Having defined the climatic factors and described the climatic variability of the two countries, this part of the research concentrates on the solar data. The two main climatic factors that affect the PV systems performance are the solar irradiation and the ambient temperature and for this reason the choice of the solar data play a key role in the PV energy prediction. In this research, the PVGIS solar database was chosen as the input for the PV energy prediction. Generally, PVGIS provides a map-based record of solar energy resource and evaluation of the electricity generation from photovoltaic systems in Europe, Africa, and South-West Asia. One of the two architects of PVGIS is Thomas Huld who was the external advisor of this specific research, and he has provided this research with the PVGIS solar data for India ahead of their release in the PVGIS web site [3]. The PVGIS solar database was studied to establish its reliability compared to other available solar data sources and identify its limitations.
2.2.1 PVGIS solar databases
PVGIS provides two solar databases for Europe, the classic and the climate SAF. The classic PVGIS solar database is based on data from the European Solar Radiation Atlas. It includes data from 560 different ground weather stations across Europe, during the period of 1981 to 1990. The disadvantages of the PVGIS classic database are:
1) The data collected are old, so the solar irradiation values may not be representative of the current conditions.
2) The mathematical interpolation used for acquiring data between the stations is subject to uncertainties.
3) The density of stations varies across Europe, so the uncertainty can be very high in areas with few stations.
4) Large areas that have only one station or have a station placed in a location that is not representative of the area can face significant measurement errors.
The new PVGIS solar database has been calculated from solar radiation data made available by the Climate Monitoring Satellite Application Facility (CM-SAF). The solar radiation values have been estimated from satellite images. The data are over the period 1998 to 2011, so they are not subject to major climate changes. The CM-SAF data has been tested extensively against high-quality ground measurements and the overall local error for the whole year is less than 5%. The disadvantages of PVGIS CM-SAF database are:
1) The pixel size in the satellite images is about 3-5 km; so smaller features such as narrow mountain valleys cannot be resolved.
2) The computer algorithm that calculates the solar radiation on the ground may have difficulties to distinguish the difference between snow and clouds.
3) When the sun’s altitude is very low, the calculation from the satellite data becomes very difficult.
Moreover, for the Mediterranean Basin, Africa and South-West Asia PVGIS also provides two solar databases: the Helioclim-1 and the CM-SAF. HelioClim-1 database consists of daily sums of global horizontal irradiation calculated from Meteosat Prime images by the Heliosat 2 method. The values represent the period of 1985-2004 and
“the original calculation is 15 arc-minutes, or about 28 km right below the satellite (at the equator, 0 degrees West)” [16]. It is obvious that even though the data are not very old the spatial resolution is too low; hence the uncertainty could be very high [16].
2.2.2 Solar data sources
This section presents the most popular solar databases, which provide monthly average data and can also be imported into PVsyst simulation software. PVsyst software is analytically discussed in the following section (Section 2.3). The reason of this study was to compare the different solar data sources with PVGIS solar data.
Namely, these databases are: Meteonorm [30], World Radiation Data Centre [31], NASA-SSE [32], SolarGIS iMaps [33], and RETScreen [34].
Meteonorm software gives average monthly irradiance data from 1200 weather stations during the period of 1960-1991. Moreover, in version 6 of Meteonorm, data are also provided for the period of 1981-2000.
World Radiation Data Centre (WRDC) gives average monthly irradiance data from 1195 sites in the world, during the period of 1964-1993. However, many of the data are averaged only for a few years and not throughout the whole period. In addition, WRDC database does not include temperature data.
NASA-SSE (Surface Meteorological and Solar Energy Programme) has satellite monthly data for a grid of 111 km x 111 km covering the whole world, for the period 1983-1993. It is noticed, that the data are quite old and the spatial resolution is low.
SolarGIS iMaps provides average monthly data of solar radiation and air temperature for Europe, Africa, and Middle East. The data are regularly revised and developed from Meteosat MSG data. Their spatial resolution is about 4 x 5 km at mid latitudes and 3 km at the sub-satellite point [33].
RETScreen Canadian software provides a complete database for any location in the world. It uses the best available data at each location from about 20 sources; the main ones are the WRDC and the NASA.
Table 2.3 presents a summary of the meteorological databases available with importing tool in PVsyst software [17].
Table 2.3: Summary of meteorological databases [17]
In general, some of the sources like NASA-SSE, ESRA (European Solar Radiation Atlas) and NREL (National Renewable Energy Laboratory) are providing data with global or continental coverage; however their spatial resolution is relatively low (i.e. 40 km x 40 km for NREL data). “Strongly varying elevation gradients combined with terrain shadowing can cause significant local irradiance fluctuations” [16]. Hence, it has been concluded that the main solar database for this research will be the PVGIS CM-SAF database as it is a free access, recently revised source with fairly uniform land coverage and good spatial resolution (pixel size 3-5 km).