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

中文关键词: K⁃L信息量  ARIMA  月度电量预测  误差修正

英文关键词: K⁃L information method  ARIMA  monthly electricity consumption forecast  error correction

中文摘要:

      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。

英文摘要:

      In order to consider the influence of multiple factors 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 indicators 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.