Wind resource is important part of the utilization of renewable energy. To effectivelyestimate the wind energy potential for a given area, a variety of probability density functions (pdf)have been available in literature. In this paper, the bimodal mixture Weibull function (WW) andthe probability function derived with maximum entropy principle (MEP) will be used and comparedwith the conventional Weibull function. Wind speed data measured at three wind farmsexperiencing different climatic environments in Taiwan are selected as sample data to test theirperformance. Judgment criterions include four kinds of statistical errors, i.e. the max error inKolmogorov-Smirnov test, Chi-square error, root mean square error and relative error of windpotential energy. The results show that the proposed WW and MEP pdfs describe wind characterizationsbetter than the conventional Weibull pdf, irrespective of wind speed and wind powerdensity data, particularly for a location where wind regime presents two humps on it. For windspeed distributions, the WW pdf describes best according to the Kolmogorov-Smirnov test;while for wind power density, the MEP pdf outperforms the others.