The Selection of Appropriate Renewable Energy Source For Turkey By Using Entropy and Waspas Methods

Öz

The production and consumption of energy, which are indispensable inputs for production, cause negative externalities on the environment and human health as well as harm the development of the country. Therefore, countries have two basic motivations when selecting energy source. The first is to have a strong economy by taking into account the increase in production and competitive power provided by the energy source, and the second is to avoid the selection of energy source that will reduce the prosperity of the people. The technical, economic, environmental and social criteria of renewable energy sources are ranked with respect to their importance degree by means of Entropy method in this study where the energy source selection which can be suitable for our country is made. In this study where the energy source selection which can be suitable for our country is made and in second stage the WASPAS method is used to suggest which renewable energy source is the most suitable to meet the energy demand in Turkey. The results obtained in WASPAS method indicated the ranking of renewable energy sources, which are the suitable for investment in Turkey, as Hydro, Geothermal, Wind, Biomass, Solar.

Anahtar Kelimeler

• Renewable energy selection
• Multi criteria decision-making
• Entropy
• WASPAS

Entropi ve Waspas Yöntemleri Kullanılarak Türkiye İçin Uygun Yenilenebilir Enerji Kaynağının Seçimi

Öz

Üretim için vazgeçilmez bir girdi olan enerji, üretim ve tüketimiyle çevre ve insan sağlığı üzerinde negatif dışsallıklara neden olmakta ve ülke kalkınmasına zarar vermektedir. Bu nedenle ülkeler enerji kaynağı seçimi yaparken iki temel motivasyonla hareket etmektedir. İlki enerji kaynağının sağladığı üretim artışını ve rekabet gücünü dikkate alarak güçlü bir ekonomiye sahip olmak, ikincisi ise halkın refahını düşürecek enerji kaynak seçiminden uzak durmaktadır. Ülkemiz için uygun olabilecek enerji kaynak seçiminin yapıldığı bu çalışmada Entropi yöntemi yardımıyla yenilenebilir enerji kaynaklarına ait teknik, ekonomik, çevresel ve sosyal kriterler, önem derecesine göre sıralanmış ve ikinci aşamada WASPAS yöntemiyle Türkiye’de enerji ihtiyacının karşılanmasında uygun yenilenebilir enerji kaynağının hangisi olabileceği yönünde öneri getirilmiştir. WASPAS yönteminden elde edilen sonuçlar Türkiye için yatırım yapılabilecek
uygun yenilenebilir enerji kaynak sıralamasının Hidro, Jeotermal, Rüzgâr, Biyokütle, Güneş şeklinde olduğunu göstermiştir. 

Anahtar Kelimeler

• Yenilenebilir enerji seçimi
• çok kriterli karar verme
• Entropi
• WASPAS

Kaynakça

1. BP (2016a). BP Statistical Review of World Energy June 2016, Carbon dioxide emissions, 65th edition, http://www.bp.com/ content/dam/bp/pdf/energy-economics/statistical-review- 2016/bp-statistical-review-of-world-energy-2016-co2- emissions.pdf, (10.05.2017)
2. BP (2016b). BP Statistical Review of World Energy June 2016. http://www.bp.com/content/dam/bp/pdf/energy-economics/ statistical-review-2016/bp-statistical-review-of-world-energy- 2016-full-report.pdf, (10.05.2017)
3. EESI (2016). Fossil Fuels. http://www.eesi.org/topics/fossil-fuels/ description, (10.05.2017)
4. EİA (2016), “Levelized Cost and Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook 2016”, US Energy Information Administration, http://www.eia.gov/ outlooks/aeo/pdf/electricity_generation.pdf , (10.05.2017)
5. ETKB (2015). İstatistikler, Denge Tabloları, Enerji İşleri Genel Müdürlüğü, Ankara, http://www.eigm.gov.tr/tr-TR/ Denge-Tablolari/Denge-Tablolari, (10.05.2017)
6. Görez, T. ve Alkan, A. (2005), “Türkiye’nin Yenilenebilir Enerji Kaynakları ve Hidroelektrik Enerji Potansiyeli”, III. Yenilenebilir Enerji Kaynakları Sempozyumu, Mersin, 19-21.
7. IEA (2015). “IEA Energy Atlas”, IEA Statistic, http://energyatlas. iea.org/?subject=-1002896040, (10.05.2017)
8. IPCC (2007). Climate Change 2007: Synthesis Report, Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 12-17 November 2007, Valencia, Spain, https:// www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr.pdf, (10.05.2017)

9. IPCC (2013). Climate Change 2013: The Physical Science Basis, Summary for Policymakers, Technical Summary and Frequently Asked Questions. Intergovernmental Panel on Climate Change.
10. IPCC (2014), “IPCC Working Group III-Mitigation of Climate Change, Annex III: Technology-Specific Cost and Performance Parameters”, https://www.ipcc.ch/pdf/assessment-report/ar5/ wg3/ipcc_wg3_ar5_annex-iii.pdf, (10.05.2017)
11. IRENA (2016) Renewable Energy and Jobs Annual Review 2016. International Renewable Energy Agency. http://www.irena. org/DocumentDownloads/Publications/IRENA_RE_Jobs_Annual_ Review_2016.pdf (10.05.2017)
12. Kayakutlu, G. ve Ercan, S. (2015), “Regional Energy Portfolio Construction: Case Studies in Turkey. In Sustainable Future Energy Technology and Supply Chains”, Springer International Publishing, 107-126.
13. Kenny, R., Law, C. ve Pearce, J.M. (2010), “Towards Real Energy Economics: Energy Policy Driven by Life-Cycle Carbon Emission”, Energy Policy, 38(4), 1969-1978.
14. Li, X., Wang, K., Liu, L., Xin, J., Yang, H. ve Gao, C. (2011)”Application of the entropy weight and TOPSIS method in safety evaluation of coal mines.” Procedia Engineering, 26 : 2085-2091.
15. Mardani, A., Nilashi, M., Zakuan, N., Loganathan, N., Soheilirad, S., Saman, M. Z. M. ve Ibrahim, O. (2017) “A systematic review and meta-Analysis of SWARA and WASPAS methods: Theory and applications with recent fuzzy developments.” Applied Soft Computing, 52: 265-292.
16. NETL (2013), “Power Generation Technology Comparison from a Life Cycle Perspective”, National Energy Technology Laboratory, US Department of Energy, Pittsburgh, PA, USA, https:// www.netl.doe.gov/File%20Library/Research/Energy%20Analysis/ Life%20Cycle%20Analysis/Technology-Assessment-Compilation- Report.pdf, (10.05.2017)
17. OECD (2015). OECD Employment Outlook 2015, Paris, http:// www.oecd.org/els/oecd-employment-outlook-19991266. htm, (10.05.2017)
18. REN21 (2015), “Renewables 2015 Global Status Report”, Renewable Energy Policy Network for the 21st Century, http:// www.ren21.net/wp-content/uploads/2015/07/GSR2015_Key- Findings_lowres.pdf, (10.05.2017)
19. Rutovitz, J. (2010), “South African Energy Sector Jobs to 2030”, Greenpeace Africa by the Institute for Sustainable Futures, University of Technology, Sydney, Greenpeace Africa, Johannesburg.
20. Rutovitz, J. ve Harris, S. (2012), “Calculating Global Energy Sector Jobs: 2012 Methodology”, Prepared for Greenpeace International by the Institute for Sustainable Futures, University of Technology, Sydney.
21. Stein, E.W. (2013), “A Comprehensive Multi-Criteria Model to Rank Electric Energy Production Technologies”, Renewable and Sustainable Energy Reviews, 22, 640-654. https://e3garden. com/wp-content/uploads/2013/10/RSER2418_Stein.pdf, (10.05.2017)
22. TCMB (2015). Ödemeler Dengesi İstatistikleri, http://www. tcmb.gov.tr/wps/wcm/connect/30cdfd52-aa34-40ce-8b57- 4ef53e322ce4/odemelerdengesi.pdf?MOD=AJPERES&CACHEID= 30cdfd52-aa34-40ce-8b57-4ef53e322ce4, (10.05.2017)
23. TEİAŞ (2016) Türkiye Elektrik Üretim-İletim İstatistikleri. Türkiye Elektrik İletim A.Ş. Genel Müdürlüğü. http://www.teias.gov. tr/T%C3%BCrkiyeElektrik%C4%B0statistikleri/istatistik2015/ istatistik2015.htm, (10.05.2017)
24. TEİAŞ (2016), “Türkiye 2015 Yılı Elektrik Üretim-İletim İstatistikleri”, Türkiye Elektrik İletim A.Ş. Genel Müdürlüğü Planlama ve Stratejik Yönetim Dairesi Başkanliği Üretim Planlama ve İstatistik Müdürlüğü, Ankara, http://www.teias.gov. tr/T%C3%BCrkiyeElektrik%C4%B0statistikleri/istatistik2015/ istatistik2015.htm, (10.05.2017)
25. UNFCCC (2015). GHG Data: GHG total including LULUCF, United Nations Framework Convention on Climate Change, http:// unfccc.int/ghg_data/ghg_data_unfccc/time_series_annex_i/ items/3842.php, (10.05.2017)
26. US Energy Information Administration (2015), “Levelized Cost and Levelized Avoided Cost of New Generation Resources in the Annual Energy Outlook”, http://www.eia.gov/outlooks/ archive/aeo15/pdf/electricity_generation_2015.pdf, (10.05.2017)
27. Wang, T. C. ve Lee, H. D. (2009) “Developing a fuzzy TOPSIS approach based on subjective weights and objective weights.” Expert Systems with Applications, 36(5): 8980-8985.
28. Zavadskas, E. K. ve Turskis, Z. (2010) “A new additive ratio assessment (ARAS) method in multicriteria decision‐making.” Technological and Economic Development of Economy, 16(2): 159-172.
29. Zavadskas, E. K., Turskis, Z., Antucheviciene, J. ve Zakarevicius, A. (2012) “Optimization of weighted aggregated sum product assessment.” Elektronika ir elektrotechnika, 122(6): 3-6.