Optimizing parametric insurance for renewable energy investments: Integrating fuzzy decision-making and artificial intelligence techniques

ETİ S., YÜKSEL S., DİNÇER H., Pamucar D., Deveci M., Antucheviciene J., ...Daha Fazla

Renewable Energy, cilt.246, 2025 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 246
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1016/j.renene.2025.122856
  • Dergi Adı: Renewable Energy
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Compendex, Environment Index, Geobase, Greenfile, Index Islamicus, INSPEC, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, DIALNET, Civil Engineering Abstracts
  • Anahtar Kelimeler: Artificial intelligence-based fuzzy logic, Pythagorean fuzzy sets, Renewable energy, Risks of investments, Sine trigonometric fuzzy logic, Solar panels
  • Marmara Üniversitesi Adresli: Evet

Özet

Small-scale solar panel investments have significant risks because of market fluctuations. However, traditional insurance models often lead to inadequate coverage. This situation has a negative impact on profitability of the projects. To satisfy this situation, this study evaluates the effectiveness of parametric insurance by identifying optimal factors in this process. The research applies an artificial intelligence-based sine trigonometric Pythagorean fuzzy (STPF) entropy technique and CRiteria Importance Through Intercriteria Correlation (CRITIC) methodology to determine the significance of criteria. In addition, geometric mean of similarity ratio to optimal solution (RATGOS) approach is employed to rank risk factors. The main contribution of this paper is that integrating the Artificial Intelligence (AI) approach into fuzzy decision-making techniques increases both the quality and originality of the proposed model. With the help of this issue, decision matrix can be constructed via AI technique so that more realistic and appropriate findings can be identified. Findings indicate that cost is the most influential factor (weight: 0.1059), followed by trigger (weight: 0.0632), policy (weight: 0.0629), and adoptability (weight: 0.0587). On the other side, based on the ranking results, price is the most essential alternative for making parametric insurance regarding small scale solar panel investments. Therefore, policymakers and insurers should focus on cost-optimized coverage models to prioritize essential risk factors while avoiding unnecessary over-insurance.