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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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    as
    1. Hu, Shushan & Hoare, Cathal & Raftery, Paul & O’Donnell, James, 2019. "Environmental and energy performance assessment of buildings using scenario modelling and fuzzy analytic network process," Applied Energy, Elsevier, vol. 255(C).
    2. Van Thanh Nguyen & Nguyen Hoang Hai & Nguyen Thi Kim Lan, 2022. "Spherical Fuzzy Multicriteria Decision-Making Model for Wind Turbine Supplier Selection in a Renewable Energy Project," Energies, MDPI, vol. 15(3), pages 1-12, January.
    3. Morteza Yazdani & Pascale Zaraté & Edmundas Kazimieras Zavadskas & Zenonas Turskis, 2019. "A Combined Compromise Solution (CoCoSo) method for multi-criteria decision-making problems," Post-Print hal-02879091, HAL.
    4. Li, Mingxin & Jiang, Xiaoli & Carroll, James & Negenborn, Rudy R., 2022. "A multi-objective maintenance strategy optimization framework for offshore wind farms considering uncertainty," Applied Energy, Elsevier, vol. 321(C).
    5. Radu, David & Berger, Mathias & Dubois, Antoine & Fonteneau, Raphaël & Pandžić, Hrvoje & Dvorkin, Yury & Louveaux, Quentin & Ernst, Damien, 2022. "Assessing the impact of offshore wind siting strategies on the design of the European power system," Applied Energy, Elsevier, vol. 305(C).
    6. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    7. Liu, Bingsheng & Liu, Song & Xue, Bin & Lu, Shijian & Yang, Yang, 2021. "Formalizing an integrated decision-making model for the risk assessment of carbon capture, utilization, and storage projects: From a sustainability perspective," Applied Energy, Elsevier, vol. 303(C).
    8. Elkadeem, M.R. & Younes, Ali & Sharshir, Swellam W. & Campana, Pietro Elia & Wang, Shaorong, 2021. "Sustainable siting and design optimization of hybrid renewable energy system: A geospatial multi-criteria analysis," Applied Energy, Elsevier, vol. 295(C).
    9. Lozano-Minguez, E. & Kolios, A.J. & Brennan, F.P., 2011. "Multi-criteria assessment of offshore wind turbine support structures," Renewable Energy, Elsevier, vol. 36(11), pages 2831-2837.
    10. Sitorus, Fernando & Brito-Parada, Pablo R., 2020. "A multiple criteria decision making method to weight the sustainability criteria of renewable energy technologies under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    11. Li, Xiang & Gao, Qi & Cao, Yuying & Yang, Yanfei & Liu, Shiming & Wang, Zhong Lin & Cheng, Tinghai, 2022. "Optimization strategy of wind energy harvesting via triboelectric-electromagnetic flexible cooperation," Applied Energy, Elsevier, vol. 307(C).
    12. Gao, Jianwei & Guo, Fengjia & Ma, Zeyang & Huang, Xin & Li, Xiangzhen, 2020. "Multi-criteria group decision-making framework for offshore wind farm site selection based on the intuitionistic linguistic aggregation operators," Energy, Elsevier, vol. 204(C).
    13. Jallal, Mohammed Ali & González-Vidal, Aurora & Skarmeta, Antonio F. & Chabaa, Samira & Zeroual, Abdelouhab, 2020. "A hybrid neuro-fuzzy inference system-based algorithm for time series forecasting applied to energy consumption prediction," Applied Energy, Elsevier, vol. 268(C).
    14. Kheybari, Siamak & Kazemi, Mostafa & Rezaei, Jafar, 2019. "Bioethanol facility location selection using best-worst method," Applied Energy, Elsevier, vol. 242(C), pages 612-623.
    15. Nansheng Pang & Mengfan Nan & Qichen Meng & Siyang Zhao, 2021. "Selection of Wind Turbine Based on Fuzzy Analytic Network Process: A Case Study in China," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    16. Sayyid Ali Banihashemi & Mohammad Khalilzadeh & Edmundas Kazimieras Zavadskas & Jurgita Antucheviciene, 2021. "Investigating the Environmental Impacts of Construction Projects in Time-Cost Trade-Off Project Scheduling Problems with CoCoSo Multi-Criteria Decision-Making Method," Sustainability, MDPI, vol. 13(19), pages 1-17, September.
    17. Singh, Shweta & Upadhyay, Surya Prakash & Powar, Satvasheel, 2022. "Developing an integrated social, economic, environmental, and technical analysis model for sustainable development using hybrid multi-criteria decision making methods," Applied Energy, Elsevier, vol. 308(C).
    18. Ma, Hongliang & Ge, Mingwei & Wu, Guangxing & Du, Bowen & Liu, Yongqian, 2021. "Formulas of the optimized yaw angles for cooperative control of wind farms with aligned turbines to maximize the power production," Applied Energy, Elsevier, vol. 303(C).
    19. Wang, Kang & Wang, Jianzhou & Zeng, Bo & Lu, Haiyan, 2022. "An integrated power load point-interval forecasting system based on information entropy and multi-objective optimization," Applied Energy, Elsevier, vol. 314(C).
    20. Zhao, Haoran & Guo, Sen & Zhao, Huiru, 2019. "Comprehensive assessment for battery energy storage systems based on fuzzy-MCDM considering risk preferences," Energy, Elsevier, vol. 168(C), pages 450-461.
    21. Supciller, Aliye Ayca & Toprak, Fatih, 2020. "Selection of wind turbines with multi-criteria decision making techniques involving neutrosophic numbers: A case from Turkey," Energy, Elsevier, vol. 207(C).
    22. Ju, Liwei & Zhao, Rui & Tan, Qinliang & Lu, Yan & Tan, Qingkun & Wang, Wei, 2019. "A multi-objective robust scheduling model and solution algorithm for a novel virtual power plant connected with power-to-gas and gas storage tank considering uncertainty and demand response," Applied Energy, Elsevier, vol. 250(C), pages 1336-1355.
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