风速概率分布特性研究是风电场风能资源评估的基础,其结果将对风功率密度分布的估算产生影响。该文以最大熵原理的风速概率分布模型为基础,通过引入修正因子重新构造最大熵分布模型,并运用改进最大熵分布模型和两参数威布尔分布模型对风电场风速及风功率密度分布进行拟合,以判定系数和均方根误差两个指标来衡量该改进模型的适用性。研究结果表明,改进最大熵分布法与实测风速的分布更加匹配;而对风功率密度分布的拟合,虽然修正因子的不同指数值所对应的分布模型的拟合有一定起伏,但总存在某个值,其对应模型的拟合效果良好,由此可见,改进型最大熵分布可以适用于不同的风速与风功率密度分布状况,适合应用于风电场风能资源分布特性的研究以及区域风能资源的评估。
Wind speed probability distribution is one of the important characteristics which can further influence the estimation of power density in wind farm resources evaluation. A novel model based on an improved maximum entropy principle (MEP) approach was developed by introducing a correction factor. In addition, the coefficient of determination (COD) and root mean square error (RMSE) were used to evaluate the availability of the proposed approach. MEP based distribution model and bi-parameter Weibull distribution model were employed to investigate wind speed distribution and power density distribution characteristics in wind farm. Compared with traditional Weibull distribution, the improved MEP method shows better fitting with the measured wind speed data. Although the fitting of the wind power density distribution varies with the change of exponential value of correction factor, a proper value can be found to fit a good result. It can be seen that the proposed MEP model is a suitable option for carrying out wind energy resource assessment in local and regional wind farms with variety of characteristics in wind speed and wind power density distribution.