摘要
短期电力负荷预测是电力系统运行调度中一项非常重要的内容。目前,大量统计数据表明,短期负荷预测精度不高,预测方法的"数学化"程度不断加深,导致预测方法实用性也不高。针对正常日负荷特点,提出利用二阶自适应系数法和移动样本倒指数法的预测误差互补特性建立组合预测模型。并利用实际负荷对改进方法进行验证分析,证明短期负荷预测的改进能有效提高预测精度,方法易于实现,计算速度快,有很好的实践价值。
Short-term load forecasting is one of the most important contents running and dispatching pow- er system.At present, unsatisfied prediction precision and mathematization of methods are two important problems in the short-term load forecasting. This led to the practicality of the pre- diction method is not high. For the normal day load, proposes the combination forecasting method of second order self-adaptive method and inverted index model. And uses the actual load check and analyses the improvement method. This proves that the improvement of short- term load forecasting can improve the prediction accuracy, the method is easy to implement, computing speed is fast and has good practical value.
出处
《现代计算机》
2013年第16期10-14,共5页
Modern Computer
关键词
短期负荷预测
二阶自适应系数法
移动样本倒指数法
组合预测
Short-Term Load Forecasting
Second Order Self-Adaptive Method
Inverted Index Model
Combination Forecasting Method
