero, Javier & Carra, Elena & Alonso-Montesinos, Joaquín & Marzo, Aitor, 2022. "Soiling forecasting of solar plants: A combined heuristic approach and autoregressive model," Energy, Elsevier, vol. 239(PE).
    6. Kaplanis, S. & Kaplani, E., 2007. "A model to predict expected mean and stochastic hourly global solar radiation I(h;nj) values," Renewable Energy, Elsevier, vol. 32(8), pages 1414-1425.
    7. Callegari, M. & Festa, R. & Ratto, C.F., 1992. "Stochastic modelling of daily beam irradiation," Renewable Energy, Elsevier, vol. 2(6), pages 611-624.
    8. Kaplanis, S.N., 2006. "New methodologies to estimate the hourly global solar radiation; Comparisons with existing models," Renewable Energy, Elsevier, vol. 31(6), pages 781-790.

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