An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey's energy planning


Ervural B. C., Zaim S., Demirel O. F., Aydin Z., Delen D.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS, cilt.82, ss.1538-1550, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 82
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.rser.2017.06.095
  • Dergi Adı: RENEWABLE & SUSTAINABLE ENERGY REVIEWS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1538-1550
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Energy planning involves a perpetual process of reevaluating alternative energy strategies. Authorities responsible for energy planning and management have to adjust their strategies according to new and improved alternative solutions based on the sustainability criteria. In this study, we propose an integrated hybrid methodology for the analysis of Turkey's energy sector using Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, Analytic Network Process (ANP) process, and weighted fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to formulate and holistically analyze the energy strategy alternatives and priorities. The methodology proposed in this study allowed identifying the relevant criteria and sub-criteria using a SWOT analysis. Then, ANP approach, which is one of the popular multi-criteria decision making (MCDM) methods, is employed to determine the weights of each SWOT factors and sub-factors. Finally, fuzzy TOPSIS methodology is conducted to prioritize alternative energy strategies. We discuss the obtained results for the development of long-range alternative energy strategies. The results showed that turning the country into an energy hub and an energy terminal by effectively using the geo-strategic position within the framework of the regional cooperation is the most important priority. On the other hand, using the nuclear energy technologies within the energy supply strategies found to be the least favored priority.