A spatial decision making framework using neutrosophic VIKOR for wind energy investment in Turkey


EROĞLU H.

SCIENTIFIC REPORTS, cilt.15, sa.1, 2025 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 1
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1038/s41598-025-18799-w
  • Dergi Adı: SCIENTIFIC REPORTS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, Chemical Abstracts Core, MEDLINE, Directory of Open Access Journals
  • Recep Tayyip Erdoğan Üniversitesi Adresli: Evet

Özet

The growing demand for clean energy and the urgency of reducing carbon emissions have made wind power a key element of Turkey's renewable energy strategy. However, identifying optimal regions for wind energy investment remains a complex task due to the interplay of technical, spatial, and economic factors, all of which are characterized by varying degrees of uncertainty. Although GIS-based site selection and multi-criteria decision-making (MCDM) methods are widely used, few approaches integrate expert judgment and spatial analysis within an uncertainty-aware national planning framework. This study proposes a novel investment prioritization model that combines Geographic Information Systems (GIS) with the Neutrosophic-VIKOR method to assess regional wind energy potential in Turkey. The model considers five core criteria: wind potential, land cost, energy consumption based on population density, presence of existing wind farms, and expert judgment. Expert input is represented using Single-Valued Neutrosophic linguistic scales. A similarity-based weighting method is used to determine the relative influence of each expert. The resulting Priority Index (PI) highlights Bal & imath;kesir, & Ccedil;anakkale, and & Idot;zmir as the top three investment regions due to their wind characteristics and energy demand. Istanbul and Samsun also rank highly, supported by existing infrastructure and consumption levels. The proposed framework offers a replicable, uncertainty-aware tool for supporting national wind energy planning. By combining expert-based neutrosophic modeling with spatial analysis, the study addresses existing methodological gaps and provides actionable insights for investors and policymakers pursuing efficient and balanced renewable energy development.