Two and three-parameter Weibull distribution in available wind power analysis


Two probability density functions are correlated to the wind measurements.

Two-parameter Weibull distribution is not always adequate to evaluate wind power.

Three-parameter Weibull distribution fits better the sets of wind velocity data.

Two-parameter Weibull distribution can give higher values of energy production.


Based on the current EU environmental policy, wind power industry has been growing fast in recent years. Knowledge of wind characteristics helps to define site requirements, choose a proper turbine design and estimate profits from the wind energy production.

The paper describes and compares the techniques of available wind energy evaluation using Weibull distributions: two-parameter Weibull probability distribution, and three-parameter Weibull distribution. The two-parameter Weibull distribution is recognized as an appropriate model and the most widely used in the wind industry sector. In some cases, in which the probability of null wind is significant, the Weibull distribution cannot reveal good conformity for the low wind speed. In theory, it seems that the three-parameter Weibull distribution, which takes into account the frequency of null winds, may better represent wind ranges for the low wind speed.

In the paper, the available wind energy is calculated for three different turbine locations. The results show that for the higher probability of the null wind the three-parameter Weibull distribution gives better results comparing to the two-parameter Weibull distribution and can be proposed as an alternative to wind energy estimation technique. Additional analyses confirm the observation.


  • Wind energy calculation;
  • Two-parameter Weibull distribution;
  • Three-parameter Weibull distribution;
  • Coefficient of determination;
  • Fit standard error;
  • Null wind speed

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