风速预报中的小波预滤波

D. L. Faria, R. Castro, C. Philippart, A. Gusmão
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引用次数: 24

摘要

风力发电是发展最快的可再生能源技术,正在成为能源结构的重要组成部分。电力系统的安全可靠运行意味着需要提前对将要产生的能源进行调度,从而使电力系统达到平衡。因此,风力发电的使用和重要性严格取决于提前预测风力的能力。本文采用ARMA模式对风速进行中期预报。此外,还研究了用小波对风速时间序列进行预滤波的优点。进行了一些模拟,目的是评估ARMA模型与参考模型的性能,并研究小波预滤波技术是否能改善预测结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wavelets pre-filtering in wind speed prediction
Wind power is the fastest growing renewable energy technology and is becoming a significant component of the energy mix. The secure and reliable operation of the power system implies the need for scheduling in advance the energy sources that will produce, so that the power system is balanced. Therefore, the use and importance of the wind power is strictly dependent on the ability to predict the wind in advance. In this paper, ARMA models are used to forecast the wind speed in terms of a medium-term prediction. Furthermore, an investigation on the benefits of pre-filtering the wind speed time series using wavelets is carried out. Some simulations are done with the twofold purpose of evaluating the performance of ARMA models as compared with reference models and investigating whether the wavelet pre-filtering technique leads to an improvement of the forecast results.
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