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Prediction of Power Generation by Offshore Wind Farms Using Multiple Data Sources

Author

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  • Cheng-Dar Yue

    (Department of Landscape Architecture, National Chiayi University, No. 300, Syuefu Rd., Chiayi 600, Taiwan)

  • Che-Chih Liu

    (Department of Mechanical Engineering, National Cheng Kung University, No. 1, University Road, Tainan City 701, Taiwan)

  • Chien-Cheng Tu

    (Research Center for Energy Technology and Strategy, National Cheng Kung University, No. 25, Xiaodong Rd., North Dist., Tainan City 704, Taiwan)

  • Ta-Hui Lin

    (Department of Mechanical Engineering, National Cheng Kung University, No. 1, University Road, Tainan City 701, Taiwan
    Research Center for Energy Technology and Strategy, National Cheng Kung University, No. 25, Xiaodong Rd., North Dist., Tainan City 704, Taiwan)

Abstract

In this study we evaluated the wind resources of wind farms in the Changhua offshore area of Taiwan. The offshore wind farm in Zone of Potential (ZoP) 26 was optimized through an economic evaluation. The annual energy production (AEP) of the offshore wind farm in ZoP 26 was predicted for 10 and 25 years with probabilities of 50%, 75%, and 90% by using measured mast data, measure-correlate-predict (MCP) data derived from Modern-Era Retrospective Analysis for Research and Applications (MERRA), and Central Weather Bureau (CWB) data. When the distance between the turbines in a wind farm was decreased from 12D to 6D, the turbine number increased from 53 to 132, while the capacity factor decreased slightly from 48.6% to 47.6%. MCP data derived from the inland CWB station with similar levels of wind resources can be used to accurately predict the power generation of the target offshore wind farm. The use of MCP with mast data as target data, together with CWB and MERRA data as reference data, proved to be a feasible method for predicting offshore wind power generation in places where a mast is available in a neighboring area.

Suggested Citation

  • Cheng-Dar Yue & Che-Chih Liu & Chien-Cheng Tu & Ta-Hui Lin, 2019. "Prediction of Power Generation by Offshore Wind Farms Using Multiple Data Sources," Energies, MDPI, vol. 12(4), pages 1-24, February.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:700-:d:207949
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    References listed on IDEAS

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