A review of Weibull functions in wind sector

The accurate assessment of the potential wind energy at a define site is very important from economic point of view, measures cost effectiveness of the project and helps estimating future incomes, revenues. Knowledge of wind characteristics also facilitates a proper turbine design selection. There are different techniques for wind energy evaluation. The direct wind speed measurement is the most accurate method to determine wind conditions, but often the different wind speed frequency distributions are proposed. One of the most widely used distribution is 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 does not 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 with high percentages of null wind speeds and may give better results. In the paper, the review of the literature is carried out on the application of two and three-parameter Weibull distribution in wind energy analyses and also focuses on the comparison of results received from different probability density functions, used in cited papers, with the frequency of 0–2m/s wind speed range in real data. For higher percentages of null wind speeds or the wind speed below 2m/s, the three-parameter Weibull model should have the advantage in relation to two-parameter Weibull distribution, gives more appropriate results and can be proposed as an alternative to wind energy estimation technique.