基于最小二乘支持向量机的风电场短期风速预测Short-Term Wind Speed Forecasting of Wind Farm Based on Least Square-Support Vector Machine
杜颖;卢继平;李青;邓颖玲;
摘要(Abstract):
提出了一种基于最小二乘支持向量机的风电场风速预测方法。以历史风速数据、气压、温度作为输入,对风速和环境条件进行训练,建立预测模型,并且运用网格搜索法确定模型参数。算例结果表明,使用上述方法预测的风速与真实值基本一致。将本文提出方法与BP(back propagation)神经网络法的预测结果进行对比,表明前者具有更高的精度和更强的鲁棒性,因此是一种比较有价值的风速预测方法。
关键词(KeyWords): 风力发电;风速预测;最小二乘支持向量机(LS-SVM);网格搜索;BP神经网络
基金项目(Foundation): 国家重点基础研究发展计划项目(973项目)(2004CB217908)。~~
作者(Author): 杜颖;卢继平;李青;邓颖玲;
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DOI:
参考文献(References):
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