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Identification of optimal waste-to-energy strategies for sustainable development in Iran: SWOT analysis, hybrid MCDM methods, and game theory

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  • Hasankhani, Zahra
  • Zandieh, Mostafa
  • Tirkolaee, Erfan Babaee

Abstract

The growing global focus on environmental sustainability and the pressing need for efficient waste management and energy crisis mitigation have prompted extensive investigations into sustainable waste management strategies. Given Iran's economic development and population growth, the country faces challenges in energy supply and waste management, making waste-to-energy (WtE) applications a promising solution for sustainable waste management. This study employs a combination of SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, Multi-Criteria Decision-Making (MCDM) approaches, and game theory to explore WtE technologies and processes, evaluate their applicability within Iran's context, and identify the most effective WtE strategies for the country. Furthermore, game theory and fuzzy Shapley value analysis were utilized to determine the optimal combination of WtE development strategies. The strategy player “SO” held the highest position of power, with a fuzzy Shapley value of (0.391, 1.744, 3.264), resulting in the identification of the optimal strategy combination of SO2ST2WO1WT2, with a value of (0.429, 0.679, 0.893). The recommended combination emphasizes landfill with gas capture, development of incineration power plants, and integrated resource recovery through residue-derived fuel (RDF) implementation. Achieving these objectives necessitates energy policy reforms, pricing adjustments, improvements in the energy subsidy system, and infrastructure and market development.

Suggested Citation

  • Hasankhani, Zahra & Zandieh, Mostafa & Tirkolaee, Erfan Babaee, 2024. "Identification of optimal waste-to-energy strategies for sustainable development in Iran: SWOT analysis, hybrid MCDM methods, and game theory," Renewable Energy, Elsevier, vol. 237(PA).
    • Handle: RePEc:eee:renene:v:237:y:2024:i:pa:s096014812401632x
    DOI: 10.1016/j.renene.2024.121564
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