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基于ARIMA算法和小波分析+BP神经网络算法的短期负荷预测

于 2020-11-30 发布
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我们用了两种算法对PJM某区电力负荷进行超短期预测。ARIMA算法预测速度较快,平均误差在3%以内,特别适合这种超短期负荷预测,而小波分析+BP神经网络算法是一种适应性比较广的算法,在此次超短期负荷预测中它的平均误差在7%以内,预测时间相对更长。此程序由华北电力大学电力专业学生编写,采用了VB、MATLAB混合编程(VB的界面,MATLAB的内核),利用了2种算法实现电力负荷超短期预测,这2种方法都是当前较先进实用的算法,十分有启发性。

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