基于Nakagami分布的风速概率分布拟合研究

准确地拟合风速概率分布对估算潜在风场所蕴含的风能有着重要的作用。本文引入了二参数Nakagami分布对美国西部涵盖沿海、海岛和内陆的八个站点风速数据进行拟合，并对比瑞丽分布、伽马分布、威布尔分布、对数正态分布、广义极值分布以及Johnson SB分布，使用决定系数、均方根误差、误差平方和以及Kolmogorov-Smirnov四个拟合指标进行校验。Nakagami分布与参数较少的瑞丽分布、伽马分布、逻辑对数分布以及威布尔分布精度进行比较，Nakagami分布在八个站点的四个拟合指标均值中取得最优的拟合精度。与三参数的广义极值分布以及四参数Johnson SB分布进行拟合对比，Nakagami分布在四个站点获得最优精度。根据风速数据的统计结果，当站点的平均风速低于3m/s时，Nakagami比其它分布获得了更高的拟合精度。考虑Nakagami简便的计算以及较高的精度，Nakagami分布在拟合风速概率分布领域更具优势。

Study on fitting wind speed probability distribution based on Nakagami distribution

With the rapid development of wind energy, the accurate fitting of wind speed probability distribution plays an important role in estimating the wind energy in potential wind sites. In this study, the two parameters Nakagami distribution is introduced to fit the wind speed data of eight stations covering coastal, island and inland in the western United States, and the Rayleigh, Gamma, Weibull, Lognormal, Generalized extreme value and Johnson SB distribution are compared by using Coefficients of determination, Root mean square error, Sum of squares of errors and Kolmogorov-Smirnov. Nakagami was compared with lower parameters Rayleigh, Gamma distribution, lognormal and Weibull distributions. The goodness-of-fit of Nakagami obtained the optimal fitting precision. Compared with three parameters generalized extreme value and four parameters Johnson SB distribution, Nakagami obtained the optimal accuracy at four stations. According to the statistical results of wind speed, it was found that the average wind speed was lower than 3m/s, Nakagami obtained the highest fitting accuracy. Considering calculation and precision, Nakagami is more suitable for fitting wind speed probability distribution.