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summary daily solar daily HDD daily CDD
daily solar daily HDD daily CDD
summary year month weather wind model
Monthly weather, degree day, solar energy and wind energy statistics and solar power statistics for Tbilisi

Tbilisi monthly solar energy plot, Tbilisi monthly wind energy plot, Tbilisi monthly heating degree day plot and Tbilisi monthly cooling degree day plot
Figure 2.1 Tbilisi average monthly percentage of solar energy, heating degree and cooling degree day plots.

Tbilisi yearly solar energy plot, Tbilisi yearly wind energy plot, Tbilisi yearly heating degree days plot and Tbilisi yearly cooling degree days plot
Figure 2.2 Tbilisi yearly solar energy, wind energy, heating degree day and cooling degree day plots.

Tbilisi monthly solar energy plot, Tbilisi monthly wind energy plot, Tbilisi monthly heating degree day plot and Tbilisi monthly cooling degree day plot
Figure 2.3 Tbilisi monthly solar energy, wind energy, heating degree day and cooling degree day plots.

Tbilisi weather statistics
Figure 2.4 Tbilisi yearly and monthly temperature and wind speed plots.

Tbilisi windmill characteristic
Figure 2.5 Wind power model for Tbilisi.

Acknowledgement: many thanks to the PVGIS team for open access to PVGIS 5.1 data from 2005 to 2015. Source - "Photovoltaic Geographic Information System (PVGIS)", European Commission, Joint Research Centre (JRC). Online tool available at re.jrc.ec.europa.eu/pvgis.html - PVGIS Ⓒ European Communities, 2000-2020. In this work, hourly data is post-processed into yearly, monthly and daily statistics - and visualized using boxplots. The main focus of PVGIS is photovoltaic solar. Wind statistics are experimental, and have known issues.

References:

[1]
Overview of PVGIS data sources and calculation methods.
joint-research-centre.ec.europa.eu/pvgis-photovoltaic-geographical-information-system/getting-started-pvgis/pvgis-data-sources-calculation-methods_en
[2]
Huld, T.; Müller, R.; Gambardella, A. A new solar radiation database for estimating PV performance in Europe and Africa. Solar Energy 2012, 86, 1803-1815.
doi: 10.1016/j.solener.2012.03.006
[3]
Gracia Amillo, A.; Huld, T.; Müller, R. A New Database of Global and Direct Solar Radiation Using the Eastern Meteosat Satellite, Models and Validation. Remote Sensing 2014, 6, 8165-8189.
doi:10.3390/rs6098165
[4]
Huld, T.; Gracia Amillo, A. Estimating PV Module Performance over Large Geographical Regions: the role of Irradiance, Air Temperature, Wind Speed and Solar Spectrum. Energies 2015, 8, 6, 5159-5181.
doi:10.3390/en8065159
[5]
Müller, Richard; Pfeifroth, Uwe; Träger-Chatterjee, Christine; Cremer, Roswitha; Trentmann, Jörg; Hollmann, Rainer (2015): Surface Solar Radiation Data Set - Heliosat (SARAH) - Edition 1, Satellite Application Facility on Climate Monitoring.
doi: 10.5676/EUM_SAF_CM/SARAH/V001
[6]
Hersbach, H, Bell, B, Berrisford, P, et al. The ERA5 global reanalysis. Q J R Meteorol Soc. 2020; 146: 1999– 2049.
doi: 10.1002/qj.3803
[7]
Manajit Sengupta, Yu Xie, Anthony Lopez, Aron Habte, Galen Maclaurin, James Shelby, The National Solar Radiation Data Base (NSRDB), Renewable and Sustainable Energy Reviews, Volume 89, 2018, Pages 51-60.
doi: 10.1016/j.rser.2018.03.003

Additional PVGIS publications are available at: ec.europa.eu/jrc/en/PVGIS/about/who.


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