丁明;缪乐颖;车建峰;毕锐;张超;王勃;

• 1:安徽省新能源利用与节能重点实验室(合肥工业大学)
• 2:新能源与储能运行控制国家重点实验室(中国电力科学研究院有限公司)

摘要(Abstract)：

提出了一种基于波动过程匹配技术的风电功率短期预测的方案。利用希尔伯特-黄变换对风电功率波动进行频谱分析,将各个固有模态分量重构成随机性强的高频分量和反映波动趋势的低频分量,并确定了分频预测方案。对低频分量进行波动过程识别并建立特征参数库,利用各类风速波动过程与风电功率波动过程的匹配关系进行预测和修正;对高频分量利用多年历史数据进行BP神经网络预测,并与低频分量预测结果叠加。综合预测结果的均方根误差在13%左右,较传统方法有显著改善。

关键词(KeyWords)： 风电功率预测;希尔伯特-黄变换;波动过程;分频预测;匹配技术

Abstract:

Keywords:

基金项目(Foundation): 国家电网公司科技项目“基于广域时空大数据分析的风电功率预测方法研究与应用”;; 可再生能源与工业节能安徽省工程实验室开放课题资助(45000-411104/012)~~

作者(Author): 丁明;缪乐颖;车建峰;毕锐;张超;王勃;

Email:

DOI: 10.13335/j.1000-3673.pst.2018.0456

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