基于风预测和小波包的储能控制策略

E. Solomin, Liu Liu, Ma Li, Pronay Kumar Paul
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引用次数: 0

摘要

可再生能源,特别是风能是间歇性和波动的。风电直接并网对电力系统的稳定性、电网频率和电能质量的控制提出了很大的挑战。虽然使用几种方法可以有一定的概率预测风的外观,但为了最终用户的安全,必须控制原始输出功率。本文采用小波包分解对原始/输入风电进行分解,直到目标并网功率满足设定要求并停止分解。该方法首次采用了人工神经网络方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy Storage Control Strategy Based on Wind Prediction and Wavelet Packet
Renewable energy and in particular the Wind power is intermittent and fluctuating. Direct grid-connected wind power poses great challenges to the stability of the power system, as well as the control of grid frequency and power quality. Although the wind appearance could be predicted with some probability using the bunch of several approaches, for the safety of the end user, the original output power must be controlled. In this paper, the wavelet packet decomposition is used to decompose the original/input wind power until the target grid-connected power meets the set requirements and stops decomposing. For the first time the approach uses the Artificial neural network approach.
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