4.6 Article

New estimation method of wind power density with three-parameter Weibull distribution: A case on Central Inner Mongolia suburbs

Journal

WIND ENERGY
Volume 25, Issue 2, Pages 368-386

Publisher

WILEY
DOI: 10.1002/we.2677

Keywords

estimation method; incomplete gamma function; three-parameter Weibull distribution; wind energy; wind power density

Funding

  1. Natural Science Foundation of Inner Mongolia [2017MS0527, 2017MS0527-0390]
  2. Major Basic Research Open Project of Inner Mongolia Autonomous Region
  3. National Natural Science Foundation of China [51766014]

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This study accurately describes the characteristics of wind energy resources in suburbs using a new method of WPD estimation and the three-parameter Weibull distribution. Taking the month as the time scale can effectively capture the scattered and changing wind energy in suburbs.
Suburbs have the potential for future wind energy development because of their open terrain, good wind conditions, closeness to the city, wind power that can be absorbed in place, and other advantages. Therefore, accurately evaluating the wind energy resources in the suburbs is particularly important. The three-parameter Weibull distribution can accurately describe the wind speed in the suburbs, but research on the estimation of wind power density (WPD) with it is limited. On the basis of the mathematical models of wind speed probability distribution as Rayleigh, two-parameter Weibull, and three-parameter Weibull, a new WPD estimation formula with three-parameter Weibull distribution is derived using the partial integration method and by introducing incomplete gamma function to solve the transcendental integration. A field experiment platform is built, and the accuracy of the formula is verified by the measured data. The analysis of the measured data collected in recent 3 years in the suburbs of Hohhot, Inner Mongolia, concludes that the statistical characteristics of the measured wind speed and the distribution of wind energy resources are more conducive to capture the scattered and changing wind energy in the suburbs by taking the month as the time scale. Moreover, the three-parameter Weibull distribution estimated by the least square method can be used as the local wind speed model. The new method of WPD estimation can also reduce the calculation error by approximately 21.06%. This study provides an important reference for the subsequent analysis of wind power fluctuation characteristics and wind energy development planning.

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