Data Quality Analysis for a Smart Solar Resource Assessment

The development of solar-based projects stimulates the demand's increase in the concern of reliable data, especially for the life cycle cost analysis of solar technologies. Reliable data requires several important aspects that should be taken into consideration. We can evoke for example, the instrument performance specifications, methods of installation, frequency of calibrations and the regularity of maintenance and data analysis. However, when analyzing solar radiation dataset, many questionable values are still identified. Thus, the crucial step is to develop more accurate automatic procedures for performing quality control (QC) of solar data, in addition to the maintenance and human monitoring. The objective of the automatic procedures is to identify aberrant observations and to reduce the manual workload of human validators, in order to guarantee reliability and allow comparison analysis between different observational datasets. In the same context, we present and we analyze an implemented procedure, using several tests, for 3 stations of Moroccan Agency for Solar Energy (masen). The analysis shows that the adopted procedure is very efficient for quality assessment. However, the procedure should be integrated in a global quality process, to ensure the procurement of bankable data.