电测与仪表2017，Vol.54Issue(3)：31-34,41,5.
基于组合优化LOWESS的电能量数据缺失处理方法
Missing electricity data processing method based on combined optimization LOWESS
陈俊 1龙东 1杨舟 1韦杏秋1
作者信息
- 1. 广西电网有限责任公司电力科学研究院,南宁530023
- 折叠
摘要
Abstract
According to the statistical distribution characteristics of the actual electric energy data, and considering the treatment effect of mean substitution method on energy loss data is usually not satisfactory, the estimation error of LOWESS model is limited by its given window width and fitting order, a LOWESS regression model of the electric energy data deletion optimization based on prediction error minimization parameters automatic processing method is proposed in this paper.By comparing the fixed window and order number in the non-stationarity of the electric energy data on the prediction effect and study the accuracy, adaptability and comparative advantage of parameters optimiza-tion LOWESS model.Through the actual data validation, the model can adapt to different data distribution of electric energy data, different loss ratio and so on, and the prediction accuracy is high, which has certain practical reference value.关键词
缺失数据处理/电力计量/LOWESS回归/组合优化Key words
missing electricity data/electric energy metering/LOWESS regression/combinatorial optimization分类
信息技术与安全科学引用本文复制引用
陈俊,龙东,杨舟,韦杏秋..基于组合优化LOWESS的电能量数据缺失处理方法[J].电测与仪表,2017,54(3):31-34,41,5.
