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An estimation of the extreme wind speed using the Korea wind map

Author

Listed:
  • Lee, Bong-Hee
  • Ahn, Dong-Joon
  • Kim, Hyun-Goo
  • Ha, Young-Cheol

Abstract

In this study, extreme wind speeds were estimated from the Korea wind map in order to ensure the structural safety of wind turbines. Fifteen major wind farm sites in Korea were selected as target locations for the study. The daily and monthly maximum wind speeds for a three-year span (2005–2007) were extracted from the time-series wind speed of the numerical analysis data obtained at a height of 80 m above ground, and were converted into average times of 3 s and 600 s. The Gumbel and Weibull distributions were used as the probability distribution models for the extreme values, from which the extreme wind speeds were estimated. In order to ascertain the accuracy of the extreme values estimated from the numerical analysis data, they were compared with the extreme values obtained from actual field measurement data collected at a height of 30 m above ground. The results of the comparison indicated that the extreme values for both the numerical analysis data and the field measurement data were identical. The results also showed that the Gumbel distribution model predicts the extreme wind speeds more accurately than the Weibull distribution model does. Therefore, it was decided that the monthly maximum wind speed would be selected to estimate extreme wind speeds for extreme values. Extreme values estimated from the field measurement data at 30 m high above ground. After the comparison, it was found that there was an agreement in the extreme values from both the numerical analysis data and the field measurement data. So, it was more reliable to use the Gumbel distribution as the model of extreme wind speeds than the Weibull distribution, and therefore, it was decided to select the monthly maximum wind speed in order to estimate the extreme wind speeds for extreme values.

Suggested Citation

  • Lee, Bong-Hee & Ahn, Dong-Joon & Kim, Hyun-Goo & Ha, Young-Cheol, 2012. "An estimation of the extreme wind speed using the Korea wind map," Renewable Energy, Elsevier, vol. 42(C), pages 4-10.
    • Handle: RePEc:eee:renene:v:42:y:2012:i:c:p:4-10
    DOI: 10.1016/j.renene.2011.09.033
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    Citations

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    Cited by:

    1. Saravanan Bhaskaran & Amrit Shankar Verma & Andrew J. Goupee & Subhamoy Bhattacharya & Amir R. Nejad & Wei Shi, 2023. "Comparison of Extreme Wind and Waves Using Different Statistical Methods in 40 Offshore Wind Energy Lease Areas Worldwide," Energies, MDPI, vol. 16(19), pages 1-26, October.
    2. Sajid Ali & Choon-Man Jang, 2019. "Selection of Best-Suited Wind Turbines for New Wind Farm Sites Using Techno-Economic and GIS Analysis in South Korea," Energies, MDPI, vol. 12(16), pages 1-22, August.
    3. Mehr Gul & Nengling Tai & Wentao Huang & Muhammad Haroon Nadeem & Moduo Yu, 2020. "Evaluation of Wind Energy Potential Using an Optimum Approach based on Maximum Distance Metric," Sustainability, MDPI, vol. 12(5), pages 1-23, March.
    4. Wang, Jianzhou & Qin, Shanshan & Jin, Shiqiang & Wu, Jie, 2015. "Estimation methods review and analysis of offshore extreme wind speeds and wind energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 26-42.
    5. Grant, Elenya & Johnson, Kathryn & Damiani, Rick & Phadnis, Mandar & Pao, Lucy, 2023. "Buoyancy can ballast control for increased power generation of a floating offshore wind turbine with a light-weight semi-submersible platform," Applied Energy, Elsevier, vol. 330(PB).
    6. Pei-Chi Chang & Ray-Yeng Yang & Chi-Ming Lai, 2015. "Potential of Offshore Wind Energy and Extreme Wind Speed Forecasting on the West Coast of Taiwan," Energies, MDPI, vol. 8(3), pages 1-16, February.
    7. Kang, Dongbum & Ko, Kyungnam & Huh, Jongchul, 2015. "Determination of extreme wind values using the Gumbel distribution," Energy, Elsevier, vol. 86(C), pages 51-58.
    8. Jia, Junmei & Yan, Zaizai & Peng, Xiuyun & An, Xiaoyan, 2020. "A new distribution for modeling the wind speed data in Inner Mongolia of China," Renewable Energy, Elsevier, vol. 162(C), pages 1979-1991.
    9. Christopher Jung & Dirk Schindler & Alexander Buchholz & Jessica Laible, 2017. "Global Gust Climate Evaluation and Its Influence on Wind Turbines," Energies, MDPI, vol. 10(10), pages 1-18, September.

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