论文部分内容阅读
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 plants, the data quality and data processing of photovoltaic power plants play a crucial role in the operation efficiency of power plants. Aiming at the problems of low quality and incomplete data collected by the data acquisition system of photovoltaic power station, a data processing model for the data acquisition system of photovoltaic power station was constructed. By analyzing the types of anomalous data, they are respectively modified by joint domain judgment and variable matching, and then the missing values are processed. According to their relationship with incomplete variables, the missing values are divided into two categories: random and non-random. Fill the missing value with the methods of hot card filling, polynomial filling and mean filling, respectively, to complete the data processing of the photovoltaic power station and improve the quality of the data stored in the data acquisition system of the photovoltaic power station and the secondary utilization value of the photovoltaic power plant data.