基于参数优化变分模态分解的混合储能功率分配策略

doi:10.19799/j.cnki.2095-4239.2021.0374

储能科学与技术 ›› 2022, Vol. 11 ›› Issue (1): 147-155.doi: 10.19799/j.cnki.2095-4239.2021.0374

基于参数优化变分模态分解的混合储能功率分配策略

高晓芝¹(), 王磊¹, 田晋¹, 刘佳璐²(), 刘庆华³

^1.河北科技大学电气工程学院，河北石家庄 050000
^2.中国特种设备检测研究院，北京 100029
^3.北京低碳清洁能源研究院，北京 102211

收稿日期:2021-07-23 修回日期:2021-09-28 出版日期:2022-01-05 发布日期:2022-01-10
通讯作者: 刘佳璐 E-mail:gaoxiaozhi@hebust.edu.cn;ljlalice@hotmail.com
作者简介:高晓芝（1981—），女，博士，研究方向为新能源控制及应用等，E-mail：gaoxiaozhi@hebust.edu.cn|刘佳璐，高级工程师，研究方向为数学建模、人工智能及特种设备安全，E-mail：ljlalice@hotmail.com。
基金资助:
河北省科技支撑计划重点项目(19214501D)

Research on hybrid energy storage power distribution strategy based on parameter optimization variational mode decomposition

Xiaozhi GAO¹(), Lei WANG¹, Jin TIAN¹, Jialu LIU²(), Qinghua LIU³

^1.School of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, Hebei, China, Beijing 102211, China
^2.China Special Equipment Inspection & Research Insstitute, Beijing 100029, China, Beijing 102211, China
^3.National Institute of Clean and Low Carbon Energy, Beijing 102211, China

Received:2021-07-23 Revised:2021-09-28 Online:2022-01-05 Published:2022-01-10
Contact: Jialu LIU E-mail:gaoxiaozhi@hebust.edu.cn;ljlalice@hotmail.com

摘要/Abstract

摘要：

以全钒液流电池和超级电容器组成的混合储能系统(hybrid energy storage system，HESS)可有效平抑风电功率波动。为了提高储能系统的灵活性和安全性，提出一种基于参数优化变分模态分解(variational mode decomposition，VMD)的混合储能功率分配方法。首先利用指数平滑法依据我国并网标准对风电功率进行滤波，得到符合要求的风电并网功率，并计算出储能系统所需要的平滑风电波动功率；然后基于三种信号分解评价指标构造适应度函数，采用麻雀搜索算法(sparrow search algorithm，SSA)对VMD算法中模态个数K与二次惩罚因子α进行优化，得到优化后的K值与α值后采用VMD算法分解风电波动功率并完成在全钒液流电池和超级电容器间的基本分配；最后采用模糊控制器优化储能设备的荷电状态，实现HESS功率的二次分配。算例结果表明，所提方法不仅能够对风电波动功率信号自适应分解，有效抑制风电功率波动，减少模态混叠，完成HESS功率的合理分配，还可以优化储能设备的充放电范围，避免储能设备的过度充电和过度放电状况的发生，保证储能设备的荷电状态维持在固定区间，实现HESS安全稳定运行。

关键词: 混合储能系统, 变分模态分解, 麻雀搜索算法, 模糊控制, 荷电状态

Abstract:

Hybrid Energy Storage System (HESS), composed of all-vanadium flow batteries and supercapacitors, can effectively suppress wind power fluctuations. In order to improve the flexibility and safety of the energy storage system, a hybrid energy storage power distribution method based on parameter optimization Variational Mode Decomposition (VMD) is proposed. Firstly, the exponential smoothing method is used to filter the wind power according to the grid connection standard to obtain the required wind power grid flowing into grid, and the wind fluctuation power which needs to be smoothed by energy storage system is calculated. Then, the fitness function is constructed by three signal decomposition evaluation indexes,and a Sparrow Search Algorithm (SSA) is adopted to optimize the mode number K and the secondary penalty factor α for VMD algorithm. Based on the optimized values of K and α, VMD algorithm is used to decompose the fluctuating wind power and then distribute it reasonably between the batteries and the supercapacitors. Finally, a fuzzy controller is employed to optimize the state of charge (SOC) of storage device to realize the secondary distribution of HESS. Example results show that the proposed method can not only adaptively decompose the wind power fluctuation power signal, effectively suppress the wind power fluctuation, reduce modal mixing and complete the reasonable distribution of HESS power, but also optimize the charge and discharge range of energy storage equipment, avoid the occurrence of overcharge and excessive discharge of energy storage equipment, and ensure the charge state of energy storage equipment in a fixed range, which realizes the safe and stable operation of HESS.

Key words: variational mode decomposition (VMD), sparrow search algorithm (SSA), hybrid energy storage system (HESS), fuzzy control, state of charge (SOC)

中图分类号:

TM 73

高晓芝, 王磊, 田晋, 刘佳璐, 刘庆华. 基于参数优化变分模态分解的混合储能功率分配策略[J]. 储能科学与技术, 2022, 11(1): 147-155.

Xiaozhi GAO, Lei WANG, Jin TIAN, Jialu LIU, Qinghua LIU. Research on hybrid energy storage power distribution strategy based on parameter optimization variational mode decomposition[J]. Energy Storage Science and Technology, 2022, 11(1): 147-155.

图/表 16

表1

图1

图2

图3

表2

全钒液流电池模糊控制规则"

$Δ P b (t)$		SOC_b
$Δ P b (t)$		NB	NM	NS	ZO	PS	PM	PB
$P b (t)$	D	PB	PM	PS	ZO	ZO	ZO	ZO
$P b (t)$	C	ZO	ZO	ZO	ZO	NS	NM	NB

表2

表3

超级电容器模糊控制规则"

$Δ P s (t)$		SOC_s
$Δ P s (t)$		NB	NM	NS	ZO	PS	PM	PB
$P s (t)$	D	PB	PM	PS	ZO	ZO	ZO	ZO
$P s (t)$	C	ZO	ZO	ZO	ZO	NS	NM	NB

表3

图4

图5

图6

图7

图8

图9

图10

图11

图12

表4

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状态	全钒液流电池SOC区间	超级电容器SOC区间
优化前	11%～91%	32%～97%
优化后	21%～79%	39%～88%

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基于参数优化变分模态分解的混合储能功率分配策略

Research on hybrid energy storage power distribution strategy based on parameter optimization variational mode decomposition

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