Autocorrelation properties of the sunshine number and sunshine stability number

Two new Boolean parameters are defined: the sunshine number (related to the state of the sky) and the sunshine stability number (which is as a measure of the fluctuation of the radiative regime). Elementary statistical and sequential properties of both parameters are presented in this paper. Actinometric and meteorological data measured at 15 s lag during 2009 in Timisoara (Romania, southeastern Europe) are used. The yearly series of daily averaged sunshine number has negative skewness and kurtosis. The series of daily averaged sunshine stability number has positive skewness and kurtosis. The series of daily averaged values of sunshine number are best described by an ARIMA(0,1,2) model. ARIMA(0,1,0) and ARIMA(0,2,0) models (associated with an appropriately defined white noise) may be used for synthesis of the sunshine number time series. The first model is to be preferred for practical reasons. The series of daily averaged values of sunshine stability number are best described by an ARIMA(2,2,1) model. The ARIMA(0,0,0) model is recommended to be used for generating time series of sunshine stability number. This model may be used for any particular day during the year and the only parameter depending on the day is the white noise standard deviation. A relationship between the white noise standard deviation and the daily averaged sunshine stability number is proposed.

[1]  Viorel Badescu,et al.  A new kind of cloudy sky model to compute instantaneous values of diffuse and global solar irradiance , 2002 .

[2]  V. Badescu,et al.  Degree-days, degree-hours and ambient temperature bin data from monthly-average temperatures (Romania) , 1999 .

[3]  P. W. Strike,et al.  Forecasting and control , 1991 .

[4]  R. Belmans,et al.  Voltage fluctuations on distribution level introduced by photovoltaic systems , 2006, IEEE Transactions on Energy Conversion.

[5]  V. Bădescu,et al.  Studies concerning the empirical relationship of cloud shade to point cloudiness (Romania) , 1991 .

[6]  David R. Cox,et al.  Time Series Analysis , 2012 .

[7]  John Boland,et al.  Time Series Modelling of Solar Radiation , 2008 .

[8]  V. Badescu.  Modeling Solar Radiation at the Earth’s Surface , 2008 .

[9]  V. B Descu.  OVER AND UNDER ESTIMATION OF CLOUD AMOUNT: THEORY AND ROMANIAN OBSERVATIONS , 1992 .

[10]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1972 .

[11]  Teolan Tomson,et al.  Fast dynamic processes of solar radiation , 2010 .

[12]  V. Badescu.  Correlations to estimate monthly mean daily solar global irradiation: application to Romania , 1999 .

[13]  C. A. Coombes,et al.  Empirical relationship of cloud shade to point cloudiness (Canada) , 1986 .

[14]  V. Badescu.  Use of Sunshine Number for Solar Irradiance Time Series Generation , 2008 .

[15]  Joaquin Tovar-Pescador,et al.  Modelling the Statistical Properties of Solar Radiation and Proposal of a Technique Based on Boltzmann Statistics , 2008 .