Suitability assessment of wind energy farming in the desert landscape of Zarafshan Valley, Uzbekistan

DOI: 10.35595/2414-9179-2024-1-30-179-192

Посмотреть или загрузить статью (Eng)

Об авторах

Mohammad Suhail

Centre of Applied Remote Sensing and GIS Applications, Samarkand State University,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,
E-mail: netgeo.suhail@gmail.com

Mohd Nazish Khan

Transformation Office, Samarkand State University,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,
E-mail: nazishgeo@gmail.com

Alikul X. Ravshanov

Department of Socioeconomic Geography, Samarkand State University,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,
E-mail: ravshanov1401@gmail.com

Marufdjan Usmanov

Department of Socioeconomic Geography, Samarkand State University,
15, Universitetsky blvd., Samarkand, 140104, Uzbekistan,
E-mail: usmaruf1974@gmail.com

Аннотация

Wind farm suitability analyses have been carried out to demarcate the potential zones in the Middle Zarafshan River basin. Uzbekistan’s major cities occupy the middle and lower Zarafshan Valley, which needs to allocate and develop wind energy farms to restore sustainability. In the current study, the Middle Zarafshan valley was assessed to provide a synoptic view of potential zones for wind energy. This study aimed to develop a geospatial method to identify optimal locations in the valley. To accomplish this task, five criteria were considered: wind speed, slope, distance from the transmission network, road network, land use, and land cover. Further, each criterion was assigned a weight according to expert opinions and published research outcomes. In addition, a maximum of 45 % weight was assigned to wind speed, followed by land use, land cover, slope, and others. Further, these criteria were categorized into four classes viz., unsuitable, less suitable, moderately suitable, and highly suitable. Further, different thematic layers were produced to realize this study. Wind speed maps were derived at different heights to calculate the results and integrate them with other derivatives. The findings of this study show that the maximum intensity of winds received at 100 m height or more, and more than 40 % area of the study area was estimated suitable for wind energy exploitation.

Ключ. слова

wind energy, renewable energy, suitability analysis, Zarafshan Valley, Arid Region, GIS

Список литературы

  1. Abas N., Kalair A., Khan N. Review of fossil fuels and future energy technologies. Futures, 2015. V. 69. P. 31–49.
  2. Adedeji P.A., Akinlabi S.A., Madushele N., Olatunji O.O. Hybrid neuro-fuzzy wind power forecast and wind turbine location for embedded generation. International Journal of Energy Research, 2021. V. 45. P. 413–428.
  3. Ahmed M., Ahmad F., Akhtar M. Assessment of Wind Power Potential for Coastal Areas of Pakistan. Turkish Journal of Physics, 2006. P. 30.
  4. Aktas A., Kabak M. A model proposal for locating wind turbines. Procedia Computer Science, 2016. V. 102. P. 426–433.
  5. Aliyu A.K., Modu B., Tan C.W. A review of renewable energy development in Africa: A focus in South Africa, Egypt and Nigeria. Renewable and Sustainable Energy Reviews, 2018. V. 81. P. 2502–2518. DOI: 10.1016/j.rser.2017.06.055.
  6. Amarasinghe A., Perera E. Modeling predictive suitability to determine potential areas for establishing wind power plants in Sri Lanka. Model Earth System Environment, 2021. V. 7. P. 443–454.
  7. Amuzu-Sefordzi B., Martinus K., Tschakert P., Wills R. Disruptive innovations and decentralized renewable energy systems in Africa: A sociotechnical review. Energy Research & Social Science, 2018. V. 46. P. 140–154. DOI: 10.1016/j.erss.2018.06.014.
  8. Avezova N., Khaitmukhamedov A., Vokhidov A. Uzbekistan renewable energy short overview: Programs and prospects. IJESG, 2017. V. 2. P. 43–46. DOI: 10.23884/IJESG.2017.2.2.03.
  9. Barreto R.A. Fossil fuels, alternative energy and economic growth. Economic Modelling, 2018. V. 75. P. 196–220.
  10. Baydyk T., Kussul E., Wunsch II D.C. Renewable energy: solar, wind, and others. Intelligent automation in renewable energy. Cham: Springer, 2019. P. 1–11.
  11. Bersalli G., Menanteau P., El-Methni J. Renewable energy policy effectiveness: A panel data analysis across Europe and Latin America. Renewable and Sustainable Energy Reviews, 2020. V. 133. 110351. DOI: 10.1016/j.rser.2020.110351.
  12. Brunet C., Savadogo O., Baptiste P., Bouchard M.A. Shedding some light on photovoltaic solar energy in Africa—A literature review. Renewable and Sustainable Energy Reviews, 2018. V. 96. P. 325–342. DOI: 10.1016/j.rser.2018.08.004.
  13. Bugaje I.M. Renewable energy for sustainable development in Africa: a review. Renewable and Sustainable Energy Reviews, 2006. V. 10. P. 603–612. DOI: 10.1016/j.rser.2004.11.002.
  14. Chamundeswari V., Niraimathi R., Shanthi M., Subahani A. Renewable energy technologies. John Wiley & Sons, 2021. P. 1–18.
  15. Da Silva P.P., Cerqueira P.A., Ogbe W. Determinants of renewable energy growth in sub-Saharan Africa: Evidence from panel ARDL. Energy, 2018. V. 156. P. 45–54. DOI: 10.1016/j.energy.2018.05.068.
  16. Farooq S., Sharma I., Khan M.N. Geomorphic evidence of active tectonics in eastern Kumaon Himalaya as deciphered from the morphometry of Ramganga River basin. International Journal of Advancement in Earth and Environmental Sciences, 2015. V. 3. No. 1. P. 30–39.
  17. Hyvärinen A. Wind turbines over a hilly terrain: performance and wake evolution. (Licentiate thesis, comprehensive summary), KTH Royal Institute of Technology, Stockholm, 2018. DiVA database. Web resource: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-221675 (accessed 10.19.2024).
  18. Kahatapitiya C., Jayasooriya V., Muthukumaran S. GIS-based weighted overlay model for wind and solar farm locating in Sri Lanka. Environmental Science and Pollution Research, 2022. V. 30. DOI: 10.1007/s11356-022-24595-0.
  19. Katsaprakakis D.A., Papadakis N., Ntintakis I. A comprehensive analysis of wind turbine blade damage. Energies, 2021. V. 14. P. 59–74.
  20. Khan M.S., Suhail M., Alharbi T. Evaluation of urban growth and land use transformation in Riyadh using Landsat satellite data. Arab Journal of Geosciences, 2018. V. 11. P. 540. DOI: 10.1007/s12517-018-3896-5.
  21. Kochnakyan A., Khosla S.K., Buranov I., Hofer K., Hankinson D., Finn J. Uzbekistan Energy/Power Sector Issues Note (Report No. ACS4146). World Bank, Washington, D.C., 2013.
  22. Laldjebaev M., Isaev R., Saukhimov A. Renewable energy in Central Asia: An overview of potentials, deployment, outlook, and barriers. Energy Reports, 2021. V. 7. P. 3125–3136. DOI: 10.1016/j.egyr.2021.05.014.
  23. Li L., Lin J., Wu N., Xie S., Meng C., Zheng Y., Wang X., Zhao Y. Review and outlook on the international renewable energy development. Energy and Built Environment, 2020. DOI: 10.1016/j.enbenv.2020.12.002.
  24. McWilliam M., Van Kooten G., Crawford C. A method for optimizing the location of wind farms. Renewable Energy, 2012. V. 48. P. 287–299.
  25. Ouedraogo N.S. Opportunities, barriers, and issues with renewable energy development in Africa: a comprehensible review. Current Sustainable/Renewable Energy Reports, 2019. V. 6. P. 52–60. DOI: 10.1007/s40518019-00130-7.
  26. Pao L.Y., Johnson K.E. A tutorial on the dynamics and control of wind turbines and wind farms. 2009—American Control Conference. IEEE, 2009. P. 2076–2089.
  27. Rahman A., Farrok O., Haque M.M. Environmental impact of renewable energy source based electrical power plants: solar, wind, hydroelectric, biomass, geothermal, tidal, ocean, and osmotic. Renewable and Sustainable Energy Reviews, 2022. P. 161.
  28. Roehrkasten S. Global governance on renewable energy. Global Governance on Renewable Energy. Springer, 2015.
  29. Shadrina E. Non-hydropower renewable energy in central Asia: Assessment of deployment status and analysis of underlying factors. Energies, 2020. V. 13. P. 2963. DOI: 10.3390/en13112963.
  30. Shata A., Ahmed S., Hanitsch R. The potential of electricity generation on the east coast of Red Sea in Egypt. Renewable Energy, 2006. V. 31. No. 10. P. 1597–1615. DOI: 10.1016/j.renene.2005.09.026.
  31. Singer S., Denruyter J.P., Yener D. The energy report: 100 % renewable energy by 2050. Towards 100 % renewable energy. Springer, 2017.
  32. Suhail M., Khan M.S., Faridi R.A. Assessment of Urban Heat Islands Effect and Land Surface Temperature of Noida, India by Using Landsat Satellite Data. MAPAN, 2019. V. 34. P. 431–441. DOI: 10.1007/s12647-019-00309-9.
  33. Thomas A., Lennart S. An overview of wind energy status 2002. Renewable and Sustainable Energy Reviews, 2002. V. 6. P. 67–128.
  34. UNDP. United Nations report on migration, 2014. Web resource: https://www.undp.org/sites/g/files/zskgke326/files/migration/eurasia/Uzbekistan.pdf (accessed 10.19.2024).
  35. Whiting K., Carmona L.G., Sousa T. A review of the use of exergy to evaluate the sustainability of fossil fuels and non-fuel mineral depletion. Renewable and Sustainable Energy Reviews, 2017. V. 76. P. 202–211.
  36. Xu X., Wei Z., Ji Q., Wang C., Gao G. Global renewable energy development: Influencing factors, trend predictions and countermeasures. Resources Policy, 2019. V. 63. 101470. DOI: 10.1016/j.resourpol.2019.101470.

Для цитирования: Suhail M., Khan M.N., Ravshanov A.X., Usmanov M. Suitability assessment of wind energy farming in the desert landscape of Zarafshan Valley, Uzbekistan. ИнтерКарто. ИнтерГИС. M.: Географический факультет МГУ, 2024. Т. 30. Ч. 1. С. 179–192. DOI: 10.35595/2414-9179-2024-1-30-179-192

For citation: Suhail M., Khan M.N., Ravshanov A.X., Usmanov M. Suitability assessment of wind energy farming in the desert landscape of Zarafshan Valley, Uzbekistan. InterCarto. InterGIS. Moscow: MSU, Faculty of Geography, 2024. V. 30. Part 1. P. 179–192. DOI: 10.35595/2414-9179-2024-1-30-179-192