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A hybrid multi-criteria decision-making framework for offshore wind turbine selection: A case study in China

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  • Yu, Yang
  • Wu, Shibo
  • Yu, Jianxing
  • Xu, Ya
  • Song, Lin
  • Xu, Weipeng

Abstract

The proper selection of offshore wind turbines is crucial for the long-term development of offshore wind farms. It also contributes to achieving the long-term sustainability goals of offshore wind power. To select the optimal offshore wind turbine with massive difficulties lying in diversity of evaluation criteria, uncertainties in the decision environment and different risk preferences of decision makers, a hybrid multi-criteria decision-making (MCDM) framework is proposed. This framework integrates the interval 2-tuple linguistic (I2TL) model, power weighted average (PWA) operator, stepwise weighted assessment ratio analysis II (SWARA II), method based on the removal effects of criteria (MEREC), cumulative prospect theory (CPT) and combined compromise solution (CoCoSo) method. First, a more realistic and holistic evaluation criteria system is developed for wind turbines based on a two-phase procedure. Then, the I2TL variables are employed to transform the subjective judgments of experts into quantitative evaluation information, and the individual evaluations are fused by the similarity measure-based PWA operator. After that, a new integrated weighing method combined with SWARA II and MEREC is adopted to acquire the criterion weights. Next, the CoCoSo method based on CPT is applied to rank alternatives. An actual case study in China is conducted to demonstrate the applicability of the proposed framework. Finally, the robustness and reliability of the framework are validated through sensitivity and comparison analysis. The hybrid MCDM framework can provide a beneficial reference for decision makers to analyze and select the optimal wind turbine.

Suggested Citation

  • Yu, Yang & Wu, Shibo & Yu, Jianxing & Xu, Ya & Song, Lin & Xu, Weipeng, 2022. "A hybrid multi-criteria decision-making framework for offshore wind turbine selection: A case study in China," Applied Energy, Elsevier, vol. 328(C).
    • Handle: RePEc:eee:appene:v:328:y:2022:i:c:s0306261922014301
    DOI: 10.1016/j.apenergy.2022.120173
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