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Assessment of wind characteristics and wind turbine characteristics in Taiwan

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  • Chang, Tsang-Jung
  • Wu, Yu-Ting
  • Hsu, Hua-Yi
  • Chu, Chia-Ren
  • Liao, Chun-Min

Abstract

Wind characteristics and wind turbine characteristics in Taiwan have been thoughtfully analyzed based on a long-term measured data source (1961–1999) of hourly mean wind speed at 25 meteorological stations across Taiwan. A two-stage procedure for estimating wind resource is proposed. The yearly wind speed distribution and wind power density for the entire Taiwan is firstly evaluated to provide annually spatial mean information of wind energy potential. A mathematical formulation using a two-parameter Weibull wind speed distribution is further established to estimate the wind energy generated by an ideal turbine and the monthly actual wind energy generated by a wind turbine operated at cubic relation of power between cut-in and rated wind speed and constant power between rated and cut-out wind speed. Three types of wind turbine characteristics (the availability factor, the capacity factor and the wind turbine efficiency) are emphasized. The monthly wind characteristics and monthly wind turbine characteristics for four meteorological stations with high winds are investigated and compared with each other as well. The results show the general availability of wind energy potential across Taiwan.

Suggested Citation

  • Chang, Tsang-Jung & Wu, Yu-Ting & Hsu, Hua-Yi & Chu, Chia-Ren & Liao, Chun-Min, 2003. "Assessment of wind characteristics and wind turbine characteristics in Taiwan," Renewable Energy, Elsevier, vol. 28(6), pages 851-871.
  • Handle: RePEc:eee:renene:v:28:y:2003:i:6:p:851-871
    DOI: 10.1016/S0960-1481(02)00184-2
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    References listed on IDEAS

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    1. 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.
    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. Alven H.S. Lam, 2000. "Republic of China (Taiwan)," American Journal of Economics and Sociology, Wiley Blackwell, vol. 59(5), pages 327-336, November.
    4. 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.
    5. Ackermann, Thomas & Söder, Lennart, 2002. "An overview of wind energy-status 2002," Renewable and Sustainable Energy Reviews, Elsevier, vol. 6(1-2), pages 67-127.
    6. 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.
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