是否有一种可靠的方法来识别具有负相关风的区域?-地江南体育网页版球科学堆栈交换江南电子竞技平台 最近30个来自www.hoelymoley.com 2023 - 04 - 06 - t16:03:42z //www.hoelymoley.com/feeds/question/2234 https://creativecommons.org/licenses/by-sa/4.0/rdf //www.hoelymoley.com/q/2234 9 是否有一种可靠的方法来识别具有负相关风的区域? 410年不见了 //www.hoelymoley.com/users/100 2014 - 07 - 07 - t07:31:20z 2014 - 07 - 07 - t14:35:44z 当研究大规模电网的潜力时,当确定生产清洁电力的最低成本方式时,一个反复出现的主题是将风力发电扩展到足够宽的区域,使其均匀。< / p >

One way to bring down costs a lot, is to combine on the same grid, regions where the wind over a period of weeks to years, are negatively correlated: that is to say, it helps if we can easily identify pairs of regions where low winds in one region tend to happen at the same time as high winds in the other.

At a scale of days, sufficiently distant regions are uncorrelated. At a scale of weeks to years, a set of correlations of reanalysis data (e.g. ECMWF or CFSR) suggests that there are pairs of regions which do exhibit negatively correlated wind, either seasonally or annually.

Is there a reliable way to identify such combinations of regions?

//www.hoelymoley.com/questions/2234/-/2239#2239 6 是否有可靠的方法来识别具有负相关风的区域? arkaia //www.hoelymoley.com/users/111 2014 - 07 - 07 - t14:35:44z 2014 - 07 - 07 - t14:35:44z 我的建议是对风数据进行主成分分析(PCA)或经验正交函数(EOF)分析。分析的结果将是一组可变性的模态。你要寻找的是模态,它显示的区域大小很大,但相位不一致。对于时间尺度,你需要检查分析的特征向量和特征值来确定时间变化的尺度。

你可以在很多地方找到合适的代码,例如here.

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