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A novel fuzzy Bayesian network-based MADM model for offshore wind turbine selection in busy waterways: An application to a case in China

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  • Xue, Jie
  • Yip, Tsz Leung
  • Wu, Bing
  • Wu, Chaozhong
  • van Gelder, P.H.A.J.M.

Abstract

Offshore wind power is an important renewable energy source and plays an essential role in optimizing the energy structure worldwide. Simultaneously, offshore wind turbine (OWT) selection is a complicated process since it concerning various variables and optimization scenarios. In this paper, a novel fuzzy Bayesian network-based model for multiple-attribute decision-making (MADM) is proposed. First of all, a three-layer decision-making framework for OWT selection is established through systematically combing previous studies, expert knowledge, and the principal component analysis (PCA) results by treating the wind turbine parameters, wind turbine economy, wind turbine reliability, and navigation safety as the attributes, and the corresponding 11 influencing factors are identified and quantified. Moreover, a triangular fuzzy number is introduced to fuzzify each influencing factor, and the belief degree for different linguistic variables corresponding to the specific influencing factor is employed in the fuzzy IF-THEN rule system. Then, the belief rule base is transformed into the Bayesian network as the conditional probability tables (CPTs), which can directly express the influence relationship of various factors and realize the integration of various influence factors to obtain the optimal scheme. Finally, the proposed model is validated by taking a case study in busy waterways in the Eastern China Sea as an example. This research provides an intuitive, feasible, and practical way for OWT selection.

Suggested Citation

  • Xue, Jie & Yip, Tsz Leung & Wu, Bing & Wu, Chaozhong & van Gelder, P.H.A.J.M., 2021. "A novel fuzzy Bayesian network-based MADM model for offshore wind turbine selection in busy waterways: An application to a case in China," Renewable Energy, Elsevier, vol. 172(C), pages 897-917.
    • Handle: RePEc:eee:renene:v:172:y:2021:i:c:p:897-917
    DOI: 10.1016/j.renene.2021.03.084
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    References listed on IDEAS

    as
    1. Llorente Iglesias, Rosario & Lacal Arantegui, Roberto & Aguado Alonso, Mónica, 2011. "Power electronics evolution in wind turbines—A market-based analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4982-4993.
    2. Khan, Salman A. & Rehman, Shafiqur, 2013. "Iterative non-deterministic algorithms in on-shore wind farm design: A brief survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 370-384.
    3. Mustakerov, Ivan & Borissova, Daniela, 2010. "Wind turbines type and number choice using combinatorial optimization," Renewable Energy, Elsevier, vol. 35(9), pages 1887-1894.
    4. Mingming Zhang & Mengting Liu, 2014. "Investigation of the Wind Resource Assessment over 2D Continuous Rolling Hills Due to Tropical Cyclones in the Coastal Region of Southeastern China," Energies, MDPI, vol. 7(2), pages 1-21, February.
    5. Z. L. Yang & J. Wang & S. Bonsall & Q. G. Fang, 2009. "Use of Fuzzy Evidential Reasoning in Maritime Security Assessment," Risk Analysis, John Wiley & Sons, vol. 29(1), pages 95-120, January.
    6. Stockton, Keith M., 2004. "Utility-scale wind on islands: an economic feasibility study of Ilio Point, Hawai’i," Renewable Energy, Elsevier, vol. 29(6), pages 949-960.
    7. Jin, Xin & Ju, Wenbin & Zhang, Zhaolong & Guo, Lianxin & Yang, Xiangang, 2016. "System safety analysis of large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1293-1307.
    8. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2013. "Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions," Renewable Energy, Elsevier, vol. 52(C), pages 273-282.
    9. Zhang, Limao & Wu, Xianguo & Skibniewski, Miroslaw J. & Zhong, Jingbing & Lu, Yujie, 2014. "Bayesian-network-based safety risk analysis in construction projects," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 29-39.
    10. Seyed Morteza Hatefi & Jolanta Tamošaitienė, 2018. "Construction Projects Assessment Based on the Sustainable Development Criteria by an Integrated Fuzzy AHP and Improved GRA Model," Sustainability, MDPI, vol. 10(4), pages 1-14, March.
    11. González-Longatt, F. & Wall, P. & Terzija, V., 2012. "Wake effect in wind farm performance: Steady-state and dynamic behavior," Renewable Energy, Elsevier, vol. 39(1), pages 329-338.
    12. Zhang, Mingming & Tan, Bin & Xu, Jianzhong, 2016. "Smart fatigue load control on the large-scale wind turbine blades using different sensing signals," Renewable Energy, Elsevier, vol. 87(P1), pages 111-119.
    13. José F. Herbert-Acero & Oliver Probst & Pierre-Elouan Réthoré & Gunner Chr. Larsen & Krystel K. Castillo-Villar, 2014. "A Review of Methodological Approaches for the Design and Optimization of Wind Farms," Energies, MDPI, vol. 7(11), pages 1-87, October.
    14. Celik, Ali Naci, 2004. "A statistical analysis of wind power density based on the Weibull and Rayleigh models at the southern region of Turkey," Renewable Energy, Elsevier, vol. 29(4), pages 593-604.
    15. Shafiqur Rehman & Salman A. Khan, 2016. "Fuzzy Logic Based Multi-Criteria Wind Turbine Selection Strategy—A Case Study of Qassim, Saudi Arabia," Energies, MDPI, vol. 9(11), pages 1-26, October.
    16. Wu, Bing & Tang, Yuheng & Yan, Xinping & Guedes Soares, Carlos, 2021. "Bayesian Network modelling for safety management of electric vehicles transported in RoPax ships," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    17. Saul Gass & Thomas Saaty, 1955. "The computational algorithm for the parametric objective function," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 2(1‐2), pages 39-45, March.
    18. Sun, Xiaojing & Huang, Diangui & Wu, Guoqing, 2012. "The current state of offshore wind energy technology development," Energy, Elsevier, vol. 41(1), pages 298-312.
    19. Yang, Kyoungboo & Kwak, Gyeongil & Cho, Kyungho & Huh, Jongchul, 2019. "Wind farm layout optimization for wake effect uniformity," Energy, Elsevier, vol. 183(C), pages 983-995.
    Full references (including those not matched with items on IDEAS)

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    2. Xu, Li & Wang, Jin & Ou, Yanxia & Fu, Yang & Bian, Xiaoyan, 2022. "A novel decision-making system for selecting offshore wind turbines with PCA and D numbers," Energy, Elsevier, vol. 258(C).
    3. Dao, Fang & Zeng, Yun & Qian, Jing, 2024. "Fault diagnosis of hydro-turbine via the incorporation of bayesian algorithm optimized CNN-LSTM neural network," Energy, Elsevier, vol. 290(C).

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