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Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function

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  • Shu, Z.R.
  • Li, Q.S.
  • Chan, P.W.

Abstract

It has been globally recognized that the harvesting of renewable energy is of considerable importance for the achievement of sustainable development. As for Hong Kong, one of the most densely populated cities, the shortage of indigenous fossil sources has inevitably resulted in excessive dependence on external energy sources. Nevertheless, in consideration of the reduction of fossil fuel reserves, as well as the impact on the environment of fossil fuel uses, the exploration of usable renewable energy sources becomes increasingly important for Hong Kong‘s long-term development. Based on 6-year wind observations from three meteorological stations at three islands in Hong Kong, this study provides a statistical assessment of the wind characteristics and wind energy potential at offshore locations surrounding Hong Kong. The Weibull distribution function was applied to estimate the Weibull parameters which can be used to facilitate the evaluation of offshore wind energy potential. The variation of the mean wind speed, the Weibull parameters and the wind power density were established under various timescales. Significant yearly, seasonal and monthly variations of the Weibull parameters were observed, while the diurnal variation was relatively small. The veracity of the Weibull distribution model to represent offshore wind data was examined, and it was shown that the Weibull model gave an adequate description of the frequencies of actual wind data. Finally, the total wind power capacities at the three potential offshore wind farm locations were derived, which indicated that the Southeastern waters are the most promising locations for offshore wind farm development in Hong Kong.

Suggested Citation

  • Shu, Z.R. & Li, Q.S. & Chan, P.W., 2015. "Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function," Applied Energy, Elsevier, vol. 156(C), pages 362-373.
    • Handle: RePEc:eee:appene:v:156:y:2015:i:c:p:362-373
    DOI: 10.1016/j.apenergy.2015.07.027
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    References listed on IDEAS

    as
    1. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2014. "Study on offshore wind power potential and wind farm optimization in Hong Kong," Applied Energy, Elsevier, vol. 130(C), pages 519-531.
    2. Jamil, M. & Parsa, S. & Majidi, M., 1995. "Wind power statistics and an evaluation of wind energy density," Renewable Energy, Elsevier, vol. 6(5), pages 623-628.
    3. Zhou, Wei & Yang, Hongxing & Fang, Zhaohong, 2006. "Wind power potential and characteristic analysis of the Pearl River Delta region, China," Renewable Energy, Elsevier, vol. 31(6), pages 739-753.
    4. Lu, Lin & Yang, Hongxing & Burnett, John, 2002. "Investigation on wind power potential on Hong Kong islands—an analysis of wind power and wind turbine characteristics," Renewable Energy, Elsevier, vol. 27(1), pages 1-12.
    5. Waewsak, Jompob & Landry, Mathieu & Gagnon, Yves, 2015. "Offshore wind power potential of the Gulf of Thailand," Renewable Energy, Elsevier, vol. 81(C), pages 609-626.
    6. Chang, Tian Pau, 2011. "Performance comparison of six numerical methods in estimating Weibull parameters for wind energy application," Applied Energy, Elsevier, vol. 88(1), pages 272-282, January.
    7. Bilgili, Mehmet & Yasar, Abdulkadir & Simsek, Erdogan, 2011. "Offshore wind power development in Europe and its comparison with onshore counterpart," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 905-915, February.
    8. Mathew, Sathyajith & Pandey, K.P. & Kumar.V, Anil, 2002. "Analysis of wind regimes for energy estimation," Renewable Energy, Elsevier, vol. 25(3), pages 381-399.
    9. Li, G, 2000. "Feasibility of large scale offshore wind power for Hong Kong — a preliminary study," Renewable Energy, Elsevier, vol. 21(3), pages 387-402.
    10. Lun, Isaac Y.F & Lam, Joseph C, 2000. "A study of Weibull parameters using long-term wind observations," Renewable Energy, Elsevier, vol. 20(2), pages 145-153.
    11. Esteban, M. Dolores & Diez, J. Javier & López, Jose S. & Negro, Vicente, 2011. "Why offshore wind energy?," Renewable Energy, Elsevier, vol. 36(2), pages 444-450.
    12. Lee, Myung Eun & Kim, Gunwoo & Jeong, Shin-Taek & Ko, Dong Hui & Kang, Keum Seok, 2013. "Assessment of offshore wind energy at Younggwang in Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 131-141.
    13. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    14. Pishgar-Komleh, S.H. & Keyhani, A. & Sefeedpari, P., 2015. "Wind speed and power density analysis based on Weibull and Rayleigh distributions (a case study: Firouzkooh county of Iran)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 313-322.
    15. Weisser, D, 2003. "A wind energy analysis of Grenada: an estimation using the ‘Weibull’ density function," Renewable Energy, Elsevier, vol. 28(11), pages 1803-1812.
    16. Hong, Lixuan & Möller, Bernd, 2012. "Feasibility study of China’s offshore wind target by 2020," Energy, Elsevier, vol. 48(1), pages 268-277.
    17. Sun, Xiaojing & Huang, Diangui & Wu, Guoqing, 2012. "The current state of offshore wind energy technology development," Energy, Elsevier, vol. 41(1), pages 298-312.
    18. Fang, Hsin-Fa, 2014. "Wind energy potential assessment for the offshore areas of Taiwan west coast and Penghu Archipelago," Renewable Energy, Elsevier, vol. 67(C), pages 237-241.
    19. Esteban, Miguel & Leary, David, 2012. "Current developments and future prospects of offshore wind and ocean energy," Applied Energy, Elsevier, vol. 90(1), pages 128-136.
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