SolarGIS: Solar Data and Online Applications for PV Planning and Performance Assessment

SolarGIS is a new generation web service (http://solargis.info) aimed to increase efficiency and reduce uncertainty in planning and performance assessment of PV systems. SolarGIS is based on more than 10 years of R&D, international collaboration, and experience with previous projects, such as PVGIS. The system consists of high-resolution database of solar radiation and air temperature (which are operationally calculated for Europe, Africa, Asia and Brazil) and some other auxiliary parameters. Solar radiation is calculated from Meteosat Prime and IODC satellites data covering a period from 1994 (2000) to the present. Derived solar parameters are calculated for any fixed-mounted or suntracking PV. Air temperature is derived from atmospheric models from ECMWF and NCEP. SolarGIS integrates previously published and validated PV performance models to simulate module surface reflectivity, non-linearities in the conversion efficiency due to irradiance/temperature outdoor conditions for c-Si, CdTe, and CIS/CIGS modules and shading. Four applications are implemented in the system: (i) iMaps high-resolution global interactive maps and data, (ii) climData interactive and automated access to solar radiation and air temperature; (iii) pvPlanner PV performance simulator with a new concept of simulation algorithms and data formats and (iv) pvSpot – a tool for performance evaluation and monitoring of PV systems. The key innovation of SolarGIS involve: (i) high-resolution and detailed solar radiation database, extensively validated and documented, (ii) Implementation of a new aerosol database from ECMWF into solar radiation model, (iii) Increased accuracy of PV simulation, (iv) Possibilities of near-real time data delivery, (v) Detailed interactive maps, precise geo-positioning and availability of other support data.

[1]  E. Dunlop,et al.  A power-rating model for crystalline silicon PV modules , 2011 .

[2]  H. Beyer,et al.  Mapping the performance of PV modules, effects of module type and data averaging , 2010 .

[3]  H. Beyer,et al.  Solar energy assessment using remote sensing technologies , 2003 .

[4]  E. Dunlop,et al.  Analysis of one‐axis tracking strategies for PV systems in Europe , 2010 .

[5]  E. Dunlop,et al.  Geographical variation of the conversion efficiency of crystalline silicon photovoltaic modules in Europe , 2008 .

[6]  Tomas Cebecauer,et al.  Spatial disaggregation of satellite-derived irradiance using a high-resolution digital elevation model , 2010 .

[7]  P. Ineichen,et al.  A NEW OPERATIONAL SATELLITE-TO-IRRADIANCE MODEL - DESCRIPTION AND VALIDATION , 2002 .

[8]  Alessandro Virtuani,et al.  Energy Yield Prediction of Amorphous Silicon PV Modules Using Full Time Data Series of Irradiance and Temperature for Different Geographical Locations , 2011 .

[9]  Richard Perez,et al.  HIGH PERFORMANCE MSG SATELLITE MODEL FOR OPERATIONAL SOLAR ENERGY APPLICATIONS , 2010 .

[10]  P. Ineichen,et al.  Comparison of Direct Normal Irradiation Maps for Europe , 2009 .

[11]  Thomas Huld,et al.  Management and Exploitation of Solar Resource Knowledge , 2008 .

[12]  E. Dunlop,et al.  Geographic Aspects of Photovoltaics in Europe: Contribution of the PVGIS Website , 2008, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[13]  N. Martín,et al.  Annual angular reflection losses in PV modules , 2005 .

[14]  Thomas Huld,et al.  First Steps in the Cross-Comparison of Solar Resource Spatial Products in Europe , 2008 .