摘要
光伏发电出力中的高比例异常数据具有相互重叠、多高斯分布的特点,如何精确地剔除光伏发电出力中的高比例异常数据是实现光伏功率精确预测的关键问题。文章分析了光伏发电出力中高比例异常数据的特点,并研究了一种基于高斯混合模型的光伏发电出力高比例异常数据检测方法。建立了高斯混合模型的算法模型,使用期望极大算法(Expectation Maximization,EM)对高斯混合模型的参数进行估计,使用算法模型对光伏发电出力中的高比例异常数据进行检测和剔除。实际算例分析和对比实验表明,文章的方法可以对多分类的高比例异常数据进行精确地检测,较传统的异常数据检测方法更加适用于光伏发电出力的高比例异常数据检测。
The high proportion of outliers in photovoltaic power output data has the characteristics of mutual overlap and multi-Gaussian distribution.How to accurately eliminate the high proportion of outliers from photovoltaic power output data is a crucial problem for realizing precise photovoltaic power forecast.This paper analyzes the characteristics of high proportion of outliers in photovoltaic power output data,and studies a high proportion of outlier detection method in photovoltaic power output data based on Gaussian mixture model.Firstly,the algorithm model of Gaussian mixture model is established,and then,the expectation maximization(EM)algorithm is used to estimate parameters of the Gaussian mixture model.Finally,the proposed algorithm is used to detect and eliminate the high proportion of outliers in the photovoltaic power output data.Experiments and comparative studies show that the proposed method is more suitable for high proportion of outlier detection in photovoltaic power output than the classical outlier data detection method.
作者
刘岩
李文文
周丽霞
魏彤珈
周辛南
杨磊
Liu Yan;Li Wenwen;Zhou Lixia;Wei Tongjia;Zhou Xinnan;Yang Lei(Metrology Center,State Grid Jibei Electric Power Company Limited,Beijing 100045,China;Marketing Department,State Grid Jibei Electric Power Company Limited,Beijing 100045,China;Qinhuangdao Power Supply Company,State Grid Jibei Electric Power Company Limited,Qinhuangdao 066000,Hebei,China)
出处
《电测与仪表》
北大核心
2021年第9期14-21,共8页
Electrical Measurement & Instrumentation
基金
国网电力公司科技项目(52010119000R)。
关键词
光伏发电出力
故障异常数据
高斯混合模型
EM算法
photovoltaic power output
high proportion of outliers
Gaussian mixture model
EM algorithm
