| 引用本文: | 邱晓燕,马娅妮,朱英伟,王鹏,雷勇.基于可变分频点的SMES-VRB混合储能系统在风电并网中的应用[J].电力自动化设备,2022,42(2): |
| QIU Xiaoyan,MA Yani,ZHU Yingwei,WANG Peng,LEI Yong.Application of SMES-VRB hybrid energy storage system based on alterable frequency division point in wind power grid-connection[J].Electric Power Automation Equipment,2022,42(2): |
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| 摘要: |
| 为了平抑风电并网引起的功率波动，以超导磁储能(SMES)和全钒液流电池(VRB)组成的混合储能系统(HESS)为研究对象，针对变流器控制设计了基于径向基函数(RBF)神经网络的比例积分控制器，可根据HESS的动态辨识结果实时改变控制参数，有利于HESS功率指令跟踪和直流侧电压稳定。针对风电的功率分配，采用小波包分解，首先秉持“能者多劳”的原则，设置根据储能荷电状态变化的分频点，灵活分配高、低频功率，从而最大限度地利用储能空间；然后基于VRB能量密度大和使用寿命长的特点，在SMES充放电不足时给予援助性功率支撑，协助SMES迅速恢复最佳状态，有利于更加充分地平滑风电功率波动。在MATLAB/Simulink平台上建模仿真，结果验证了所提方法的优越性。 |
| 关键词: 混合储能系统 RBF神经网络 超导磁储能 全钒液流电池 可变分频点 最佳荷电状态 风电并网 小波包分解 |
| DOI：10.16081/j.epae.202110007 |
| 分类号:TM614;TM716 |
| 基金项目:国家自然科学基金资助项目(51977134) |
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| Application of SMES-VRB hybrid energy storage system based on alterable frequency division point in wind power grid-connection |
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QIU Xiaoyan, MA Yani, ZHU Yingwei, WANG Peng, LEI Yong
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College of Electrical Engineering, Sichuan University, Chengdu 610065, China
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| Abstract: |
| In order to smooth the power fluctuations caused by wind power grid-connection, the HESS(Hybrid Energy Storage System) composed of SMES(Superconducting Magnetic Energy Storage) and VRB(Vanadium Redox flow Battery) is taken as the research object. A proportional integral controller based on RBF(Radial Basis Function) neural network is designed for converter control. The control parameters can be changed in real time according to the dynamic identification results of HESS, which is beneficial to HESS power instruction tracking and DC side voltage stability. For the power distribution of wind power, the wavelet packet decomposition is adopted. Firstly, according to the principle of “Able men are always busy”,the frequency division points are set according to the change of energy storage, and the power of high and low frequency is allocated flexibly, so as to make the energy storage space be utilized to a greater extent. Then, based on the characteristics of high energy density and long service life of VRB, auxiliary power support is given to SMES when charging or discharging power is insufficient, so as to help SMES quickly recover to the optimal state, which is conducive to smooth wind power fluctuations more fully. The simulative results on MATLAB/Simulink platform verify the advantages of the proposed method. |
| Key words: hybrid energy storage system RBF neural network SMES VRB alterable frequency division point optimal state of charge wind power grid-connection wavelet packet decomposition |
