IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v46y2012i1p555-563.html
   My bibliography  Save this article

An assessment of wind energy potential at the demonstration offshore wind farm in Korea

Author

Listed:
  • Oh, Ki-Yong
  • Kim, Ji-Young
  • Lee, Jae-Kyung
  • Ryu, Moo-Sung
  • Lee, Jun-Shin

Abstract

The construction of an offshore demonstration wind farm was planned in a southwestern sea-area of the Korean Peninsula. To estimate economic feasibility and to establish a reliable design basis, it is necessary to identify the design parameters of the demo-farm. For a reliable estimation of the design parameters, the first offshore meteorological mast, HeMOSU (Herald of the Meteorological and Oceanographic Special Research Unit), was constructed at the site of the demo-farm. In addition, supplementary meteorological masts were installed in advance at Gochang and Wangdeung-do in order to enhance the estimation of the long-term wind potential for the demo-farm. In this paper, assessments of wind energy potential are carried out with the data measured from these three meteorological masts. The analysis includes seasonal and diurnal changes in wind speed and surface roughness as well as wind/energy rose. Long-term wind potential is also estimated by using MCP (Measure-Correlate-Predict) techniques to clarify the design basis and to determine the wind turbine class in accordance with IEC 61400. The AEP (Annual Energy Production), as well as the C.F. (Capacity Factor) of the candidate site are evaluated with the estimated design parameters.

Suggested Citation

  • Oh, Ki-Yong & Kim, Ji-Young & Lee, Jae-Kyung & Ryu, Moo-Sung & Lee, Jun-Shin, 2012. "An assessment of wind energy potential at the demonstration offshore wind farm in Korea," Energy, Elsevier, vol. 46(1), pages 555-563.
  • Handle: RePEc:eee:energy:v:46:y:2012:i:1:p:555-563
    DOI: 10.1016/j.energy.2012.07.056
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544212006056
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2012.07.056?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Guo, Zhenhai & Zhao, Jing & Zhang, Wenyu & Wang, Jianzhou, 2011. "A corrected hybrid approach for wind speed prediction in Hexi Corridor of China," Energy, Elsevier, vol. 36(3), pages 1668-1679.
    2. Islam, M.R. & Saidur, R. & Rahim, N.A., 2011. "Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function," Energy, Elsevier, vol. 36(2), pages 985-992.
    3. Oh, Ki-Yong & Kim, Ji-Young & Lee, Jun-Shin & Ryu, Ki-Wahn, 2012. "Wind resource assessment around Korean Peninsula for feasibility study on 100 MW class offshore wind farm," Renewable Energy, Elsevier, vol. 42(C), pages 217-226.
    4. Rehman, Shafiqur & Ahmad, Aftab, 2004. "Assessment of wind energy potential for coastal locations of the Kingdom of Saudi Arabia," Energy, Elsevier, vol. 29(8), pages 1105-1115.
    5. Lim, Hee-Chang & Jeong, Tae-Yoon, 2010. "Wind energy estimation of the Wol-Ryong coastal region," Energy, Elsevier, vol. 35(12), pages 4700-4709.
    6. Carta, José A. & Velázquez, Sergio, 2011. "A new probabilistic method to estimate the long-term wind speed characteristics at a potential wind energy conversion site," Energy, Elsevier, vol. 36(5), pages 2671-2685.
    7. Onat, Nevzat & Ersoz, Sedat, 2011. "Analysis of wind climate and wind energy potential of regions in Turkey," Energy, Elsevier, vol. 36(1), pages 148-156.
    8. Ko, Kyungnam & Kim, Kyoungbo & Huh, Jongchul, 2010. "Variations of wind speed in time on Jeju Island, Korea," Energy, Elsevier, vol. 35(8), pages 3381-3387.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kim, Ji-Young & Oh, Ki-Yong & Kim, Min-Suek & Kim, Kwang-Yul, 2019. "Evaluation and characterization of offshore wind resources with long-term met mast data corrected by wind lidar," Renewable Energy, Elsevier, vol. 144(C), pages 41-55.
    2. Kang, Dongbum & Ko, Kyungnam & Huh, Jongchul, 2015. "Determination of extreme wind values using the Gumbel distribution," Energy, Elsevier, vol. 86(C), pages 51-58.
    3. Yu, Jie & Chen, Kuilin & Mori, Junichi & Rashid, Mudassir M., 2013. "A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction," Energy, Elsevier, vol. 61(C), pages 673-686.
    4. Woochul Nam & Ki-Yong Oh, 2020. "Mutually Complementary Measure-Correlate-Predict Method for Enhanced Long-Term Wind-Resource Assessment," Mathematics, MDPI, vol. 8(10), pages 1-20, October.
    5. Wang, Jianzhou & Qin, Shanshan & Zhou, Qingping & Jiang, Haiyan, 2015. "Medium-term wind speeds forecasting utilizing hybrid models for three different sites in Xinjiang, China," Renewable Energy, Elsevier, vol. 76(C), pages 91-101.
    6. Ho, Lip-Wah, 2016. "Wind energy in Malaysia: Past, present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 279-295.
    7. Mohammed H. Alsharif & Jeong Kim & Jin Hong Kim, 2018. "Opportunities and Challenges of Solar and Wind Energy in South Korea: A Review," Sustainability, MDPI, vol. 10(6), pages 1-23, June.
    8. El Alimi, Souheil & Maatallah, Taher & Dahmouni, Anouar Wajdi & Ben Nasrallah, Sassi, 2012. "Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5466-5478.
    9. Jiang, Haiyan & Wang, Jianzhou & Wu, Jie & Geng, Wei, 2017. "Comparison of numerical methods and metaheuristic optimization algorithms for estimating parameters for wind energy potential assessment in low wind regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1199-1217.
    10. Arslan, Talha & Bulut, Y. Murat & Altın Yavuz, Arzu, 2014. "Comparative study of numerical methods for determining Weibull parameters for wind energy potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 820-825.
    11. 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.
    12. Aliashim Albani & Mohd Zamri Ibrahim, 2017. "Wind Energy Potential and Power Law Indexes Assessment for Selected Near-Coastal Sites in Malaysia," Energies, MDPI, vol. 10(3), pages 1-21, March.
    13. Oh, Ki-Yong & Nam, Woochul & Ryu, Moo Sung & Kim, Ji-Young & Epureanu, Bogdan I., 2018. "A review of foundations of offshore wind energy convertors: Current status and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 16-36.
    14. Sergei Kolesnik & Yossi Rabinovitz & Michael Byalsky & Asher Yahalom & Alon Kuperman, 2023. "Assessment of Wind Speed Statistics in Samaria Region and Potential Energy Production," Energies, MDPI, vol. 16(9), pages 1-35, May.
    15. Ali, Sajid & Lee, Sang-Moon & Jang, Choon-Man, 2018. "Statistical analysis of wind characteristics using Weibull and Rayleigh distributions in Deokjeok-do Island – Incheon, South Korea," Renewable Energy, Elsevier, vol. 123(C), pages 652-663.
    16. Akpınar, Adem, 2013. "Evaluation of wind energy potentiality at coastal locations along the north eastern coasts of Turkey," Energy, Elsevier, vol. 50(C), pages 395-405.
    17. Tosunoğlu, Fatih, 2018. "Accurate estimation of T year extreme wind speeds by considering different model selection criterions and different parameter estimation methods," Energy, Elsevier, vol. 162(C), pages 813-824.
    18. Liu, Xiaolei & Lin, Zi & Feng, Ziming, 2021. "Short-term offshore wind speed forecast by seasonal ARIMA - A comparison against GRU and LSTM," Energy, Elsevier, vol. 227(C).
    19. Wang, Jianzhou & Xiong, Shenghua, 2014. "A hybrid forecasting model based on outlier detection and fuzzy time series – A case study on Hainan wind farm of China," Energy, Elsevier, vol. 76(C), pages 526-541.
    20. Fazelpour, Farivar & Markarian, Elin & Soltani, Nima, 2017. "Wind energy potential and economic assessment of four locations in Sistan and Balouchestan province in Iran," Renewable Energy, Elsevier, vol. 109(C), pages 646-667.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:46:y:2012:i:1:p:555-563. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.