基于K-L信息量和ARIMA误差修正的月度电量预测  

Monthly electricity forecasting based on K⁃L information and ARIMA error correction

作　　者：陈明帆 宁光涛 李琳玮 何礼鹏 刘丽新 CHEN Mingfan;NING Guangtao;LI Linwei;HE Lipeng;LIU Lixin(Hainan Power Grid Co.,Ltd.,Haikou 570204,China;Beijing Tsingsoft Technology Co.,Ltd.,Beijing 100085,China)

机构地区：[1]海南电网有限公司,海口570204 [2]北京清软创新科技股份有限公司,北京100085

出　　处：《电力需求侧管理》2021年第2期43-46,共4页Power Demand Side Management

基　　金：海南电网有限责任公司科技项目(070000KK52160001)。

摘　　要：为考虑多因素对电量的影响及提高月电量预测准确率,提出基于K-L信息量法和ARIMA误差修正的月度电量预测方法。在筛选相关性强的指标基础上,利用相关分析法对影响指标与电量进行回归建模,计算拟合误差并构建新的非平稳时间序列,结合ARIMA模型对此序列进行修正,进而获得准度性更佳的月度电量预测值,具有较高的应用价值。In order to consider the influence of multiple fac⁃tors on electricity and improve the accuracy of monthly electricity forecasting.A monthly electricity forecasting method is proposed based on the K⁃L information method and ARIMA error correction.Based on screening relevant indicators,the correlation analysis method is used to make regression modeling on the influence indi⁃cators and electricity,calculate of fitting errors,and construct a new non⁃stationary time series,combined with the ARIMA model to modify this series.Monthly electricity predictions obtained with better accuracy,have higher application value.

关 键 词：K-L信息量 ARIMA 月度电量预测 误差修正 

分 类 号：TM71[电气工程—电力系统及自动化] TM93