张金良;谭忠富;

• 1:华北电力大学经济与管理学院

摘要(Abstract)：

为提高短期电力负荷的预测精度,提出一种基于经验模态分解、计量经济学模型和神经网络混沌模型的组合预测方法。首先,利用经验模态分解将负荷序列分解成一系列本征模态函数及余项;其次,针对不同分量的特性,建立不同的模型进行预测;最后,将所有分量的预测值求和作为最终的预测结果。以美国宾夕法尼亚州–新泽西州–马里兰州(Pennsylvania-New Jersey-Maryland,PJM)电力市场为实例,验证了普通日负荷和特殊日负荷的预测效果,此外,将该方法与其他预测方法进行了比较,算例表明,该方法具有较高的预测精度。

关键词(KeyWords)： 负荷预测;经验模态分解;计量经济学模型;神经网络混沌模型

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(70971038);; 高等学校博士学科点专项科研基金资助项目(20070079005)~~

作者(Author): 张金良;谭忠富;

Email:

DOI: 10.13335/j.1000-3673.pst.2011.09.034

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