摘要
Abstract
This paper proposes a modified method for multi-step forecasting of short-term load. Firstly, the BP neural network method is adopted to establish time-sharing and multi-step forecasting model of short-term load; then Kalman filter model is utilized to modify each initial forecast value to reduce the cumulative error of the model and improve multi-step forecasting. The calculation example result demonstrates that the pro-posed method can not only improve forecasting of single-step forecasting but effectively reduce multi-step forecasting errors;it is of operation significance for consecutive daily short-term load forecasting.关键词
卡尔曼滤波/短期负荷/多步预测/累积误差/BP神经网络Key words
Kalman filter/short-term load/multi-step forecasting/cumulative error/BP neural network分类
信息技术与安全科学
