乔颖;鲁宗相;闵勇;

• 1:电力系统及发电设备控制和仿真国家重点实验室(清华大学电机系)

摘要(Abstract)：

风电功率预测技术既是交叉应用学科,又是众多学科的共性基础性学科。目前国际最先进水平的风电预测误差甚至低于3%,我国还处于追赶期。从发展趋势来看,当前数据积累带来的精度提升效果日渐式微,数值天气预报短期内出现突破不可预期。风功率预测在未来一段时间内仍需要有限的天气预报水平下提高各环节的预报技巧,筛选和组合预测方法,争取误差学习曲线最末端2%~3%。若干实践表明,综合应用多项精细化预测技术,可显著提高原有水平较差的风场精度。这些技术包括优化数值天气预报参数化方案、提高功率转换环节精度与自适应能力、采用复合数据源的组合法、考虑空间相关性的非线性误差修正等。

关键词(KeyWords)： 风功率预测;数值天气预报;物理法;统计法;精度提升

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划(2016YFB0900100);; 国家自然科学基金重大项目(51190101)~~

作者(Author): 乔颖;鲁宗相;闵勇;

Email:

DOI: 10.13335/j.1000-3673.pst.2017.1581

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