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基于时频分析的改进小波包风电功率波动平抑方法
引用本文:齐先军,郑夕炜,王晓蓉,韩平平.基于时频分析的改进小波包风电功率波动平抑方法[J].太阳能学报,2022,43(7):302-309.
作者姓名:齐先军  郑夕炜  王晓蓉  韩平平
作者单位:1.新能源利用与节能安徽省重点实验室(合肥工业大学),合肥 230009; 2.新能源与储能运行控制国家重点实验室(中国电力科学研究院有限公司),北京 100192
基金项目:新能源与储能运行控制国家重点实验室开放基金(NYB51201901203);;中央高校基本科研业务费专项资金(PA2020GDSK0099);
摘    要:针对传统小波包风电波动平抑方法存在的过度平抑问题,提出一种基于时频分析的改进小波包平抑方法。首先,找出功率最大变化范围超过波动标准的时刻对集合,利用小波包对风电功率进行小波分解得到各频段分量;然后,从高频到低频依次对各频段分量在时刻对集合上进行局部削峰填谷,直到风电功率满足波动标准,从而得到平抑后的风电并网功率和储能功率指令;最后,对波动平抑效果进行评价。算例仿真表明该方法在满足风电波动标准的基础上,减小了储能功率指令的累积功率和充放电切换次数,有利于降低储能配置成本、延长储能寿命。

关 键 词:风电功率  储能  小波分解  时频分析  小波包  波动平抑  
收稿时间:2020-11-17

IMPROVED WAVELET PACKET METHOD OF SMOOTHING WIND POWER FLUCTUATIONS BASED ON TIME-FREQUENCY ANALYSIS
Qi Xianjun,Zheng Xiwei,Wang Xiaorong,Han Pingping.IMPROVED WAVELET PACKET METHOD OF SMOOTHING WIND POWER FLUCTUATIONS BASED ON TIME-FREQUENCY ANALYSIS[J].Acta Energiae Solaris Sinica,2022,43(7):302-309.
Authors:Qi Xianjun  Zheng Xiwei  Wang Xiaorong  Han Pingping
Affiliation:1. Anhui Province Key Laboratory of Renewable Energy Utilization and Energy Saving(Hefei University of Technology), Hefei 230009, China; 2. State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems(China Electric Power Research Institute), Beijing 100192, China
Abstract:Aiming at excessive smoothing in the traditional wavelet packet method to smooth wind power fluctuations, an improved wavelet packet smoothing method based on time-frequency analysis is proposed. Firstly, the set of time pairs when the maximum power-fluctuation range exceeds the fluctuation standard is found out; and the wavelet decomposition based on wavelet packet is performed on wind power to obtain its components in each frequency band. Secondly, starting from the highest frequency component, the local peak-shaving and valley-filling of the components are performed only at these time pairs until the fluctuation standard is satisfied, and thus the grid-connected wind power and energy storage power command are obtained. Finally, the effect of smoothing is evaluated. Results of the case study show that this method can reduce the cumulative power and the charging-discharging switching times of energy storage power command, thus helping reduce the cost of energy storage configuration and prolong the life of energy storage while meeting the standards of wind power fluctuations.
Keywords:wind power  energy storage  wavelet decomposition  time-frequency analysis  wavelet packet  fluctuation smoothing  
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