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Study of Generalized Interaction Wake Models Systems with ELM Variation for Off-Shore Wind Farms

Author

Listed:
  • Mingcan Li

    (School of Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
    These authors contributed equally to this work.)

  • Hanbin Xiao

    (School of Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
    These authors contributed equally to this work.)

  • Lin Pan

    (School of Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
    National Engineering Research Center for Water Transport Safety (WTS Center), Wuhan 430063, China
    State Key Laboratory of Ocean Engineering, Shanghai Jiaotong University, Shanghai 200240, China)

  • Chengjun Xu

    (School of Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China
    These authors contributed equally to this work.)

Abstract

This paper reports a novel frandsen generalized wake model and its variation model-frandsen generalized normal distribution wake model for off-shore wind farms. Two different new wake models in off-shore wind farms have been studied comparatively. Their characteristics have been analyzed through mathematical modeling and derivation. Meanwhile, simulation experiments show that the proposed two new wake models have different properties. Furthermore, the distributions of wind speed and wind direction are modeled by the statistical methods and Extreme Learning Machine through the off-shore wind farms of Yangshan Deepwater Harbor in the Port of Shanghai, China. In addition, the data of wind energy are provided to verify and test the correctness and effectiveness of the proposed two models. Wind power has been demonstrated by wind rose and wind resources with real-time data. These techniques contribute to enhance planning, utilization and exploitation for wind power of off-shore wind farms.

Suggested Citation

  • Mingcan Li & Hanbin Xiao & Lin Pan & Chengjun Xu, 2019. "Study of Generalized Interaction Wake Models Systems with ELM Variation for Off-Shore Wind Farms," Energies, MDPI, vol. 12(5), pages 1-32, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:863-:d:211103
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    References listed on IDEAS

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    2. Pan, Lin & Wang, Xudong, 2020. "Variable pitch control on direct-driven PMSG for offshore wind turbine using Repetitive-TS fuzzy PID control," Renewable Energy, Elsevier, vol. 159(C), pages 221-237.

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