刘岩,李文文,周丽霞,魏彤珈,周辛南,杨磊.基于高斯混合模型的光伏发电出力中高比例异常数据检测方法研究[J].电测与仪表,2021,58(9):14-21. Liu Yan,Li Wenwen,Zhou Lixi,Wei Tongjia,Zhou Xinnan,Yang Lei.Research of High Proportion of Outliers Detection in Photovoltaic Power Data based on Gaussian Mixture Model[J].Electrical Measurement & Instrumentation,2021,58(9):14-21.
基于高斯混合模型的光伏发电出力中高比例异常数据检测方法研究
Research of High Proportion of Outliers Detection in Photovoltaic Power Data based on Gaussian Mixture Model
The high proportion of outliers in photovoltaic power data has the characteristics of mutual overlap and multi-Gaussian distribution. How to accurately eliminate the high proportion of outliers from photovoltaic power data is a crucial problem for realizing precise photovoltaic power forecast. This paper analyzes the characteristics of high proportion of outliers in photovoltaic power data, and studies a high proportion of outlier detection method in photovoltaic power data based on Gaussian mixture model. Firstly, the algorithm model of Gaussian mixture model is established, and then the EM algorithm is used to estimate parameters of the Gaussian mixture model. At last, the proposed algorithm is used to detect and eliminate the high proportion of outliers in the photovoltaic power data. Experiments and comparative studies show that the proposed method is more suitable for high proportion of outlier detection in photovoltaic power than the classical outlier data detection method.
