RÜZGAR TÜRBİNİ SAHA PLANLAMASI: TÜRKİYE’DEN BİR VAKA ANALİZİ

Abstract

Dünya nüfusunun artması ve ekonomik büyümeye bağlı olarak tüketim hızla artmıştır. Tüketimin artması enerji ihtiyacının da artmasına neden olmuştur. Bu durumun, daha fazla enerji üretimi ve daha verimli enerji kullanımı gibi çözümler ile yönetilebileceği düşünülmektedir. Ancak bu çözümlerin geliştirilmesinde, enerji sektörünün sürdürülebilirliği ve çevresel etkileri de göz önünde bulundurulmalıdır. Rüzgar enerjisinin kullanımı da bu doğrultuda tüm dünyada artmaktadır. Türkiye konumu itibariyle rüzgar enerjisi potansiyeli bakımından en uygun ülkeler arasındadır. Bu çalışmanın amacı, Türkiye'deki rüzgar santrallerinin mevcut durumunu incelemektir. Bu amaçla Türkiye’deki potansiyeli en yüksek illerden biri olan Tekirdağ ilinde kurulması planlanan rüzgar enerji santralinin lokasyonunun çok kriterli karar verme (MCDM) yaklaşımları ile belirlenmesi ele alınmıştır. Rüzgar santrali kurulumunda değerlendirilebilecek 10 faktör, literatür taraması ve uzmanlardan gelen geri dönüşlerle belirlenmiş, AHP yöntemiyle bu faktörlerin ağırlıkları hesaplanmıştır. Tekirdağ'da önceden belirlenmiş 10 farklı lokasyon hesaplanan ağırlıklar ve TOPSIS yöntemi yardımı ile rüzgar santrallerinin uygulanabilirliği açısından sıralanmıştır. Elde edilen sonuçta, Şarköy ilçesine 22 km uzaklıkta bulunan lokasyon en uygun nokta olarak tespit edilmiştir. Bu çalışmanın gelecekte yapılacak sürdürülebilir enerji değerlendirme çalışmalarına katkıda bulunması amaçlanmaktadır.

Keywords

• Sürdürülebilirlik
• MCDM
• Rüzgar Enerjisi
• AHP
• TOPSIS

STANDORTPLANUNG EINER WINDKRAFTANLAGE: EINE FALLANALYSE AUS DER TÜRKEI

Abstract

Der Konsum hat aufgrund des Anstiegs der Weltbevölkerung und des Wirtschaftswachstums rapide zugenommen. Der Anstieg des Verbrauchs hat zu einem Anstieg des Energiebedarfs geführt. Man geht davon aus, dass diese Situation durch Lösungen wie mehr Energieproduktion und effizientere Energienutzung bewältigt werden kann. Allerdings sollten bei der Entwicklung dieser Lösungen auch die Nachhaltigkeit und Umweltauswirkungen des Energiesektors berücksichtigt werden. In diese Richtung nimmt die Nutzung der Windenergie weltweit zu. Die Türkei gehört aufgrund seiner Lage zu den am besten geeigneten Ländern des Windenergiepotenzials. Ziel dieser Studie ist es, die aktuelle Situation von Windparks in der Türkei zu untersuchen. Zu diesem Zweck wird die Standortbestimmung der geplanten Windkraftanlage in Tekirdağ, einer der Provinzen mit dem höchsten Potenzial in der Türkei, mit multikriteriellen Entscheidungsunterstützungs (MCDM)-Ansätzen diskutiert. Die zehn Faktoren, die bei der Windparkinstallation bewertet werden können, wurden durch Literaturrecherche und Feedback von Experten ermittelt und die Gewichte dieser Faktoren mit der AHP berechnet. Mithilfe von Gewichten und TOPSIS werden zehn Standorte in Tekirdağ im Hinblick auf die Anwendbarkeit von Windparks aufgelistet. Infolgedessen wurde der Standort 22 km vom Bezirk Şarköy entfernt als am besten geeigneter Punkt ermittelt. Ziel ist es, dass die Studie in Zukunft zu Studien zur nachhaltigen Energiebewertung beitragen wird.

Keywords

• Nachhaltigkeit
• MCDM
• Windkraft
• AHP
• TOPSIS

References

1. Abdel-Basset, M., & Mohamed, R. (2020). A novel plithogenic TOPSIS-CRITIC model for sustainable supply chain risk management. Journal of Cleaner Production, 247, 119586.
2. Ali, S., Lee, S. M., & Jang, C. M. (2017). Determination of the most optimal on-shore wind farm site location using a GIS-MCDM methodology: Evaluating the case of south korea. Energies, 10(12), 2072.
3. Awasthi, S. R. (2018). Wind power: practical aspects. The Energy and Resources Institute (TERI).
4. Aydın, L., & Acar, M. (2011). Economic impact of oil price shocks on the Turkish economy in the coming decades: A dynamic CGE analysis. Energy Policy, 39(3), 1722-1731.
5. Beauson, J., Laurent, A., Rudolph, D. P., & Jensen, J. P. (2022). The complex end-of-life of wind turbine blades: A review of the European context. Renewable and Sustainable Energy Reviews, 155, 111847.
6. Benli, H. (2013). Potential of renewable energy in electrical energy production and sustainable energy development of Turkey: Performance and policies. Renewable Energy, 50, 33-46.
7. Bıçakçı, E., Balabanlı, C., & Emrah, A. (2023). Tarım ve Mera Alanlarında Rüzgâr ve Güneş Enerji Sistemleri Kurulması Hakkında Değerlendirmeler. Journal of the Institute of Science and Technology, 13(1), 700- 712.
8. Chang, C. W., Wu, C. R., Lin, C. T., & Chen, H. C. (2007). An application of AHP and sensitivity analysis for selecting the best slicing machine. Computers & Industrial Engineering, 52(2), 296-307.

9. Chaouachi, A., Covrig, C. F., & Ardelean, M. (2017). Multi-criteria selection of offshore wind farms: Case study for the Baltic States. Energy Policy, 103, 179-192.
10. Chodha, V., Dubey, R., Kumar, R., Singh, S., & Kaur, S. (2022). Selection of industrial arc welding robot with TOPSIS and Entropy MCDM techniques. Materials Today: Proceedings, 50, 709-715.
11. Cunden, T. S., Doorga, J., Lollchund, M. R., & Rughooputh, S. D. (2020). Multi-level constraints wind farms siting for a complex terrain in a tropical region using MCDM approach coupled with GIS. Energy, 211, 118533.
12. Çelik, İ., Yıldız, C., & Şekkeli, M. (2018). Rüzgâr Enerji Santrali kurulumunda rüzgâr türbinlerinin mikro yerleşimi için bir optimizasyon modeli. Gazi University Journal of Science Part C: Design and Technology, 6(4), 898-908.
13. Değirmenci, S., Bingöl, F., & Sofuoglu, S. C. (2018). MCDM analysis of wind energy in Turkey: decision making based on environmental impact. Environmental Science and Pollution Research, 25, 19753-19766.
14. Dincer, F. (2011). The analysis on wind energy electricity generation status, potential and policies in the world. Renewable and sustainable energy reviews, 15(9), 5135-5142.
15. Dwivedi, Y. K., Hughes, L., Kar, A. K., Baabdullah, A. M., Grover, P., Abbas, R., ... & Wade, M. (2022). Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action. International Journal of Information Management, 63, 102456.
16. Elhosiny, A. M., El-Ghareeb, H., Shabana, B. T., & AbouElfetouh, A. (2021). A hybrid neutrosophic gis-mcdm method using a weighted combination approach for selecting wind energy power plant locations: A case study of sinai peninsula, egypt. International Journal of Fuzzy Logic and Intelligent Systems, 21(1), 12-28.
17. Enerji Atlası (2023). Tekirdağ Rüzgar Santralleri. https://www.enerjiatlasi.com/ruzgar-enerjisi-haritasi/tekirdag Abgerufen am: 01.12.2023
18. 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.
19. Fetanat, A., & Khorasaninejad, E. (2015). A novel hybrid MCDM approach for offshore wind farm site selection: A case study of Iran. Ocean & Coastal Management, 109, 17-28.
20. Garetti, M., & Taisch, M. (2012). Sustainable manufacturing: trends and research challenges. Production planning & control, 23(2-3), 83-104.
21. Gaudenzi, B., & Borghesi, A. (2006). Managing risks in the supply chain using the AHP method. The International Journal of Logistics Management, 17(1), 114-136.
22. Genç, M. S., Karipoğlu, F., Koca, K., & Azgın, Ş. T. (2021). Suitable site selection for offshore wind farms in Turkey’s seas: GIS-MCDM based approach. Earth Science Informatics, 14(3), 1213-1225.
23. Guo, S. J., Chen, J. H., & Chiu, C. H. (2017). Fuzzy duration forecast model for wind turbine construction project subject to the impact of wind uncertainty. Automation in Construction, 81, 401-410.
24. Gupta, A. K. (2015). Efficient wind energy conversion: Evolution to modern design. Journal of Energy Resources Technology, 137(5), 051201.
25. Höfer, T., Sunak, Y., Siddique, H., & Madlener, R. (2016). Wind farm siting using a spatial Analytic Hierarchy Process approach: A case study of the Städteregion Aachen. Applied energy, 163, 222-243.
26. Hwang, C. L., Yoon, K., Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. Multiple Attribute Decision Making: Methods and Applications A State-of-the-art Survey, 58-191.
27. International Energy Agency (IEA). (2021). Turkey 2021 – Energy Policy Review. https://www.iea.org/reports/turkey-2021 Abgerufen am: 06.11.2023
28. Ilić, B., Stojanovic, D., & Djukic, G. (2019). Green economy: mobilization of international capital for financing projects of renewable energy sources. Green Finance, 1(2), 94-109.
29. Jiang, Z. (2021). Installation of offshore wind turbines: A technical review. Renewable and Sustainable Energy Reviews, 139, 110576.
30. Koç, T. (1998). Ayvalık‘ta Rüzgar Enerjisi Potansiyeli. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 1(2), 1-18.
31. Koç, E., & Burhan, H. A. (2015). An application of analytic hierarchy process (AHP) in a real world problem of store location selection. Advances in Management and Applied Economics, 5(1), 41.
32. Meshram, S. G., Alvandi, E., Meshram, C., Kahya, E., & Fadhil Al-Quraishi, A. M. (2020). Application of SAW and TOPSIS in prioritizing watersheds. Water Resources Management, 34, 715-732.
33. Mikhaylov, A., Moiseev, N., Aleshin, K., & Burkhardt, T. (2020). Global climate change and greenhouse effect.
34. Entrepreneurship and Sustainability Issues, 7(4), 2897. Ministerium für Energie und natürliche Ressourcen (MENR). (2023a). Elektrik. https://enerji.gov.tr/bilgimerkezi-enerji-elektrik Abgerufen am: 01.12.2023
35. Ministerium für Energie und natürliche Ressourcen (MENR). (2023b). Rüzgar. https://enerji.gov.tr/eigmyenilenebilir- enerji-kaynaklar-ruzgar Abgerufen am: 01.12.2023
36. Nazim, M., Mohammad, C. W., & Sadiq, M. (2022). A comparison between fuzzy AHP and fuzzy TOPSIS methods to software requirements selection. Alexandria Engineering Journal, 61(12), 10851-10870.
37. Özkan, A., Yeter, U., & Gedikli, E. (2022). Türkiye’nin yenilenebilir enerji potansiyelinde rüzgâr gücü ve Danimarka örneği. Akdeniz İİBF Dergisi, 22(2), 26-35.
38. Ritschel, U., Warnke, I., Kirchner, J., & Meussen, B. (2003, November). Wind turbines and earthquakes. In 2nd World Wind Energy Conference (pp. 1-8). Cape Town,, South Africa: World Wind Energy Association.
39. Saaty, R. W. (1987). The analytic hierarchy process—what it is and how it is used. Mathematical Modelling, 9(3–5), 161–176.
40. Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European journal of operational research, 48(1), 9-26.
41. Saraswat, S. K., Digalwar, A. K., Yadav, S. S., & Kumar, G. (2021). MCDM and GIS based modelling technique for assessment of solar and wind farm locations in India. Renewable Energy, 169, 865-884.
42. Sonar, H. C., & Kulkarni, S. D. (2021). An integrated AHP-MABAC approach for electric vehicle selection. Research in Transportation Business & Management, 41, 100665.
43. Tripathi, L., Mishra, A. K., Dubey, A. K., Tripathi, C. B., & Baredar, P. (2016). Renewable energy: An overview on its contribution in current energy scenario of India. Renewable and Sustainable Energy Reviews, 60, 226-233.
44. Türkiye Rüzgar Enerjisi Birliği (TÜREB). (2023). Rakamlarla Rüzgar Enerjisi. https://www.tureb.com.tr/
45. Urfali, T., & Eymen, A. (2021). CBS ve AHP yöntemi yardımıyla Kayseri İli Örneğinde rüzgâr enerji santrallerinin yer seçimi. Geomatik, 6(3), 227-237.
46. Villacreses, G., Gaona, G., Martínez-Gómez, J., & Jijón, D. J. (2017). Wind farms suitability location usinggeographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador. Renewable energy, 109, 275-286.
47. Villacreses, G., Jijón, D., Nicolalde, J. F., Martínez-Gómez, J., & Betancourt, F. (2022). Multicriteria Decision Analysis of Suitable Location for Wind and Photovoltaic Power Plants on the Galápagos Islands. Energies, 16(1), 29.
48. Wątróbski, J., Bączkiewicz, A., Ziemba, E., & Sałabun, W. (2022). Sustainable cities and communities assessment using the DARIA-TOPSIS method. Sustainable Cities and Society, 83, 103926.
49. Wang, F., Harindintwali, J. D., Yuan, Z., Wang, M., Wang, F., Li, S., ... & Chen, J. M. (2021). Technologies and perspectives for achieving carbon neutrality. The Innovation, 2(4).
50. Wiatros-Motyka, M. (2023). Global Electricity Review 2023. https://ember-climate.org/insights/research/globalelectricity-review-2023/ Abgerufen am: 05.12.2023
51. Yıldırım, U., Gazibey, Y., & Güngör, A. (2016). Niğde ili rüzgar enerjisi potansiyeli. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 1(1), 37-47.
52. Zaidan, A. A., Zaidan, B. B., Al-Haiqi, A., Kiah, M. L. M., Hussain, M., & Abdulnabi, M. (2015). Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS. Journal of biomedical informatics, 53, 390-404.
53. Zhang, D., Xu, Z., Li, C., Yang, R., Shahidehpour, M., Wu, Q., & Yan, M. (2019). Economic and sustainability promises of wind energy considering the impacts of climate change and vulnerabilities to extreme conditions. The Electricity Journal, 32(6), 7-12.