吴兴华;周晖;

• 1:北京交通大学电气工程学院
• 2:北京交通大学电气工程学院 北京市海淀区100044
• 3:北京市海淀区100044

摘要(Abstract)：

提出了基于Takagi-Sugeno模型的自适应模糊神经网络的短期电价预测方法。首先采用减法聚类方法确定自适应模糊神经网络的结构,然后利用混合学习算法训练该网络的前件参数和结论参数,最后将影响未来日电价的相关因素输入到训练好的自适应模糊神经网络中进行电价预测。以美国加州电力市场公布的1999年负荷与电价数据进行模型训练和预测,结果表明采用该方法所建立的预测模型具有较高的预测精度。

关键词(KeyWords)： 电力市场;短期电价预测;减法聚类;自适应模糊神经网络

Abstract:

Keywords:

基金项目(Foundation):

作者(Author): 吴兴华;周晖;

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DOI:

参考文献(References)：

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