摘要
随着光伏电站的发展,光伏电站数据质量和数据处理问题对电站运行效率起到至关重要的作用。针对光伏电站数据采集系统采集数据的质量低,数据不完善等问题,构建了针对光伏电站数据采集系统的数据处理模型。通过分析异常数据类型,分别用判断域值和变量联合匹配的方法对其进行修正,然后处理缺失值,根据它们与不完全变量的关系,将缺失值分为随机和非随机两类。分别运用热卡填充法、多项式填补和均值填补等方法对缺失值进行填补,完成对光伏电站的数据处理,提高了光伏电站数据采集系统存储数据的质量和光伏电站数据的二次利用价值。
With the development of photovoltaic power station,the photovoltaic power station data quality and data processing problems play a crucial role for the efficiency of plant operation. Based on the weaknesses on low quality and incomplete data of current photovoltaic power station data acquisition system,this paper built the data processing model for the data acquisition system. By analysing the types of abnormal data,this model uses the method of judging threshold and variable joint matching to modify the abnormal data. After that,according to the relationship between missing value and imcomplete variable,this model divides the missing value into random and nonrandom,then using hotdecking method,polynomial filling method and mean filling method respectivel to fill up the missing values,in order to improve the quality of the photovoltaic power station data acquisition system and secondary utilization value of the PV data.
出处
《电器与能效管理技术》
2016年第6期8-13,共6页
Electrical & Energy Management Technology
基金
青海省光伏发电并网技术重点实验室建设专项资助(2014-Z-Y34A)
关键词
光伏电站
变量联合匹配
热卡填充法
多项式填补
均值填补
PV power station
variable joint matching
calorie filling method
polynomial filling method
mean filling method
