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RÜZGÂR ENERJİSİ SANTRALİ PLANLAMASINDA CBS VE AHP KULLANIMI: AĞRI İLİ ÜZERİNE BİR DEĞERLENDİRME

Yıl 2026, Cilt: 29 Sayı: 1, 13 - 34, 03.03.2026

Çağrı Mercan

https://doi.org/10.17780/ksujes.1658900
https://izlik.org/JA76XH53MZ

Öz

Teknolojik gelişmeler ve nüfus artışı, çevresel bozulmayı ve iklim değişikliğini hızlandırarak enerji talebini önemli ölçüde artırdı. Bu durum, yenilenebilir enerjiye yönelimi zorunlu kılmaktadır. Rüzgâr enerjisi, düşük karbon ayak izi ve sürdürülebilirliği ile önemli bir alternatif olarak öne çıkmaktadır. Bu bağlamda, rüzgâr enerjisi potansiyelinin optimal kullanımı için uygun alanların belirlenmesi kritik önem taşımaktadır. Bu çalışma, Coğrafi Bilgi Sistemleri (CBS) tabanlı Analitik Hiyerarşi Süreci (AHP) yöntemi ile Türkiye'nin Ağrı ilinde rüzgâr enerjisi santrali (RES) için en uygun alanları belirlemeyi amaçlamaktadır. Rüzgâr hızı, arazi örtüsü, enerji iletim hatlarına uzaklık, eğim, yol ağına yakınlık, kentsel alanlara mesafe, trafo merkezlerine uzaklık, korunan alanlara mesafe, fay hatları ve heyelan bölgelerine uzaklık olmak üzere on farklı kriter değerlendirilmiştir. AHP ile belirlenen kriter ağırlıkları doğrultusunda uygunluk haritası oluşturulmuş ve sonuçların güvenilirliğini test etmek amacıyla duyarlılık analizi yapılmıştır. Bulgular, çalışma alanının %66,3’ünün RES için uygun olmadığını, %33,7’sinin ise farklı uygunluk seviyelerine sahip olduğunu göstermektedir. Özellikle Taşlıçay ilçesi en yüksek uygunluk kategorisinde öne çıkmıştır. Mevcut RES alanları ile karşılaştırıldığında, bazı santrallerin jeolojik riskler nedeniyle düşük uygunluk gösteren alanlarda konumlandığı belirlenmiştir. Bu çalışma, CBS-AHP yönteminin sürdürülebilir enerji planlamasındaki etkinliğini vurgulayarak, karar vericilere bilimsel bir çerçeve sunmaktadır. Gelecekteki çalışmalarda farklı ÇKKV yöntemlerinin karşılaştırmalı analizi ve daha detaylı jeoteknik değerlendirmelerin entegrasyonu önerilmektedir.

Anahtar Kelimeler

analitik hiyerarşi süreci arazi uygunluk değerlendirmesi sürdürülebilir enerji planlaması

Kaynakça

  • Abdullah, A. G., Setiorini, A. H., Dwitasari, N. A., Hakim, D. L., & Aziz, M. (2021). Location suitability analysis for wind farm exploitation using fuzzy analytic hierarchy process. Indonesian Journal of Science and Technology, 6(3), 523-534. https://doi.org/10.17509/ijost.v6i3.38957
  • Aghaloo, K., Ali, T., Chiu, Y.-R., & Sharifi, A. (2023). Optimal site selection for the solar-wind hybrid renewable energy systems in Bangladesh using an integrated GIS-based BWM-fuzzy logic method. Energy Conversion and Management, 283, 116899. https://doi.org/10.1016/j.enconman.2023.116899
  • Ajanaku, B. A., Strager, M. P., & Collins, A. R. (2021). GIS-based multi-criteria decision analysis of utility-scale wind farm site suitability in West Virginia. GeoJournal, 87(5), 3735-3757. https://doi.org/10.1007/s10708-021-10453-y
  • Amiri, A. A., Wahid, M. N., Al-Buraiki, A. S., & Al-Sharafi, A. (2024). A strategic multi-criteria decision-making framework for renewable energy source selection in Saudi Arabia using AHP-TOPSIS. Renewable Energy, 236, 121523. https://doi.org/10.1016/j.renene.2024.121523
  • Arslan, H., Baltaci, H., Akkoyunlu, B. O., Karanfil, S., & Tayanc, M. (2020). Wind speed variability and wind power potential over Turkey: Case studies for Çanakkale and İstanbul. Renewable Energy, 145, 1020-1032. https://doi.org/10.1016/j.renene.2019.06.128
  • Ayalke, Z. G., & Şişman, A. (2022). Site selection for wind farms using geographic information system with best-worst method: A case study Amhara Region of Ethiopia. Advanced Land Management, 2(2), 69-78.
  • Azizi, A., Malekmohammadi, B., Jafari, H. R., Nasiri, H., & Amini Parsa, V. (2014). Land suitability assessment for wind power plant site selection using ANP-DEMATEL in a GIS environment: case study of Ardabil province, Iran. Environ Monit Assess, 186(10), 6695-6709. https://doi.org/10.1007/s10661-014-3883-6
  • Badi, I., Pamučar, D., Stević, Ž., & Muhammad, L. J. (2023). Wind farm site selection using BWM-AHP-MARCOS method: A case study of Libya. Scientific African, 19. https://doi.org/10.1016/j.sciaf.2022.e01511
  • Barzehkar, M., Parnell, K. E., Mobarghaee Dinan, N., & Brodie, G. (2020). Decision support tools for wind and solar farm site selection in Isfahan Province, Iran. Clean Technologies and Environmental Policy, 23(4), 1179-1195. https://doi.org/10.1007/s10098-020-01978-w
  • Baseer, M. A., Rehman, S., Meyer, J. P., & Alam, M. M. (2017). GIS-based site suitability analysis for wind farm development in Saudi Arabia. Energy, 141, 1166-1176. https://doi.org/10.1016/j.energy.2017.10.016
  • Benti, N. E., Alemu, Y. B., Balta, M. M., Gunta, S., Chaka, M. D., Semie, A. G., Mekonnen, Y. S., & Yohannes, H. (2023). Site suitability assessment for the development of wind power plant in Wolaita area, Southern Ethiopia: an AHP-GIS model. Scientific Reports, 13(1), 19811. https://doi.org/10.1038/s41598-023-47149-x
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GIS AND AHP UTILIZATION IN WIND ENERGY POWER PLANT PLANNING: AN ASSESSMENT OF AĞRI PROVINCE

Yıl 2026, Cilt: 29 Sayı: 1, 13 - 34, 03.03.2026

Çağrı Mercan

https://doi.org/10.17780/ksujes.1658900
https://izlik.org/JA76XH53MZ

Öz

Technological advancements and population growth have significantly increased energy demand, accelerating environmental degradation and climate change. This necessitates a transition to renewable energy, with wind energy emerging as a key alternative due to its sustainability and low carbon footprint. Identifying optimal locations for wind farms is therefore crucial. This study employs a Geographic Information System (GIS)-based Analytical Hierarchy Process (AHP) to determine suitable wind energy sites in Ağrı, Turkey. Ten criteria were analyzed, including wind speed, land cover, slope, proximity to infrastructure, urban areas, fault lines, and environmentally sensitive zones. A suitability map was generated based on AHP-derived weights, and a sensitivity analysis was conducted to validate the results. Findings indicate that 66.3% of the area is unsuitable, while 33.7% exhibits varying suitability levels, with Taşlıçay district as the most favorable site. A comparison with existing wind farms highlights installations in geologically high-risk zones. The study demonstrates the GIS-AHP approach’s effectiveness in sustainable energy planning and provides a scientific basis for decision-making. Future research should focus on integrating alternative multi-criteria decision-making methods and incorporate detailed geotechnical assessments.

Anahtar Kelimeler

analytical hierarchy process land suitability assessment sustainable energy planning

Kaynakça

  • Abdullah, A. G., Setiorini, A. H., Dwitasari, N. A., Hakim, D. L., & Aziz, M. (2021). Location suitability analysis for wind farm exploitation using fuzzy analytic hierarchy process. Indonesian Journal of Science and Technology, 6(3), 523-534. https://doi.org/10.17509/ijost.v6i3.38957
  • Aghaloo, K., Ali, T., Chiu, Y.-R., & Sharifi, A. (2023). Optimal site selection for the solar-wind hybrid renewable energy systems in Bangladesh using an integrated GIS-based BWM-fuzzy logic method. Energy Conversion and Management, 283, 116899. https://doi.org/10.1016/j.enconman.2023.116899
  • Ajanaku, B. A., Strager, M. P., & Collins, A. R. (2021). GIS-based multi-criteria decision analysis of utility-scale wind farm site suitability in West Virginia. GeoJournal, 87(5), 3735-3757. https://doi.org/10.1007/s10708-021-10453-y
  • Amiri, A. A., Wahid, M. N., Al-Buraiki, A. S., & Al-Sharafi, A. (2024). A strategic multi-criteria decision-making framework for renewable energy source selection in Saudi Arabia using AHP-TOPSIS. Renewable Energy, 236, 121523. https://doi.org/10.1016/j.renene.2024.121523
  • Arslan, H., Baltaci, H., Akkoyunlu, B. O., Karanfil, S., & Tayanc, M. (2020). Wind speed variability and wind power potential over Turkey: Case studies for Çanakkale and İstanbul. Renewable Energy, 145, 1020-1032. https://doi.org/10.1016/j.renene.2019.06.128
  • Ayalke, Z. G., & Şişman, A. (2022). Site selection for wind farms using geographic information system with best-worst method: A case study Amhara Region of Ethiopia. Advanced Land Management, 2(2), 69-78.
  • Azizi, A., Malekmohammadi, B., Jafari, H. R., Nasiri, H., & Amini Parsa, V. (2014). Land suitability assessment for wind power plant site selection using ANP-DEMATEL in a GIS environment: case study of Ardabil province, Iran. Environ Monit Assess, 186(10), 6695-6709. https://doi.org/10.1007/s10661-014-3883-6
  • Badi, I., Pamučar, D., Stević, Ž., & Muhammad, L. J. (2023). Wind farm site selection using BWM-AHP-MARCOS method: A case study of Libya. Scientific African, 19. https://doi.org/10.1016/j.sciaf.2022.e01511
  • Barzehkar, M., Parnell, K. E., Mobarghaee Dinan, N., & Brodie, G. (2020). Decision support tools for wind and solar farm site selection in Isfahan Province, Iran. Clean Technologies and Environmental Policy, 23(4), 1179-1195. https://doi.org/10.1007/s10098-020-01978-w
  • Baseer, M. A., Rehman, S., Meyer, J. P., & Alam, M. M. (2017). GIS-based site suitability analysis for wind farm development in Saudi Arabia. Energy, 141, 1166-1176. https://doi.org/10.1016/j.energy.2017.10.016
  • Benti, N. E., Alemu, Y. B., Balta, M. M., Gunta, S., Chaka, M. D., Semie, A. G., Mekonnen, Y. S., & Yohannes, H. (2023). Site suitability assessment for the development of wind power plant in Wolaita area, Southern Ethiopia: an AHP-GIS model. Scientific Reports, 13(1), 19811. https://doi.org/10.1038/s41598-023-47149-x
  • Bilgili, A., Arda, T., & Kilic, B. (2024). Explainability in wind farm planning: A machine learning framework for automatic site selection of wind farms. Energy Conversion and Management, 309. https://doi.org/10.1016/j.enconman.2024.118441
  • Birdmap. (2025). Birdmap-The interactive Bird Migration Map visualizes migration paths of birds. https://birdmap.5dvision.ee/en/
  • Çolak, Z. (2024). A hybrid MCDM method for enhancing site selection for wind power plants in Turkey. Energy for Sustainable Development, 82. https://doi.org/10.1016/j.esd.2024.101536
  • Dinçer, F., (2025). Şebeke Bağlantılı Güneş Enerjisi Santrali Yatırımı İçin Modelleme ve Simülasyon Analizi: Ilgın/Konya Örneği. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 28(1), 112-128. https://doi.org/10.17780/ksujes.1523469
  • Ekiz, S., Şirin, A., & Erener, A. (2021). En uygun rüzgâr enerji santrali yerlerinin coğrafi bilgi sistemleri ile belirlenmesi: Kocaeli ili örneği. Journal of Geodesy and Geoinformation, 9(1), 59-79. https://doi.org/10.9733/jgg.2022r0005.T
  • Elkadeem, M. R., Younes, A., Sharshir, S. W., Campana, P. E., & Wang, S. (2021). Sustainable siting and design optimization of hybrid renewable energy system: A geospatial multi-criteria analysis. Applied Energy, 295. https://doi.org/10.1016/j.apenergy.2021.117071
  • Eroğlu, H. (2021). Multi-criteria decision analysis for wind power plant location selection based on fuzzy AHP and geographic information systems. Environment, Development and Sustainability, 23(12), 18278-18310. https://doi.org/10.1007/s10668-021-01438-5
  • Flora, F. M. I., Donatien, N., Tchinda, R., & Hamandjoda, O. (2021). Selection wind farm sites based on GIS using a boolean method: evaluation of the case of Cameroon. Journal of Power and Energy Engineering, 9(1), 1-24. https://doi.org/10.4236/jpee.2021.91001
  • Franke, K., Garcia, J. F., Kleinschmitt, C., & Sensfuß, F. (2024). Assessing worldwide future potentials of renewable electricity generation: Installable capacity, full load hours and costs. Renewable Energy, 226. https://doi.org/10.1016/j.renene.2024.120376
  • GWA. (2025). Global Wind Atlas. https://globalwindatlas.info/en/about/KeyFeatures Hosseini Dehshiri, S. S., & Hosseini Dehshiri, S. J. (2022). Locating wind farm for power and hydrogen production based on Geographic information system and multi-criteria decision making method: An application. International Journal of Hydrogen Energy, 47(58), 24569-24583. https://doi.org/10.1016/j.ijhydene.2022.03.083
  • Ifkirne, M., El Bouhi, H., Acharki, S., Pham, Q. B., Farah, A., & Linh, N. T. T. (2022). Multi-Criteria GIS-Based Analysis for Mapping Suitable Sites for Onshore Wind Farms in Southeast France. Land, 11(10). https://doi.org/10.3390/land11101839
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  • Karataş, K., & Bıçakcı, C. (2025). Creation of Wind Speed Maps and Determination of Wind Energy Potential with Geographic Information Systems: The Case of Kırklareli Province, Türkiye. Sustainability, 17(3). https://doi.org/10.3390/su17031185
  • Koc, A., Turk, S., & Sahin, G. (2019). Multi-criteria of wind-solar site selection problem using a GIS-AHP-based approach with an application in Igdir Province/Turkey. Environ Sci Pollut Res Int, 26(31), 32298-32310. https://doi.org/10.1007/s11356-019-06260-1
  • Latinopoulos, D., & Kechagia, K. (2015). A GIS-based multi-criteria evaluation for wind farm site selection. A regional scale application in Greece. Renewable Energy, 78, 550-560. https://doi.org/10.1016/j.renene.2015.01.041
  • Malczewski, J. (1999). GIS and Multicriteria Decision Analysis. (John Wiley and Sons: New York.). In: USA.
  • Mercan, Ç. (2025). Assessment of walnut (Juglans regia L.) cultivation land suitability using a multiple-criteria decision-making method in Southeastern Turkey. Scientific Reports, 15(1), 2716. https://doi.org/10.1038/s41598-025-87110-8
  • Mercan, Ç., & Acibuca, V. (2023). Land Suitability Assessment for Pistachio Cultivation Using GIS and Multi-Criteria Decision-Making: A Case Study of Mardin, Turkey. Environmental Monitoring and Assessment, 195(11), 1300. https://doi.org/10.1007/s10661-023-11899-y
  • Mercan, Ç. (2023). Coğrafi bilgi sistemi ve AHP ile arıcılık faaliyet alanları için arazi uygunluk değerlendirmesi: Bitlis/Türkiye Örneği. Uludağ Arıcılık Dergisi, 23(1), 61-77. https://doi.org/10.31467/uluaricilik.1245078
  • MGM. (2025). Meteoroloji Genel Müdürlüğü. Resmi istatstikler. https://mgm.gov.tr/veridegerlendirme/il-ve-ilceler-istatistik.aspx?k=A&m=MARDIN
  • Molla, S., Farrok, O., & Alam, M. J. (2024). Electrical energy and the environment: Prospects and upcoming challenges of the World's top leading countries. Renewable and Sustainable Energy Reviews, 191. https://doi.org/10.1016/j.rser.2023.114177
  • 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. https://doi.org/10.1016/j.esr.2020.100478
  • Moslem, S. (2024). A novel parsimonious spherical fuzzy analytic hierarchy process for sustainable urban transport solutions. Engineering Applications of Artificial Intelligence, 128. https://doi.org/10.1016/j.engappai.2023.107447
  • Mutlu, S. (2022). Balık Gölü fay zonu’nun paleosismolojik özellikleri ve segmentasyonu. Van Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü (Yayınlanmamış doktora tezi).
  • Mutlu, S. (2025). Iğdır Fay Zonu’nun Doğu Anadolu Kısalmalı Tektonik Bloğu içerisindeki önemi ve Morfotektonik Özellikleri. Türkiye Jeoloji Bülteni, 68(2), 225-258. https://doi.org/10.25288/tjb.1627676
  • Nagababu, G., Puppala, H., Pritam, K., & Kantipudi, M. V. V. P. (2022). Two-stage GIS-MCDM based algorithm to identify plausible regions at micro level to install wind farms: A case study of India. Energy, 248. https://doi.org/10.1016/j.energy.2022.123594
  • Nasery, S., Matci, D. K., & Avdan, U. (2021). GIS-based wind farm suitability assessment using fuzzy AHP multi-criteria approach: the case of Herat, Afghanistan. Arabian Journal of Geosciences, 14(12). https://doi.org/10.1007/s12517-021-07478-5
  • Nekhay, O., Arriaza, M., & Guzmán-Álvarez, J. R. (2009). Spatial analysis of the suitability of olive plantations for wildlife habitat restoration. Computers and Electronics in Agriculture, 65(1), 49-64. https://doi.org/10.1016/j.compag.2008.07.012
  • Noorollahi, Y., Yousefi, H., & Mohammadi, M. (2016). Multi-criteria decision support system for wind farm site selection using GIS. Sustainable Energy Technologies and Assessments, 13, 38-50. https://doi.org/10.1016/j.seta.2015.11.007
  • Öztürk, M., Kayabaşı, R., & Taşdemir, O. (2025). Kırşehir’in Rüzgar Enerjisi Potansiyeli ve İç Anadolu Bölgesi Kurulu Rüzgar Enerjisi Santrallerinin Güç Analizi. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 28(1), 189-201. https://doi.org/10.17780/ksujes.1533576
  • Pamučar, D., Gigović, L., Bajić, Z., & Janošević, M. (2017). Location Selection for Wind Farms Using GIS Multi-Criteria Hybrid Model: An Approach Based on Fuzzy and Rough Numbers. Sustainability, 9(8). https://doi.org/10.3390/su9081315
  • Price, J., Warren, R., & Forstenhäusler, N. (2024). Biodiversity losses associated with global warming of 1.5 to 4 °C above pre-industrial levels in six countries. Climatic Change, 177(3). https://doi.org/10.1007/s10584-023-03666-2
  • Rediske, G., Burin, H. P., Rigo, P. D., Rosa, C. B., Michels, L., & Siluk, J. C. M. (2021). Wind power plant site selection: A systematic review. Renewable and Sustainable Energy Reviews, 148. https://doi.org/10.1016/j.rser.2021.111293
  • Rekik, S., Khabbouchi, I., & El Alimi, S. (2025). A Spatial Analysis for Optimal Wind Site Selection from a Sustainable Supply-Chain-Management Perspective. Sustainability, 17(4). https://doi.org/10.3390/su17041571
  • Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234-281. https://doi.org/10.1016/0022-2496(77)90033-5
  • Saaty, T. L. (1980). The analytic hierarchy process (AHP). The Journal of the Operational Research Society, 41(11), 1073-1076.
  • Sachit, M. S., Shafri, H. Z. M., Abdullah, A. F., Rafie, A. S. M., & Gibril, M. B. A. (2024). A novel GeoAI-based multidisciplinary model for SpatioTemporal Decision-Making of utility-scale wind–solar installations: To promote green infrastructure in Iraq. The Egyptian Journal of Remote Sensing and Space Sciences, 27(1), 120-136. https://doi.org/10.1016/j.ejrs.2024.02.001
  • Shobande, O. A., Ogbeifun, L., & Tiwari, A. K. (2025). Net-zero transitions: Advancing dynamic econometric analysis of carbon tax, renewable energy, and circular economy on government actions. J Environ Manage, 378, 124761. https://doi.org/10.1016/j.jenvman.2025.124761
  • Tegou, L. I., Polatidis, H., & Haralambopoulos, D. A. (2010). Environmental management framework for wind farm siting: methodology and case study. J Environ Manage, 91(11), 2134-2147. https://doi.org/10.1016/j.jenvman.2010.05.010
  • Tekdamar, D. A., & Tekdamar, K. (2024). Coğrafi Bilgi Sistemleri Tabanlı Analitik Hiyerarşi Yöntemi Kullanılarak Güneş Enerjisi Santrali Yer Seçimi: Mardin İli Örneği. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 27(1), 199-212. https://doi.org/10.17780/ksujes.1371448
  • 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. https://doi.org/10.1016/j.seta.2021.101491
  • TETKB. (2022). T.C. Enerji ve Tabi Kaynaklar Bakanlığı, Türkiye ulusal enerji planı. https://enerji.gov.tr/Media/Dizin/EIGM/tr/Raporlar/TUEP/T%C3%BCrkiye_Ulusal_Enerji_Plan%C4%B1.pdf
  • Toprak, A., & Sunkar, M. (2022). Ağrı İlinde Meydana Gelen Doğal Afetlerin Mekânsal ve Zamansal Analizi. Coğrafya Dergisi / Journal of Geography, 0(44), 97-113. https://doi.org/10.26650/jgeog2022-978387
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  • TWES. (2024). Turkish Wind Energy Statistics Report. T. W. E. Association. https://www.tureb.com.tr/eng/lib/uploads/3201020b27d9b8e8.pdf
  • Wang, J., & Azam, W. (2024). Natural resource scarcity, fossil fuel energy consumption, and total greenhouse gas emissions in top emitting countries. Geoscience Frontiers, 15(2). https://doi.org/10.1016/j.gsf.2023.101757
  • Yaman, A. (2024). A GIS-based multi-criteria decision-making approach (GIS-MCDM) for determination of the most appropriate site selection of onshore wind farm in Adana, Turkey. Clean Technologies and Environmental Policy, 26(12), 4231-4254. https://doi.org/10.1007/s10098-024-02866-3
  • Yamaçlı, V. (2025). Rüzgâr Gücü Tahmininde Uzun Kısa-Süreli Bellek: Veri Örnekleme ve Kümelemenin Etkisi. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 28(1), 202-215. https://doi.org/10.17780/ksujes.1535461
  • Yildiz, S. S. (2024). Spatial multi-criteria decision making approach for wind farm site selection: A case study in Balıkesir, Turkey. Renewable and Sustainable Energy Reviews, 192. https://doi.org/10.1016/j.rser.2023.114158
  • Yılmaz, E. A., & Can Öziç, H. (2018). Türkiye’nin Yenilenebilir Enerji Potansiyeli ve Gelecek Hedefleri. Ordu Üniversitesi Sosyal Bilimler Araştırmaları Dergisi, 8(3), 525-535.
  • Yousefi, H., Moradi, S., Zahedi, R., & Ranjbar, Z. (2024). Developed analytic hierarchy process and multi criteria decision support system for wind farm site selection using GIS: A regional-scale application with environmental responsibility. Energy Conversion and Management: X, 22. https://doi.org/10.1016/j.ecmx.2024.100594
  • Yousefi, H., Motlagh, S. G., & Montazeri, M. (2022). Multi-Criteria Decision-Making System for Wind Farm Site-Selection Using Geographic Information System (GIS): Case Study of Semnan Province, Iran. Sustainability, 14(13). https://doi.org/10.3390/su14137640
  • Zalhaf, A. S., Elboshy, B., Kotb, K. M., Han, Y., Almaliki, A. H., Aly, R. M. H., & 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). https://doi.org/10.3390/su14010358
Toplam 64 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Elektrik Enerjisi Üretimi (Yenilenebilir Kaynaklar Dahil, Fotovoltaikler Hariç), Rüzgar, Çok Ölçütlü Karar Verme
Bölüm Araştırma Makalesi
Yazarlar

Çağrı Mercan 0000-0003-1694-0024

Gönderilme Tarihi 16 Mart 2025
Kabul Tarihi 23 Aralık 2025
Yayımlanma Tarihi 3 Mart 2026
DOI https://doi.org/10.17780/ksujes.1658900
IZ https://izlik.org/JA76XH53MZ
Yayımlandığı Sayı Yıl 2026 Cilt: 29 Sayı: 1

Kaynak Göster

APA Mercan, Ç. (2026). RÜZGÂR ENERJİSİ SANTRALİ PLANLAMASINDA CBS VE AHP KULLANIMI: AĞRI İLİ ÜZERİNE BİR DEĞERLENDİRME. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 29(1), 13-34. https://doi.org/10.17780/ksujes.1658900