周松林;茆美琴;苏建徽;

• 1:教育部光伏系统工程研究中心(合肥工业大学)

摘要(Abstract)：

提出了主成分分析与前馈神经网络相结合的风电功率预测模型。采用主成分分析法对原始多维输入变量进行预处理,选择输入变量的主成分作为神经网络的输入,既减少了输入变量的维数,又消除了各输入变量的相关性,从而简化了网络的结构,提高了网络收敛性和稳定性。仿真结果表明,相对于一般神经网络模型,基于主成分分析的神经网络模型预测精度更高、泛化性能更好。

关键词(KeyWords)： 风电功率预测;主成分分析;前馈神经网络;泛化性能

Abstract:

Keywords:

基金项目(Foundation): 国家重点基础研究发展计划项目(973项目)(2009CB219708)~~

作者(Author): 周松林;茆美琴;苏建徽;

Email:

DOI: 10.13335/j.1000-3673.pst.2011.09.004

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