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Determining the Optimized Hub Height of Wind Turbine Using the Wind Resource Map of South Korea

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  • Jung-Tae Lee

    (New and Renewable Energy Resource & Policy Center, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon 34129, Korea)

  • Hyun-Goo Kim

    (New and Renewable Energy Resource & Policy Center, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon 34129, Korea)

  • Yong-Heack Kang

    (New and Renewable Energy Resource & Policy Center, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon 34129, Korea)

  • Jin-Young Kim

    (New and Renewable Energy Resource & Policy Center, Korea Institute of Energy Research, 152 Gajeong-ro, Yuseong-gu, Daejeon 34129, Korea)

Abstract

Although the size of the wind turbine has become larger to improve the economic feasibility of wind power generation, whether increases in rotor diameter and hub height always lead to the optimization of energy cost remains to be seen. This paper proposes an algorithm that calculates the optimized hub height to minimize the cost of energy (COE) using the regional wind profile database. The optimized hub height was determined by identifying the minimum COE after calculating the annual energy production (AEP) and cost increase, according to hub height increase, by using the wind profiles of the wind resource map in South Korea and drawing the COE curve. The optimized hub altitude was calculated as 75~80 m in the inland plain but as 60~70 m in onshore or mountain sites, where the wind profile at the lower layer from the hub height showed relatively strong wind speed than that in inland plain. The AEP loss due to the decrease in hub height was compensated for by increasing the rotor diameter, in which case COE also decreased in the entire region of South Korea. The proposed algorithm of identifying the optimized hub height is expected to serve as a good guideline when determining the hub height according to different geographic regions.

Suggested Citation

  • Jung-Tae Lee & Hyun-Goo Kim & Yong-Heack Kang & Jin-Young Kim, 2019. "Determining the Optimized Hub Height of Wind Turbine Using the Wind Resource Map of South Korea," Energies, MDPI, vol. 12(15), pages 1-13, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:2949-:d:253580
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    References listed on IDEAS

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    1. Emami, Alireza & Noghreh, Pirooz, 2010. "New approach on optimization in placement of wind turbines within wind farm by genetic algorithms," Renewable Energy, Elsevier, vol. 35(7), pages 1559-1564.
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    3. Maki, Kevin & Sbragio, Ricardo & Vlahopoulos, Nickolas, 2012. "System design of a wind turbine using a multi-level optimization approach," Renewable Energy, Elsevier, vol. 43(C), pages 101-110.
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    Cited by:

    1. Shafiqur Rehman & Salman A. Khan & Luai M. Alhems, 2020. "A Rule-Based Fuzzy Logic Methodology for Multi-Criteria Selection of Wind Turbines," Sustainability, MDPI, vol. 12(20), pages 1-21, October.
    2. Petrović, A. & Đurišić, Ž., 2021. "Genetic algorithm based optimized model for the selection of wind turbine for any site-specific wind conditions," Energy, Elsevier, vol. 236(C).
    3. Franke, Katja & Sensfuß, Frank & Deac, Gerda & Kleinschmitt, Christoph & Ragwitz, Mario, 2021. "Factors affecting the calculation of wind power potentials: A case study of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    4. Myeongchan Oh & Boyoung Kim & Changyeol Yun & Chang Ki Kim & Jin-Young Kim & Su-Jin Hwang & Yong-Heack Kang & Hyun-Goo Kim, 2022. "Spatiotemporal Analysis of Hydrogen Requirement to Minimize Seasonal Variability in Future Solar and Wind Energy in South Korea," Energies, MDPI, vol. 15(23), pages 1-13, November.
    5. Katarzyna Wolniewicz & Adam Zagubień & Mirosław Wesołowski, 2021. "Energy and Acoustic Environmental Effective Approach for a Wind Farm Location," Energies, MDPI, vol. 14(21), pages 1-17, November.
    6. Andrés E. Feijóo-Lorenzo, 2021. "Wind Farm Power Curves and Power Distributions," Energies, MDPI, vol. 15(1), pages 1-2, December.

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