Geoinformation analysis of wind energy potential in Zhytomyr region
Abstract
The purpose of this article is to conduct a comprehensive geoinformation assessment of the wind energy potential in the Zhytomyr region using advanced GIS technologies and remote sensing data. The research focuses on identifying suitable areas through multi-criteria analysis of constraints and developing recommendations for their rational utilization within the energy sector, ensuring a balance between economic feasibility and environmental safety.
The main material. The paper substantiates the selection of evaluation criteria, including technical parameters (wind speed, proximity to power grids) and environmental determinants (distance to protected areas, forest massifs, and avian migration routes). The study analyzes the spatial distribution of wind resources in Zhytomyr region within the context of Ukraine’s current energy security challenges. Despite the region’s moderate wind characteristics, the development of wind energy is argued to be a viable alternative to the contentious exploitation of landscapes in the Carpathian region. Based on Weighted Linear Combination (WLC) analysis, the most promising zones for wind farm localization were identified. It was established that the total area of highly suitable land amounts to 264.41 hectares, primarily concentrated in the southern part of the region (Berdychiv and Zhytomyr districts) and on the loess plateaus of the Slovechansko-Ovruch ridge. Particular attention is paid to the verification of results by comparing them with existing municipal investment plans (notably those of the Barashivka territorial community).
Conclusions and further research. In the course of the research, a series of thematic maps were developed, visualizing the suitability of territories for wind farm construction. It was determined that the leaders in terms of high-suitability land area are the Krasnopil, Ruzhyn, and Vchoraishe communities. The formulated results have practical significance for business entities in choosing starter sites, local self-government bodies for spatial planning of communities, and for the educational process in studying applied aspects of cartography and sustainable regional development.
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References
Kudria, S. O. (Ed.). (2020). Atlas enerhetychnoho potentsialu vidnovliuvanykh dzherel enerhii Ukrainy [Atlas of renewable energy potential of Ukraine]. Institute of Renewable Energy of the NAS of Ukraine. [in Ukrainian].
Bohatov, Yu. M., Zakharkiv, I. V., & Ishchenko, O. P. (2017). Enerhetychnyi potentsial ta otsinka efektyvnosti vykorystannia vidnovliuvanykh dzherel enerhii [Energy potential and assessment of the efficiency of using renewable energy sources]. NUBiP of Ukraine. [in Ukrainian].
Vplyv vitrianykh elektrostantsii na navkolishnie seredovyshche [Impact of wind power plants on the environment]. (n.d.). https://alternative-energy.com.ua/vpliv-vitryanih-elektrostanczij-na-navkolishn%D1%94-seredovishhe/ [in Ukrainian].
Kudria, S. O. (2020). Vidnovliuvani dzherel enerhii [Renewable energy sources]. Institute of Renewable Energy of the NASU. [in Ukrainian].
Moskalchuk, N. M., & Adamenko, Ya. O. (2019). Vybir maidanchyka dlia roztashuvannia vitroelektrostantsii na pidstavi HISpidkhodu [Site selection for wind power plants based on the GIS approach]. Scientific Bulletin of UNFU, 29(6), 71–75. [in Ukrainian].
Chyliaretskyi, P., & Paslavska, A. (2019). Posibnyk z otsinky vplyvu vitroelektrostantsii na ptakhiv [Manual for assessing the impact of wind power plants on birds]. [in Ukrainian].
Shykhailov, M. O. (2004). Problemy ta rozvytok maloi vitroenerhetyky v Ukraini [Problems and development of small wind energy in Ukraine]. Promelektro, (5), 51–56. [in Ukrainian].
Ayodele, T. R., Ogunjuyigbe, A. S. O., Odigie, O., & Munda, J. L. (2018). A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria. Applied Energy, 228, 1853–1869. https://doi.org/10.1016/j.apenergy.2018.07.051 [in English].
Li, G., & Zhi, J. (2016). Analysis of Wind Power Characteristics. In I. Dincer (Ed.), Comprehensive Energy Systems (Vol. 2, pp. 37–85). Academic Press. https://doi.org/10.1016/B978-0-12-849895-8.00002-6 [in English].
Moradi, S., Yousefi, H., Noorollahi, Y., & Rosso, D. (2020). Multi-criteria decision support system for wind farm site selection and sensitivity analysis: Case study of Alborz Province, Iran. Energy Strategy Reviews, 29, 100478. https://doi.org/10.1016/j.esr.2020.100478 [in English].
O’Sullivan, C. (2020). Blog: Draft Revised Wind Energy Development Guidelines. IWEA Blog. https://windenergyireland.com/latestnews/3180-blog-draft-revised-wind-energy-development-guidelines [in English].
Sánchez-Lozano, J. M., García-Cascales, M. S., & Lamata, M. T. (2016). GIS-based on-shore wind farm site selection using Fuzzy Multi-Criteria Decision Making methods, evaluating the case of Southeastern Spain. Applied Energy, 171, 86–102. https://doi.org/10.1016/j.apenergy.2016.03.030 [in English].
Tercan, E. (2021). Land suitability assessment for wind farms through best-worst method and GIS in Balıkesir province of Turkey. Sustainable Energy Technologies and Assessments, 47, 101491. https://doi.org/10.1016/j.seta.2021.101491 [in English].
Zalhaf, A. S., Elboshy, B., Kotb, K. M., Han, Y., Almaliki, A. H., Aly, R., & Elkadeem, M. R. (2021). A High-Resolution Wind Farms Suitability Mapping Using GIS and Fuzzy AHP Approach: A National-Level Case Study in Sudan. Sustainability, 14(1), 358. https://doi.org/10.3390/su14010358 [in English].
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