基于增量SVD的风力发电研究

C. Kamath, Y. Fan
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引用次数: 0

摘要

本文将风力发电预测问题表述为流数据分析问题之一。我们想知道是否有可能使用当前时间之前的时间窗口中的天气数据来深入了解当前时间之后的时间间隔内风力发电的行为。具体来说,我们使用了对天气数据的奇异值分解,以及如何利用奇异值的个数和最大的奇异值来预测在不久的将来产生的变化幅度。该分析使用基于滑动窗口的增量算法来减少计算成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Incremental SVD for Insight into Wind Generation
In this paper, we formulate the problem of predicting wind generation as one of streaming data analysis. We want to understand if it is possible to use the weather data in a time window just before the current time to gain insight into how the wind generation might behave in a time interval just after the current time. Specifically, we use a singular value decomposition of the weather data, and how that the number of singular values and the largest singular value can be used to predict the magnitude of the change in the generation in the near future. The analysis uses an incremental algorithm based on a sliding window for reduced computational costs.
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