EuroSun2008-13

Yearly Sum and Frequency distribution of DNI

The accuracy of the proposed method to derive DNI was evaluated for the year 2005 for six stations of the Spanish Meteorological Service INM, see table 1. The evaluation was performed for all hourly values with the sun above horizon.

Special focus of the evaluation was on the accuracy of yearly sums and on the investigation of frequency distributions of the time series, as these are relevant for yield estimates. Beside this, the relative bias rBIAS and the relative root mean square error rRMSE are used for quantitative comparisons.

For hourly values an rRMSE of 14.7% for global irradiance and of 31% for direct normal irradiance was found for the Spanish stations. The rBIAS is 1.5% for global irradiance and 1.1% for direct irradiance respectively.

Figure 4 displays rBIAS and rRMSE of DNI for the Spanish stations. The rBIAS for one year and one station is equivalent to the relative deviation of the annual sum for one station. In addition the rBIAS for clear sky situations rBIASclearsky is provided. Hours are assigned as clear sky situations, if two criteria match: The clear sky index lies within 0.9<=k*< =1.1 and the variability of the cloud index in a small region of 3x5 pixel is small.

The comparison of rBIAS and rBIASciearsky illustrates the strong influence of the quality of the clear sky model and the atmospheric input parameters on the quality of the annual sums. The deviation of annual satellite derived irradiance sums from the respective ground measured sums between -2% and 8.5% for DNI.

In table 2 the accuracy information is given on different time scales which are relevant for solar energy applications. The deviation of annual satellite derived irradiance sums from the respective ground measured sums is between -2% and 4.5% for GHI and between -2% and 8.5% for DNI.

Table 2: Accuracy of satellite derived global horizontal irradiance GHI and direct normal irradiance DNI for

different time scales.

For energy conversion systems with non-linear response to the irradiance input a correct representation of the frequency distribution is of special importance. Figure 5 displays the frequency distribution of calculated and measured DNI and GHI for the Spanish stations; a fairly good agreement is achieved.

3. Conclusion

We developed a method to derive direct normal irradiance from MSG data. The influence of clouds on the direct normal irradiance is derived from MSG data with high quality. The quality for clear skies is determined by the accuracy of the aerosol climatology.

4. Acknowledgements

Thanks are due to the Spanish Meteorological Service INM for the supply of ground data.

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