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Research on Wind Turbine Location and Wind Energy Resource Evaluation Methodology in Port Scenarios

Author

Listed:
  • Chuan Huang

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China)

  • Changjian Liu

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    Digital Laboratory of Integrated Transportation Planning, Beijing 100028, China)

  • Ming Zhong

    (Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China
    National Engineering Research Center for Water Transport Safety, Wuhan University of Technology, Wuhan 430063, China
    State Key Laboratory of Waterway Traffic Control, Wuhan University of Technology, Wuhan 430063, China)

  • Hanbing Sun

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    Digital Laboratory of Integrated Transportation Planning, Beijing 100028, China)

  • Tianhang Gao

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    Digital Laboratory of Integrated Transportation Planning, Beijing 100028, China)

  • Yonglin Zhang

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
    Digital Laboratory of Integrated Transportation Planning, Beijing 100028, China)

Abstract

Wind energy is widely distributed in China as a renewable energy source. Aiming to alleviate the issues resulting from fossil fuel consumption faced by developing and developed countries (e.g., climate change) and to meet development needs, this study innovatively proposed methods for the location selection of wind farms and wind turbines in port areas based on the fuzzy comprehensive evaluation method. Considering that the wind turbine location is crucial to wind power generation, this paper focuses on locating wind turbines within a specific set of sea ports. The primary objectives of this paper are to evaluate the potential of wind power generation under different port scenarios and develop a method for assessing the potential of wind energy resources in wind farm areas. Firstly, a method is proposed for identifying the boundaries of wind farms in the port areas and locating wind turbines at sea ports. Furthermore, this study used the National Aeronautics and Space Administration (NASA) wind speed database to test the proposed method with the real-world wind power projects of the Ports of Tianjin, Shanghai, Xiamen, Shenzhen, and Hainan, which are top ports within five major coastal port clusters in China. It is found that the potential power generation capacity of the wind power farms at the above ports is 30.71 GWh, 19.82 GWh, 16.72 GWh, 29.45 GWh, and 24.42 GWh, respectively. Additionally, sensitive results for different types of wind turbines are conducted in the following experiment. The results of this study are fundamental for enriching the research of evaluating wind energy resources of sea ports and promoting the development and use of clean energy in practical environments. Further, the method proposed in this study is essential for optimizing the location and construction of wind turbines, which may help ports in adopting a low-carbon and green development path, thereby mitigating air pollution, and promoting sustainable development.

Suggested Citation

  • Chuan Huang & Changjian Liu & Ming Zhong & Hanbing Sun & Tianhang Gao & Yonglin Zhang, 2024. "Research on Wind Turbine Location and Wind Energy Resource Evaluation Methodology in Port Scenarios," Sustainability, MDPI, vol. 16(3), pages 1-24, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:3:p:1074-:d:1326997
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    References listed on IDEAS

    as
    1. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2023. "Sustainable development pathways of China's wind power industry under uncertainties: Perspective from economic benefits and technical potential," Energy Policy, Elsevier, vol. 182(C).
    2. Díaz, H. & Silva, D. & Bernardo, C. & Guedes Soares, C., 2023. "Micro sitting of floating wind turbines in a wind farm using a multi-criteria framework," Renewable Energy, Elsevier, vol. 204(C), pages 449-474.
    3. Elshafei, Basem & Peña, Alfredo & Xu, Dong & Ren, Jie & Badger, Jake & Pimenta, Felipe M. & Giddings, Donald & Mao, Xuerui, 2021. "A hybrid solution for offshore wind resource assessment from limited onshore measurements," Applied Energy, Elsevier, vol. 298(C).
    4. Jin, Jingxin & Li, Yilin & Ye, Lin & Xu, Xunjian & Lu, Jiazheng, 2023. "Integration of atmospheric stability in wind resource assessment through multi-scale coupling method," Applied Energy, Elsevier, vol. 348(C).
    5. Wimhurst, Joshua J. & Greene, J. Scott & Koch, Jennifer, 2023. "Predicting commercial wind farm site suitability in the conterminous United States using a logistic regression model," Applied Energy, Elsevier, vol. 352(C).
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