风电功率波动特性的概率分布研究

波动性是风电功率的固有特性,如何定量地描述风电功率的波动性尚缺乏有效方法。基于大量实测数据的分析,发现可以采用带移位因子与伸缩系数的t分布(t location-scale)描述风电功率波动特性的概率分布。分析表明:风电功率的min级分量约占风电场装机容量的2%~5%;多个风电场输出叠加在一起后可以有效减小min级分量的比例;风机类型对风电波动特性的影响很小,而风电场当前风电出力则对风电波动特性几乎无影响。带移位因子与伸缩系数的t分布还适合于描述风电场相邻时间间隔平均功率变化的概率分布,时间间隔加长后,由于风速相关性减弱,相邻时段平均功率的波动特性增强。

Probability Density Function of Wind Power Variations

Variations is an intrinsic property of wind power,but few common methods are reported that quantificationally define the variations.Based on the field measurement,it’s found that t location-scale distribution is suitable to identify the probability distribution of wind power variations.Analysis shows that the minute-scale wind power is about 2% to 5% of the installed capacity.Summation of the outputs from different wind farms regional apart could effectively decrease the percentage of minute-scale wind power.The types of wind farms have a little influence on the percentage of minute-scale wind power,and the influence of the present total output is negligible.The t location-scale distribution is also capable to describe the probability distribution of variations of average wind power of adjacent time intervals.As the length of average time interval increases,the variations increase due to the decrease of the correlation between wind velocities.