A BWM-GIS Based Approach for Wind Power Plant (WPP) Site Selection: Sample of Tunceli

Year 2023, Issue: 47, 15 - 28, 10.01.2024

Zekeriya Konurhan , Erkin Başaran

https://doi.org/10.26650/JGEOG2023-1233104

Abstract

In today’s world, searching for an alternative energy source instead of fossil fuels has become highly popular. Renewable energy sources such as solar panels and wind power plants are the alternatives to fossil fuels. Wind power plants (WPPs) are actively used in several regions of the world, both at sea and on land. In Turkey, WPPs have been used, especially since the early 2000s, with the Aegean and Marmara regions being their prime locations. However, there is no WPP in Tunceli. Thus, the main objective of this study is to recommend suitable WPP areas for Tunceli. In this context, the best-worst method (BWM) was integrated into the geographical information system (GIS) and used in the study. The BWM method is a multi-criteria decision making (MCDM) method based on pairwise comparison. In the study, 16 criteria were determined under four main criteria “topography”, “socio-economic”, “technical,” and “location” by using the BWM model. Experts from different disciplines evaluated each criterion as a questionnaire and used it for appropriate site selection. For the 16 criteria, separate maps were created, explanations of the criteria were established, and these maps were cumulatively used in the resulting map. The criteria weights determined using the BWM model were integrated into the GIS, and suitable WPP installation areas for Tunceli were determined. Accordingly, some areas around Pertek and Mazgirt in the southeast of Tunceli, north of Pülümür, and around Çemişgezek, which provide suitable conditions in terms of physical geography, are suitable for WPP installation.

Keywords

WPP, Best-Worst Method, Appropriate Site Selection with GIS, Tunceli

Project Number

YOK

Rüzgâr Enerji Santrali (RES) Yer Seçimi için BWM-CBS Tabanlı Bir Yaklaşım: Tunceli Örneği

Abstract

Günümüz dünyasında fosil yakıtların yerine alternatif bir enerji kaynak arayışı oldukça popüler bir yaklaşımdır. Güneş panelleri ve rüzgâr enerjisi santralleri gibi yenilenebilir enerji kaynakları fosil yakıtların alternatifleri arasındadır. Rüzgâr enerjisi santralleri hem denizde hem de karada olmak üzere dünyanın birçok bölgesinde aktif olarak kullanılmaktadır. Türkiye’de de RES’ler özellikle 2000’lerin başından itibaren kullanılmaya başlamıştır. Türkiye’deki RES’ler daha çok Ege ve Marmara Bölgesinde yer almaktadır. Çalışma alanı olan Tunceli’de ise herhangi bir RES bulunmamaktadır. Bu çalışmanın temel amacı Tunceli için uygun RES alanlarını önermektir. Bu kapsamda Best-Worst yöntemi (BWM) CBS’ye entegre edilerek kullanılmıştır. BWM yöntemi ikili karşılaştırmaya dayanan Çok Kriterli Karar Verme (ÇKKV) yöntemidir. Çalışmada BWM modeli kullanılarak “topografya”, “sosyo-ekonomik”, “teknik” ve “lokasyon” olmak üzere dört ana kriter altında 16 kriter belirlenmiştir. Her bir kriter farklı disiplinlerden uzmanlar tarafından anket olarak değerlendirilmiş ve uygun yer seçimi için kullanılmıştır. 16 kriter için ayrı ayrı haritalar oluşturulmuş, kriterlerin açıklamaları yapılmış ve bu haritalar sonuç haritasında kullanılmıştır. BWM modeli kullanılarak tespit edilen kriter ağırlıkları CBS’ye entegre edilerek Tunceli için uygun RES kurulum alanları belirlenmiştir. Buna göre, Tunceli’nin güneydoğusunda yer alan Pertek ve Mazgirt çevresi ile Pülümür’ün kuzeyi ve Çemişgezek’in çevresinde fiziki coğrafya açısından uygun şartları sağlayan bazı alanlar RES kurulumuna elverişlidir.

Keywords

RES, Best-Worst Metot, CBS ile Uygun Yer Seçimi, Tunceli

Supporting Institution

YOK

Project Number

YOK

Thanks

-

References

• Akova, İ. (2003). Dünya enerji sorunu ve yenilenebilir enerji kaynaklarının kullanımı. Coğrafya Dergisi, 0(11), 47-73. https:// dergipark.org.tr/tr/pub/iucografya/issue/25060/264568. google scholar
• Ali S, Taweekun J, Techato K, Waewsak J, Gyawali S. (2019). GIS based site suitability assessment for wind and solar farms in Songkhla, Thailand. Renewable Energy, 132, 1360-72. https://doi. org/10.1016/j.renene.2018.09.035 google scholar
• Anwarzai M. A. ve Nagasaka, K. (2017). Utility-scale implementable potential of wind and solar energies for Afghanistan using GIS multi-criteria decision analysis, Renewable and Sustainable Energy Reviews, 71, 150-160. https://doi.org/10.1016/j.rser.2016.12.048. google scholar
• Arslan, E. ve Solak, A. (2019). Türkiye’de yenilenebilir enerji tüketiminin ithalat üzerindeki etkisi. OPUS International Journal of Society Researches, 10(17), 1380-1407. https://doi.org/10.26466/ opus.521269 google scholar
• Aydin N. Y, Kentel E. ve Düzgün S. (2010). GIS-based environmental assessment of wind energy systems for spatial planning: a case study from Western Turkey. Renewable and Sustainable Energy Reviews, 14(1), 364-73. https://doi.org/10.1016/j.rser.2009.07.023 google scholar
• Baban, S. ve Parry, T. (2001). Developing and applying a GIS-assisted approach to locating wind farms in the UK. Renewable Energy 24, 59-71. google scholar
• Baseer M. A., Rehman S., Meyer J.P. ve Alam MM. (2017). GIS-based site suitability analysis for wind farm development in Saudi Arabia. Energy-141, 1166-76. https://doi.org/10.1016/j.energy.2017.10.016 google scholar
• Bennui, A., Rattanamanee, P., Puetpaiboon, U., Phukpattaranont, P. ve Chetpattananondh, K. (2007). Site selection for large wind turbine using GIS. In: Proceedings of the PSU-UNS International Conference on Engineering and Environment e ICEE, Phuket. google scholar
• Effat, H. A. ve El-Zeiny A. M. (2022). Geospatial modeling for selection of optimum sites for hybrid solar-wind energy in Assiut Governorate, Egypt. The Egyptian Journal of Remote Sensing and Space Science, 25(2), 627-637. https://doi.org/10.1016/j.ejrs.2022.03.005. google scholar
• Erinç, S. (1953). Doğu Anadolu coğrafyası. İstanbul: İstanbul Üniversitesi Coğrafya Enstitüsü Yayınları. google scholar
• Esen, F. ve Avcı, V. (2017). Tunceli ilinde topografik faktörlere göre yerleşmelerin ve nüfusun dağılışı. Uluslararası Sosyal Araştırmalar Dergisi, 10, 376-389. google scholar
• Gielen, D., Boshell, F., Saygin, D., Bazilian, M. D., Wagner, N., & Gorini, R. (2019). The role of renewable energy in the global energy transformation. Energy Strategy Reviews, 24, 38-50. https://doi. org/10.1016/j.esr.2019.01.006 google scholar
• Gorsevski P. V, Cathcart S., C, Mirzaei G., Jamali M., M., Ye X ve Gomez delcampo E., A. (2013). Group-based spatial decision support system for wind farm site selection in northwest Ohio. Energy Policy, 55, 374-85. google scholar
• Gul, M., & Ak, M. F. (2020). Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA. Stochastic Environmental Research and Risk Assessment, 34(8), 1231-1262. https://doi.org/10.1007/s00477-020-01816-x. google scholar
• Gültekin, U. (2019). Türkiye’de rüzgâr enerjisi yatırımlarının gelişimi. Electronic Turkish Studies, 14(4). google scholar
• Höfer, T., Sunak, Y., Siddique, H. and Madlener, R. (2016) Wind farm siting using a spatial analytic hierarchy process approach: a case study of the Stadteregion Aachen. Appl Energy, 163, 222-43. google scholar
• J. Jangid, A.K. Bera, M. Joseph, V. Singh, T.P. ve Singh, B.K. (2016). Potential zones identification for harvesting wind energy resources in desert region of India e a multi criteria evaluation approach using remote sensing and GIS. Renew. Sustain. Energy Rev. 65, 1-10. https://doi.org/10.1016/j.rser.2016.06.078. google scholar
• Kiziroglu, I. ve Erdogan, A. (2015). Relations between ecosystem and wind energy. Fresenius Environ. Bull. 24, 163-171. google scholar
• Langer L., Zaaijer M, Quist J. ve Blok K. (2023). Introducing site selection flexibility to technical and economic onshore wind potential assessments: New method with application to Indonesia, Renewable Energy, 202, 320-335. https://doi.org/10.1016/j.renene.2022.11.084. google scholar
• Uyan, M. (2013). GIS-based solar farms site selection using analytic hierarchy process (AHP) in Karapinar region, Konya/Turkey. Renewable and Sustainable Energy Reviews, 28, 11-17. google scholar
• Manish, S., Pillai, I. R., & Banerjee, R. (2006). Sustainability analysis of renewables for climate change mitigation. Energy for Sustainable Development, 10(4), 25-36. google scholar
• Messaoudi D., Settou N., Negrou B. ve Settou B. (2019). GIS based multi-criteria decision making for solar hydrogen production sites selection in Algeria. International Journal of Hydrogen Energy, 44(60), 31808-31. https://doi.org/10.1016/j.ijhydene.2019.10.099. google scholar
• MGM, 2022: https://www.mgm.gov.tr/ (Erişim Tarihi 31.12.2022). google scholar
• Morris, C., & Jungjohann, A. (2017). Energizing the people. Nature, 551(7682), S138-S140. google scholar
• Nedaei, M., Assareh, E., and Biglari, M. (2014). An extensive evaluation of wind resource using new methods and strategies for development and utilizing wind power in Mahshahr station in Iran. Energy ConversManag, 81, 475-503. google scholar
• Noorollahi Y, Yousefi H. ve Mohammadi M. (2016). Multi-criteria decision support system for wind farm site selection using GIS. Sustain Energy Tecchn, 13, 38-50. google scholar
• Omer, A. M. (2008). Energy, environment and sustainable development. Renewable and Sustainable Energy Reviews, 12(9), 2265-2300. google scholar
• Özşahin, E. ve Kaymaz, Ç. (2014). Rüzgâr enerji santrallerinin (RES) kuruluş yeri seçiminin CBS ile analizi: Hatay örneği. TÜBAV Bilim Dergisi, 6 (2), 1-18. https://dergipark.org.tr/tr/pub/tubav/issue/21531/230992. google scholar
• Pınar, A., Buldur, A., ve Tuncer, T. (2020). Türkiye’deki rüzgâr enerji santralleri dağılışının coğrafi perspektiften analizi. Doğu Coğrafya Dergisi, 25(43), 167-182. google scholar
• Quaschning, V. (2005). Understanding Renewable Energy Systems: Earthscan. Renewable energy, 3, 224-228. google scholar
• Renn, O., & Marshall, J. P. (2016). Coal, nuclear and renewable energy policies in Germany: From the 1950s to the “Energiewende”. Energy Policy, 99, 224-232. google scholar
• Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. google scholar
• Rezaei, J. (2016). Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 64, 126-130. google scholar
• Rezaei, J. (2020). A concentration ratio for nonlinear best worst method. International Journal of Information Technology & Decision Making, 19(3), 891-907. google scholar
• Rezaei, J., Nispeling, T., Sarkis, J., & Tavasszy, L. (2016). A supplier selection life cy-cle approach integrating traditional and environmental criteria using the best worst method. Journal of CleanerProduction, 135, 577-588. google scholar
• Saraçoğlu, H. (1956). Türkiye coğrafyası üzerine etüdler-I, Doğu Anadolu, İstanbul: Maarif Basımevi. google scholar
• SETA. (2017). Dünyada ve Türkiye’de Yenilenebilir Enerji, Sayı 197. İstanbul google scholar
• Shorabeh S.N., Firozjaei, H.K. Firozjaei M.K., Jelokhani-Niaraki, M., Homaee M. ve Nematollahi O. (2022). The site selection of wind energy power plant using GIS-multi-criteria evaluation from economic perspectives, Renewable and Sustainable Energy Reviews, 168. 112778. https://doi.org/10.1016/j.rser.2022.112778. google scholar
• Siyal, S.H., Mörtberg, U., Mentis, D., Welsch, M., Babelon, I. and Howells, M. (2015). Wind energy assessment considering geographic and environmental restrictions in Sweden: a GIS-based approach, Energy 83, 447-461, https://doi.org/10.1016/j.energy.2015.02.044. google scholar
• Tegou LI, Polatidis H. ve Haralambopoulos D.A. (2010). Environmental management framework for wind farm siting: methodology and case study. J EnvironManag-91. 2134-47. https://doi.org/10.1016/j. jenvman.2010.05.010. google scholar
• Tercan, E. (2021). Land suitability assessment for wind farms through best-worst method and GIS in Balıkesir province of Turkey. Sustainable Energy Technologies andAssessments, 47, 101491. google scholar
• Tercan, E., Eymen A., Urfalı T. ve Saracoglu O. B. (2021). A sustainable framework for spatial planning of photovoltaic solar farms using GIS and multi-criteria assessment approach in Central Anatolia, Turkey. Land Use Policy 102. 105272. https://doi.org/10.1016/j. landusepol.2020.105272. google scholar
• TUREB (2022). https://www.tureb.com.tr/ (Erişim Tarihi 31.12.2022). google scholar
• URL-1: http://www.ndrc.gov.cn/zcfb/zcfbghwb/201701/ W0201701173 50627940556.pdf. (Erişim Tarihi 31.12.2022). google scholar
• USGS (2022). https://earthexplorer.usgs.gov/ (Erişim Tarihi 31.12.2022). google scholar
• Van Haaren R. ve Fthenakis V. (2011). GIS-based wind farm site selection using spatial multi-criteria analysis (SMCA): Evaluating the case for New York State. Renewable and Sustainable Energy Reviews-15, 3332-40. google scholar
• Ye Xu, Ye Li, Lijun Zheng, Liang Cui, Sha Li, Wei Li ve Yanpeng Cai (2020). Site selection of wind farms using GIS and multi-criteria decision making method in Wafangdian, China, Energy, 207, 118222. https://doi.org/10.1016/j.energy.2020.118222. google scholar
• Yılmaz, E. A., & Öziç, H. C. (2018). Renewable energy potential and future aims of Turkey. Ordu University Journal of Social Science Research, 8(3), 525-535. google scholar
• Yılmaz, M. (2012). Türkiye’nin enerji potansiyeli ve yenilenebilir enerji kaynaklarının elektrik enerjisi üretimi açısından önemi. Ankara Üniversitesi Çevrebilimleri Dergisi, 4(2), 33-54.DOI:10.1501/Csaum 0000000064. google scholar