A proposed methodology for quick assessment of timestamp and quality control results of solar radiation data

To evaluate the solar resource at a site, the period of measurements analyzed must be as long as possible. In solar radiation database, a quality control that identifies errors and labels the data by means of different flags or indicators is fundamental. Reading and interpretation of flagged data can usually be tedious due to the large numbers of data that have to be handled. This article presents a new type of graphical representation that facilitates the identification and interpretation of data quality by using their flagged values. These graphs represent the results of quality control (QC) for up to one year of measurements with any recording frequency on the same graph, making it easier to identify frequent errors such as incorrect timestamp. The utility of this visual tool to identify the most common errors found in quality control of solar radiation data is exemplified by applying it to the QC performed to 4 databases registered at different locations in Spain. The quality control process followed the recommendations of the Baseline Solar Radiation Network (BSRN).CIEMATUniversidad Carlos III (Madrid

Solar resource assessment in Seville, Spain. Statistical characterisation of solar radiation at different time resolutions

The characterisation of the solar resource of a site is essential for different phases of solar energy projects. While only rough estimates of yearly levels of solar irradiation (global or direct, depending on the technology) are needed in their very early stages, the required depth of the assessment increases as the project advances, including long-term estimates that can only be obtained through a statistical analysis of a continuous and long-term database of solar radiation measurements. This paper provides the results of a statistical analysis of thirteen years of Global Horizontal Insolation (GHI) measurements and Direct Normal Insolation (DNI) measurements from Seville, Spain (37.4°N, 6.05°W) at different time resolutions, i.e. from annual to nearly instantaneous (5-s). In addition, a new methodology for gap-filling is proposed which keeps the frequency distribution of the original dataset and reduces the uncertainty of the aggregated values (hourly, daily, monthly, yearly) due to the gaps. Some relevant results of this analysis are: (a) the instantaneous values of GHI and DNI have bimodal distributions, although of different characteristics, in agreement with the results of some works developed in similar climate locations; (b) the frequency distributions of the instantaneous and 10-min clearness index (kt) and beam fraction index (kb) are almost identical, suggesting 10 min as a good time resolution for the simulation of Concentrated Solar Power (CSP) systems oriented to feasibility analyses; (c) the distributions of hourly kt and kb values, show significant differences with respect to the instantaneous ones; (d) the difference between the percentile 99 (P99) of the instantaneous GHI and its maximum value is very high, because of the enhancement effect due to the cloud reflection, while for the DNI the corresponding values are much closer. The comparison with the results of other locations of similar climates suggest that these results can be extrapolated, at least, to other locations of similar climates. Other, more site-specific, results are: (a) the number of typical overcast days in summer is extremely low, while it takes its maximum value in December, suggesting this month as the best for maintenance operations that require halting the operation of CSP plants; (b) the annual mean daily values are 4.98 kW h m−2 for GHI and 5.68 kW h m−2 for DNI, with a low inter-annual variability and a greater monthly variability which depends on the season. The monthly and yearly average values from Seville have been compared with three long-term databases derived from satellite images. The best concordance in GHI values is found with NASA’s Surface Meteorology and Solar Energy (NASA SSE), but NASA SSE provides significantly higher DNI values compared to the Seville database. A comparison of one year of DNI and GHI measurements recorded at two locations, Durban (South Africa) and Abu Dhabi (United Arab Emirates), with high solar potential is also addressed