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Onshore and offshore wind energy potential assessment near Lake Erie shoreline: A spatial and temporal analysis

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  • Li, Jiale
  • Yu, Xiong (Bill)

Abstract

Choosing a proper location is a pivotal initial step in building a wind farm. As appropriate locations for onshore wind farms become more and more scarce, offshore wind farms have drawn significant attention. The coastal line of the Great Lakes is an area that has great wind energy potential. This research conducted detailed statistical analysis of the onshore, nearshore, and offshore wind energy potential of Lake Erie near Cleveland, Ohio. It analyzed the wind data collected in 10-min time intervals from three locations near the Lake Erie shoreline to assess wind characteristics. Statistical analyses of wind data include the Weibull shape and scale factors, turbulence intensity, and wind power density. In addition, the capacity factor and the potential energy output are estimated by using two commercial wind turbines, which are appropriate for the sites at 50 m and 80 m hub heights. The results show that offshore sites will produce at least 1.7 times more energy than the onshore and nearshore sites when using the same commercial wind turbine. Furthermore, offshore wind turbines could produce more power during peak hours in the spring and winter. This indicates that offshore wind turbines offer advantages over onshore wind turbines in Lake Erie.

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  • Li, Jiale & Yu, Xiong (Bill), 2018. "Onshore and offshore wind energy potential assessment near Lake Erie shoreline: A spatial and temporal analysis," Energy, Elsevier, vol. 147(C), pages 1092-1107.
    • Handle: RePEc:eee:energy:v:147:y:2018:i:c:p:1092-1107
    DOI: 10.1016/j.energy.2018.01.118
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    Cited by:

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    3. Wang, Xuefei & Zeng, Xiangwu & Yang, Xu & Li, Jiale, 2019. "Seismic response of offshore wind turbine with hybrid monopile foundation based on centrifuge modelling," Applied Energy, Elsevier, vol. 235(C), pages 1335-1350.
    4. Yang, Zihao & Dong, Sheng, 2024. "A novel framework for wind energy assessment at multi-time scale based on non-stationary wind speed models: A case study in China," Renewable Energy, Elsevier, vol. 226(C).
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    7. Liu, Yichao & Chen, Daoyi & Li, Sunwei & Chan, P.W., 2018. "Discerning the spatial variations in offshore wind resources along the coast of China via dynamic downscaling," Energy, Elsevier, vol. 160(C), pages 582-596.
    8. Lins, Davi Ribeiro & Guedes, Kevin Santos & Pitombeira-Neto, Anselmo Ramalho & Rocha, Paulo Alexandre Costa & de Andrade, Carla Freitas, 2023. "Comparison of the performance of different wind speed distribution models applied to onshore and offshore wind speed data in the Northeast Brazil," Energy, Elsevier, vol. 278(PA).
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