Alternatives to Solar Power Plant Location Through GIS and AHP: Case of Karaman, Turkey

Year 2020, Volume: 13 Issue: 4, 651 - 667, 31.12.2020

Tayfun Salihoğlu , Eren Can Seyrek , Melike Kaymakçıoğlu

https://doi.org/10.35674/kent.746845

Abstract

In meeting today's increasing energy needs, the use of renewable energy sources becomes widespread comparing with the thermal and nuclear power plants, which cause great harm to nature. While hydroelectric power plants are most common among renewable energy plants in Turkey, national policies towards increasing wind power plants and solar power plants are gaining momentum.
Due to its geographical location, Turkey is more advantageous position compared to many other countries in terms of solar energy potential. The region receiving the most solar energy in Turkey is Southeastern Anatolia, followed by the Mediterranean and Eastern Anatolia. It is seen that the solar energy potentials of Antalya, Karaman, Mersin and Van provinces are higher than other provinces of Turkey.
With the help of a well-known Turkey map on the solar potential of cities, it is possible to determine the advantageous cities which solar power plants (SPP) can be placed. However, there is a need for a multi-criteria decision-making method regarding where position solar power plants in these cities.
With this work; according to the solar radiation values of Turkey, it is aimed to determine the alternatives for the most suitable SPP locations in Karaman Province, which has an important potential for the establishment of a solar power plant. Appropriate locations were determined by a multi-criteria and geographic information systems (GIS) supported method. Eleven criteria with data for the city of Karaman have been identified among the criteria mentioned in the related literature. The scores obtained from these criteria (in grids of 100x100 meters) are classified into five categories. The weighted scores were then standardized to a range of 1-5 with tools to reclassify in GIS environment. Reclassified weighted criteria were overlapped with Weighted Overlay Analysis to determine the most suitable regions for SPP investment.

Keywords

Solar Power Plant, Geographical Information Systems, Overlay Analysis, Multi Criteria Decision Making

AHP ve CBS Yardımıyla Kentlerde Güneş Enerji Santrali Yer Seçimi Alternatifleri: Karaman Türkiye Örneği

Abstract

GGünümüzde enerji ihtiyacının karşılanmasında doğaya zararlı etkilerde bulunan termal ve nükleer kaynaklara kıyasla yenilenebilir enerji kaynakları giderek yaygınlaşmaktadır. Hidroelektrik santraller Türkiye'deki yenilenebilir enerji santralleri arasında en yaygını olmakla birlikte, rüzgar santralleri ve güneş enerjisi santrallerinin artırılmasına yönelik ulusal politikaların da ivme kazandığı görülmektedir.
Coğrafi konumu nedeniyle Türkiye, güneş enerjisi potansiyeli açısından diğer birçok ülkeye göre daha avantajlı bir konuma sahiptir. Türkiye'de en fazla güneş enerjisi alan bölge Güneydoğu Anadolu, ardından Akdeniz ve Doğu Anadolu'dur. Antalya, Karaman, Mersin ve Van illerinin güneş enerjisi potansiyellerinin Türkiye'nin diğer illerinden daha yüksek olduğu görülmektedir.
Şehirlerin güneş enerjisi potansiyeline ilişkin Türkiye haritası yardımıyla, güneş enerjisi santrallerinin (GES) yer seçimi açısından avantajlı şehirleri belirlemek mümkündür. Bununla birlikte, bir şehir içerisinde güneş enerjisi santrallerinin nerede konumlandırılabileceğine ilişkin çok kriterli karar verme yöntemine ihtiyaç vardır.
Bu çalışma ile; ülkemizin güneş radyasyonu değerlerine göre bir güneş enerjisi santrali kurulması için önemli bir potansiyele sahip olan Karaman ilindeki en uygun GES yerlerine ilişkin alternatiflerin belirlenmesi hedeflenmektedir. Uygun yerler çok kriterli ve coğrafi bilgi sistemleri destekli yöntemle belirlenmiştir. İlgili literatürde bahsedilen kriterler arasında Karaman kenti için elde edilebilen verilere bağlı olarak on bir kriter belirlenmiştir. Bu kriterlerden elde edilen puanlar düşükten yükseğe doğru beş kategoride sınıflandırılmış, yeniden sınıflandırılan ağırlıklandırılmış kriterlere Ağırlıklı Bindirme Analizi uygulanarak GES yatırımı için en uygun bölgeler belirlenmiştir.

Keywords

Güneş Enerji Santrali, Coğrafi Bilgi Sistemleri, Bindirme Analizi, Çok Ölçütlü Karar Verme

References

• Akad, M., & Gedizlioğlu, E. (2007). Toplu Taşıma Türü Seçiminde Simülasyon Destekli Analitik Hiyerarşi Yaklaşımı, İTÜ Dergisi.
• Akkas, O. P., Erten, M. Y., Cam, E., & Inanc, N. (2017). Optimal Site Selection for a Solar Power Plant in the Central Anatolian Region of Turkey. International Journal of Photoenergy, 2017.
• Asakereh, A., Omid, M., Alimardani, R., & Sarmadian, F. (2014). Developing A GIS-Based Fuzzy AHP Model for Selecting Solar Energy Sites in Shodirwan Region in Iran. International Journal of Advanced Science and Technology, 68, 37-48.
• Atak, A., Çabuk, S. N., Bakış, R., & Çabuk, A. (2019). Determination of Suitable Sites for Solar Power Plants by Using Weighted Overlay Analysis: Sivrihisar Case.
• Ayday. C., Yaman. N., Sabah. L., & Höke. O. (2016). Güneş Enerji Santrali Yer Seçiminde Açık Kaynak Kodlu CBS Kullanımı-Eskişehir Il Örneği, 6. Uzaktan Algılama-CBS Sempozyumu (UZAL-CBS2016), S:510-520, 5-7 Ekim 2016, Adana.
• Aydin, N. Y. (2009). GIS-Based Site Selection Approach for Wind and Solar Energy Systems: A Case Study from Western Turkey (MS Thesis). Middle East Technical University, Ankara.
• Aydin, N. Y., Kentel, E., & Duzgun, H. S. (2013). GIS-Based Site Selection Methodology For Hybrid Renewable Energy Systems: A Case Study From Western Turkey. Energy Conversion And Management, 70, 90-106.
• Brunner, I. M., Kim, K., & Yamashita, E. (2011). Analytic Hierarchy Process and Geographic Information Systems to Identify Optimal Transit Alignments. Transportation Research Record, 2215(1), 59-66.
• Chandio, I. A., Abd Nasir, B. M., WanYusof, K. B., Talpur, M. A. H., Balogun, A. L., & Lawal, D. U. (2013). GIS-Based Analytic Hierarchy Process as a Multicriteria Decision Analysis İnstrument: A Review. Arabian Journal Of Geosciences, 6(8), 3059-3066.
• Çanka Kılıç, F. (2015). Güneş Enerjisi, Türkiye’deki Son Durumu ve Üretim Teknolojileri. Mühendis ve Makina, 56(671), 28-40.
• Ellabban, O., Abu-Rub, H., & Blaabjerg, F. (2014). Renewable Energy Resources: Current Status, Future Prospects and Their Enabling Technology. Renewable and Sustainable Energy Reviews, 39, 748-764.
• ElQuoliti, S. A. H. (2015). An Analytic Hierarchy Process to Evaluate Candidate Locations for Solar Energy Stations: Kingdom of Saudi Arabia as a Case Study. International Journal On Power Engineering And Energy (IJPEE), 6(3).
• Eroglu, H. (2018). Güneş Enerji Santralleri İçin Uygunluk Haritasının Elde Edilmesi: Bir Uygulama. Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 8(4), 97-106.
• Gasparovic, I., & Gasparovic, M. (2019). Determining Optimal Solar Power Plant Locations Based on Remote Sensing and GIS Methods: A Case Study from Croatia. Remote Sensing, 11, 1481, 1-18.
• Georgiou, A., & Skarlatos, D. (2016). Optimal Site Selection for Sitting a Solar Park Using Multi-Criteria Decision Analysis and Geographical Information Systems. Geoscientific Instrumentation, Methods and Data Systems, 5(2), 321-332.
• Guaita-Pradas, I., Marques-Perez, I., Gallego, A., & Segura, B. (2019). Analyzing Territory for the Sustainable Development of Solar Photovoltaic Power Using GIS Databases. Environmental Monitoring And Assessment, 191(12), 764.
• Güçlüer, D. (2010). Güneş Enerjisi Santrali Kurulacak Alanların CBS-Çok Ölçütlü Karar Analizi Yöntemi ile Belirlenmesi.Yüksek LisansTezi, Yıldız Teknik Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
• Kum, G., Sönmez, M. E., & Karabaş, M. (2019). Gaziantep İlinde Güneş Enerjisi Potansiyelinin Analitik Hiyerarşi Süreci Yöntemi (AHP) ile Belirlenmesi. Coğrafya Dergisi, 1-1.
• Harjanne, A., & Korhonen, J. M. (2019). Abandoning the Concept of Renewable Energy. Energy policy, 127, 330-340.
• Ho, D., Newell, G. And Walker, A. (2005). The Importance of Property-Specific Attributes in Assessing CBD Office Building Quality. Journal of Property Investment & Finance, 23(5), 424-444.
• Kaya, T., & Kahraman, C. (2010). Multicriteria Renewable Energy Planning Using An Integrated Fuzzy VIKOR & AHP Methodology: The Case Of Istanbul. Energy, 35(6), 2517-2527.
• Kengpol, A., Rontlaong, P., & Tuominen, M. (2012). Design of A Decision Support System For Site Selection Using Fuzzy AHP: A Case Study of Solar Power Plant in North Eastern Parts Of Thailand. In 2012 Proceedings Of PICMET'12: Technology Management For Emerging Technologies (Pp. 734-743). IEEE.
• Khemiri, W., Yaagoubi, R., & Miky, Y. (2018). Optimal Placement Of Solar Photovoltaic Farms Using Analytical Hierarchical Process and Geographic Information System in Mekkah, Saudi Arabia. In AIP Conference Proceedings (Vol. 2056, No. 1, P. 020025). AIP Publishing LLC.
• Kırlangıçoğlu, C. (2016). Çok Kriterli Karar Verme Yöntemleri ile Kent İçi Raylı Sistem Koridor Planlaması, Coğrafya Dergisi, (33), 53-71.
• 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. Environmental Science And Pollution Research, 26(31), 32298-32310.
• Koç, E., & Şenel, M. C. (2013). Dünyada ve Türkiye’de Enerji Durumu-Genel Değerlendirme. Mühendis ve Makina, 54(639), 32-44.
• Merrouni, A. A., Elalaoui, F. E., Ghennioui, A., Mezrhab, A., & Mezrhab, A. (2018). A GIS-AHP Combination For The Sites Assessment Of Large-Scale CSP Plants With Dry And Wet Cooling Systems. Case Study: Eastern Morocco. Solar Energy, 166, 3-6.
• Mokarram, M., Mokarram, M. J., Khosravi, M. R., Saber, A., & Rahideh, A. (2020). Determination of the Optimal Location for Constructing Solar Photovoltaic Farms Based on Multi-Criteria Decision System and Dempster–Shafer Theory. Scientific Reports, 10(1), 1-17.
• Ozdemir, S., & Sahin, G. (2018). Multi-Criteria Decision-Making in the Location Selection for a Solar PV Power Plant Using AHP. Measurement, 129, 218-226.
• Rumbayan, M., Nagasaka, K. (2012). Prioritization Decision for Renewable Energy Development Using Analytic Hierarchy Process and Geographic Information System. In The 2012 International Conference On Advanced Mechatronic Systems (Pp. 36-41). IEEE.
• Saaty, T. L. (1990). Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. RWS Publications.
• Saaty, T. L. (2013). The Modern Science of Multicriteria Decision Making and Its Practical Applications: The AHP/ANP Approach. Operations Research, 61(5), 1101-1118.
• Sánchez-Lozano, J. M., Antunes, C. H., García-Cascales, M. S., & Dias, L. C. (2014). GIS-Based Photovoltaic Solar Farms Site Selection Using ELECTRE-TRI: Evaluating The Case For Torre Pacheco, Murcia, Southeast Of Spain. Renewable Energy, 66, 478-494.
• Sozen, A., Mirzapour, A., & Çakir, M. T. (2015). Selection Of The Best Location For Solar Plants In Turkey. Journal Of Energy In Southern Africa, 26(4), 52-63.
• Tunc, A., Tuncay, G., Alacakanat, Z., & Sevimli, F. S. (2019). Gis Based Solar Power Plants Site Selection Using Analytic Hierarchy Process (Ahp) In Istanbul, Turkey. International Archives Of The Photogrammetry, Remote Sensing & Spatial Information Sciences.
• 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.
• Uyan, M. (2017). Optimal Site Selection For Solar Power Plants Using Multi-Criteria Evaluation: A Case Study From The Ayranci Region in Karaman, Turkey. Clean Technologies And Environmental Policy, 19(9), 2231-2244.
• Uyan, M. (2017). Güneş Enerjisi Santrali Kurulabilecek Alanların AHP Yöntemi Kullanılarak CBS Destekli Haritalanması. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 23(4), 344.
• Yalçın, C., Yüce, M. (2019). Burdur’da Güneş Enerjisi Santrali (GES) Yatırımına Uygun Alanların CBS Tabanlı AHP Yöntemiyle Tespiti. Geomatik, 5(1), 40-50.
• Wedley, W. C. (1993). Consistency Prediction For İncomplete AHP Matrices. Mathematical and Computer Modelling, 17(4-5), 151-161.
• Yushchenko, A., De Bono, A., Chatenoux, B., Patel, M. K., & Ray, N. (2018). GIS-Based Assessment of Photovoltaic (PV) and Concentrated Solar Power (CSP) Generation Potential in West Africa. Renewable and Sustainable Energy Reviews, 81, 2088-2103.
• Yousefi, H., Hafeznia, H., & Yousefi-Sahzabi, A. (2018). Spatial Site Selection for Solar Power Plants Using A GIS-Based Boolean-Fuzzy Logic Model: A Case Study of Markazi Province, Iran. Energies, 11(7), 1648.
• URL 1: http://www.yegm.gov.tr/genc_cocuk/Yenilenebilir_Enerji_Nedir.aspx/ URL 2: http://www.yegm.gov.tr/MyCalculator/iller/TR.png URL 3: https://enerji.gov.tr/bilgi-merkezi-enerji-gunes URL 4: http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/understanding-overlay-analysis.htm
• URL 5: http://www.resmigazete.gov.tr/ilanlar/eskiilanlar/2011/08/20110811-4.htm#%C3%A707/ URL 6: https://www.enerjiatlasi.com/gunes-enerjisi-haritasi/karaman/ URL 7: http://www.yegm.gov.tr/MyCalculator/pages/70.aspx URL 8: http://birdmap.5dvision.ee/EN/