摘要
为解决在风资源评估阶段,数据插补应用条件及插补结果偏差难以量化、插补算法难以选择等相关问题,通过大量数据模拟实际缺失情况,采用插补方法将数据补全,利用均方误差(MSE)、威布尔分布k值、平均风速、风功率密度、风电机组发电量5个评价指标构建指标体系,与真实数据进行了对比及偏差分析,在此基础上得出了数据插补应用的相关系数水平,并推荐了最优的测风月份及最优的测风数据插补算法。
In the wind resource evaluation,the use of data interpolation has problems such as difficulty in quantifying application conditions,deviation of interpolation results,and difficulty in selecting interpolation algorithms.In this paper,a large amount of data is used to simulate the actual missing situation,and the data is completed by using an imputation method.The index system was constructed using mean square error(MSE),Weibull distribution k value,average wind speed,wind power density,power generation of wind turbine,et al.Based on the deviation analysis compared with the real data,the correlation coefficient level of the data interpolation application is obtained,and the best wind measurement month and the best interpolation method of wind measurement data are recommended.
作者
于佳鹤
崔杰
王风涛
Yu Jiahe;Cui Jie;Wang Fengtao(Beijing Goldwind Science&Creation Windpower Equipment Co.,Ltd.,Beijing 100176,China)
出处
《太阳能》
2021年第2期26-35,共10页
Solar Energy
