Geospatial analysis of the potential of the territories of Ukraine for the placement of solar power plants based on satellite data

1Kussul, NM, 2Drozd, SYu.
1Space Research Institute of the NAS of Ukraine and the SSA of Ukraine, Kyiv, Ukraine; NTTU "Igor Sikorsky Kyiv Politechnic Institute", Kyiv, Ukraine
2Space Research Institute of the NAS of Ukraine and SSA of Ukraine, Kyiv, Ukraine
Space Sci. & Technol. 2024, 30 ;(1):31-43
https://doi.org/10.15407/knit2024.01.031
Язык публикации: Ukrainian
Аннотация: 
Climate change necessitates the relevance of renewable energy utilization worldwide. The Green Deal defines the energy development policy in Europe until 2030. This challenge holds particular significance for Ukraine in the context of post-war energy infrastructure recovery. Therefore, an important issue is the analysis of the suitability of Ukrainian territories for the installation of large-scale solar power plants (solar farms) and the optimization of their placement. This research aims to determine the suitability of Ukrainian territories for solar power plant placement using satellite data on climate and terrain characteristics. Among the factors determining the suitability of the territory for solar farms, the greatest impact lies in climatic indicators, including data on the total global horizontal solar irradiation (GHI), accumulated temperature above 25°C at a height of 2 meters, average annual wind speed, and map of accumulated annual precipitation from the ERA5-Land dataset.
       In this study, terrain maps containing information on elevations, slopes, and terrain shading from the Shuttle Radar Topography Mission (SRTM) project were also used to determine the suitability of the territories. The suitability of the territories is determined through geospatial analysis using weighted sums. Based on the research results, a suitability map was constructed, depicting the distribution of zones with different suitability coefficients (ranging from 0 to 1). It was found that a significant portion of Ukraine's territory is favorable for the placement of solar power plants. Over 48% of the country has moderate suitability values (0.3-0.4). The best conditions for solar farms are observed in the southern regions of Ukraine. The obtained suitability map was used to analyze the optimal placement of already constructed major solar power plants in Ukraine. Data from Wikimapia was utilized to determine the locations of these energy facilities. Overall, all the analyzed large-scale solar power plants in Ukraine were situated in optimal territories. The research also revealed that certain regions, such as Odessa, Poltava, Kharkiv, Zaporizhia, Dnipropetrovsk, Donetsk, and Luhansk, have good suitability values (0.3-0.4) but are not fully utilized. These areas have significant potential for future construction of powerful and productive solar power plants.
Ключевые слова: climate, geospatial analysis, method of weighted sums, relief, satellite data, solar power plants, suitability of territories
References: 

1. Butenko O., Zvyaschenko K., Buravchenko K., Nikitin A. (2019). Optimization of the process of selecting the location of solar power plants using GIS analysis. Systemy upravlinnya, navigatsii ta zv'yazku. Zbirnyk naukovykh prats, 1(53), 17-21 [in Ukrainian]
https://doi.org/10.26906/SUNZ.2019.1.017

2. Chandra S., Agrawal S., Chauhan D. S. (2018). Effect of Ambient Temperature and Wind Speed on Performance Ratio of Polycrystalline Solar Photovoltaic Module: an Experimental Analysis. Int. Energy J., 18, 171-179.

3. Charabi Y., Gastli A. (2011). PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation. Renewable Energy, 36, 2554-2561.
https://doi.org/10.1016/j.renene.2010.10.037

4. Chitturi S., Sharma E., Elmenreich W. (2018). Efficiency of photovoltaic systems in mountainous areas. 2018 IEEE Int. Energy Conf. (ENERGYCON), 1-6.
https://doi.org/10.1109/ENERGYCON.2018.8398766

5. Dubey S., Sarvaiya J. N., Seshadri B. (2013). Temperature Dependent Photovoltaic (PV) Efficiency and Its Effect on PV Production in the World - A Review. Energy Procedia, 33, 311-321.
https://doi.org/10.1016/j.egypro.2013.05.072

6. Effat H. A. (2013). Selection of Potential Sites for Solar Energy Farms in Ismailia Governorate, Egypt using SRTM and Multicriteria Analysis. Int. J. Adv. Remote Sensing and GIS, 2, 205-220.

7. Fazelpour F., Vafaeipour M., Rahbari O., Shirmohammadi R. (2013). Considerable parameters of using PV cells for solarpowered aircrafts. Renewable & Sustainable Energy Reviews, 22, 81-91.
https://doi.org/10.1016/j.rser.2013.01.016

8. Gokmen N., Hu W., Hou P., Chen Z., Sera D., Spataru S. V. (2016). Investigation of wind speed cooling effect on PV panels in windy locations. Renewable Energy, 90, 283-290.
https://doi.org/10.1016/j.renene.2016.01.017

9. Goossens D., Kerschaever E. V. (1999). Aeolian dust deposition on photovoltaic solar cells: the effects of wind velocity and airborne dust concentration on cell performance. Solar Energy, 66, 277-289.
https://doi.org/10.1016/S0038-092X(99)00028-6

10. Generation as of May lost 27 GW of installed capacity. Ukrinform. (2 023). URL: https://www.ukrinform.ua/rubriceconomy/ 3714703-generacia-stanom-na-traven-vtratila-27-gvt-vstanovlenoi-potuznosti-ukrenergo.html (Last accessed: 19.07.2023).

11. Heo J., Moon H., Chang S., Han S., Lee D. (2021). Case study of solar photovoltaic power-plant site selection for infrastructure planning using a BIM-GIS-based approach. Appl. Sci., 11(18), 8785.
https://doi.org/10.3390/app11188785

12. Ibrahim A., Fudholi A., Sopian K., Othman M. Y., Ruslan M. H. (2014). Efficiencies and improvement potential of building integrated photovoltaic thermal (BIPVT) system. Energy Conversion and Management, 77, 527-534.
https://doi.org/10.1016/j.enconman.2013.10.033

13. Idoko L., Anaya Lara O., McDonald A. S. (2018). Enhancing PV modules efficiency and power output using multi-concept cooling technique. Energy Reports, 4, 357-369.
https://doi.org/10.1016/j.egyr.2018.05.004

14. Imamverdiyev N. S. (2021). Site selection for solar photovoltaic system installation using analytical hierarchy process model in Azerbaijan. J. Belarusian State Univ. Geography and Geology, № 1, 75-92.
https://doi.org/10.33581/2521-6740-2021-1-75-92

15. Kaldellis J. K., Kapsali M., Kavadias K. A. (2014). Temperature and wind speed impact on the efficiency of PV installations. Experience obtained from outdoor measurements in Greece. Renewable Energy, 66, 612-624.
https://doi.org/10.1016/j.renene.2013.12.041

16. Kim G. G., Choi J. H., Park S. Y., Bhang B. G., Nam W. J., Cha H. L., Park N., Ahn H. K. (2019). Prediction Model for PV Performance with correlation analysis of environmental variables. IEEE J. Photovoltaics, 9, 832-841.
https://doi.org/10.1109/JPHOTOV.2019.2898521

17. Kussul N. N., Lavreniuk N. S., Shelestov, A. Y., Yailymov B., Butko I. (2016). Land cover changes analysis based on deep machine learning technique. J. Automation and Inform. Sci., 48, 42-54.
https://doi.org/10.1615/JAutomatInfScien.v48.i5.40

18. Mahtta R., Joshi P. K., Jindal A. K. (2014). Solar power potential mapping in India using remote sensing inputs and environmental parameters. Renewable Energy, 71, 255-262.
https://doi.org/10.1016/j.renene.2014.05.037

19. Mekhilef S., Saidur R., Kamalisarvestani M. (2012). Effect of dust, humidity and air velocity on efficiency of photovoltaic cells. Renewable & Sustainable Energy Reviews, 16, 2920-2925.
https://doi.org/10.1016/j.rser.2012.02.012

20. Mohammadi K., Goudarzi N. (2018). Study of inter-correlations of solar radiation, wind speed and precipitation under the influence of El Niño Southern Oscillation (ENSO) in California. Renewable Energy, 120, 190-200.
https://doi.org/10.1016/j.renene.2017.12.069

21. Muhsin N., Ali W., Alzubaidy Z. (2021). The effect of temperature and other conditions on efficiency of solar panels. J. Advs in Electrical Devices, 6(03), 8-14.

22. Mustafa R. J., Gomaa M. R., Al-Dhaifallah M., Rezk H. (2020). Environmental impacts on the performance of solar photovoltaic systems. Sustainability, 12(2), 608.
https://doi.org/10.3390/su12020608

23. Razak A. B., Irwan Y. M., Leow W. Z., Irwanto M., Safwati I., Zhafarina M. (2016). Investigation of the effect temperature on photovoltaic (PV) panel output performance. Int. J. Adv. Sci., Engineering and Inform. Technol., 6, 682-688.
https://doi.org/10.18517/ijaseit.6.5.938

24. Shelestov A. Y., Kussul N. N. (2008). Using the fuzzy-ellipsoid method for robust estimation of the state of a grid system node. Cybernetics and Systems Analysis, 44, 847-854.
https://doi.org/10.1007/s10559-008-9057-1

25. Shorabeh S. N., Firozjaei M. K., Nematollahi O., Firozjaei H. K., Jelokhani-Niaraki M. (2019). A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: A case study in Iran. Renewable Energy, 143, 958-973.
https://doi.org/10.1016/j.renene.2019.05.063

26. Vilanova A., Kim B., Kim C. K., Kim H. (2020). Linear-gompertz model-based regression of photovoltaic power generation by satellite imagery-based solar irradiance. Energies, 13(4), 781.
https://doi.org/10.3390/en13040781

27. Yelisieieva O. K., Khazan P. V. (2016). Economic and statistical analysis of solar energy in Ukrainian regions. Statystyka Ukrainy, 4, 51-58 [in Ukrainian]