OPTIMAL ALLOCATION OF HYBRID ENERGY STORAGE CAPACITY BASED ON VARIATIONAL MODE DECOMPOSITION

Li Xin; Wang Juan; Qiu Ya; Hou Yangcheng; Zhou Qin

doi:10.19912/j.0254-0096.tynxb.2020-0276

PDF(1862 KB)

Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (2) : 88-96. DOI: 10.19912/j.0254-0096.tynxb.2020-0276

OPTIMAL ALLOCATION OF HYBRID ENERGY STORAGE CAPACITY BASED ON VARIATIONAL MODE DECOMPOSITION

Li Xin, Wang Juan, Qiu Ya, Hou Yangcheng, Zhou Qin

Author information +

History +

Abstract

Focusing on the photovoltaic power output fluctuation and the hybrid energy storage capacity optimization, taking the photovoltaic system as research object, an optimal allocation strategy of hybrid energy storage capacity is put forward based on variational mode decomposition （VMD）. In this strategy, VMD is used to deal with the photovoltaic power output and Euclidean distance is employed to distinguish the relevant modes from the irrelevant modes. Meanwhile, persistent component signals in the irrelevant modes are extracted with the moving average method, which are reconstructed with the relevant modes to satisfy the national standard as the grid-connected power, and the fluctuation component signals in the irrelevant modes are suppressed with the hybrid energy storage system. As the result, the capacity optimization model of the hybrid energy storage system is established taking the minimum annual average allocation cost of the energy storage system as the objective function and the energy storage capacity allocation solution meeting the system requirements is obtained by using the improved cuckoo search algorithm to solve the model. The effectiveness and the economical efficiency are verified with the simulation and analysis on MATLAB/Simulink.

Key words

photovoltaic modules / energy storage / moving average / capacity allocation / variational mode decomposition / cuckoo search algorithm

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Li Xin, Wang Juan, Qiu Ya, Hou Yangcheng, Zhou Qin. OPTIMAL ALLOCATION OF HYBRID ENERGY STORAGE CAPACITY BASED ON VARIATIONAL MODE DECOMPOSITION[J]. Acta Energiae Solaris Sinica. 2022, 43(2): 88-96 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0276

References

[1] WANG X, YUE M, MULJADI E, et al.Probabilisticapproach for power capacity specification of wind energystorage systems[J]. IEEE transactions on industry applications, 2014, 50(2):1215-1224.
[2] JIANG Q Y, HONG H S.Wavelet-based capacity configuration and coordinated control of hybrid energy storage system for smoothing out wind power fluctuations[J]. IEEE transactions on power systems, 2013, 28(2):1363-1372.
[3] 冯磊, 杨淑连, 徐达, 等. 考虑风电输出功率波动性的混合储能容量多级优化配置[J]. 热力发电, 2019, 48(10): 44-50.
FENG L, YANG S L, XU D, et al.Multistage optimal allocation of hybrid energy storage capacity considering the fluctuation of wind power output[J]. Thermal power generation, 2019, 48(10): 44-50.
[4] 李建林, 牛萌, 田立亭, 等. 光伏扶贫电站光-储协同配置方法研究[J]. 太阳能学报, 2019, 40(1): 79-86.
LI J L, NIU M, TIAN L T, et al.Research on the method of light storage collaborative configuration of photovoltaic poverty alleviation power stations[J]. Acta enerigae solaris sinica, 2019, 40(1): 79-86.
[5] 韩晓娟, 田春光, 程成, 等. 基于经验模态分解的混合储能系统功率分配方法[J]. 太阳能学报, 2014, 35(10):1889-1896.
HAN X J, TIAN C G, CHENG C, et al.Power allocation method of hybrid energy storage system based on empirical mode decomposition[J]. Acta energiae solaris sinica, 2014, 35(10): 1889-1896.
[6] 张梦田, 田书, 曾志辉. 基于变分模态分解的混合储能容量优化配置[J]. 储能科学与技术, 2020, 9(1): 170-177.
ZHANG M T, TIAN S, ZENG Z H.Optimal allocation of hybrid energy storage capacity based on variational mode decomposition[J]. Energy storage science and technology, 2020, 9(1): 170-177.
[7] 张晓宇, 张建成, 王宁, 等. 基于变分模态分解的混合储能系统协调控制[J]. 中国电力, 2018, 51(9): 165-173.
ZHANG X Y, ZHANG J C, WANG N, et al.Coordinated control of hybrid energy storage system based on variational mode decomposition[J]. Electric power, 2018, 51(9): 165-173.
[8] 曲春辉, 孙文文, 陶思钰, 等. 基于模糊控制算法和布谷鸟搜索算法的混合储能系统优化配置[J]. 电气应用, 2019, 38(1): 16-22, 47.
QU C H, SUN W W, TAO S Y, et al.Optimal configuration of hybrid energy storage system based on fuzzy control algorithm and cuckoo search algorithm[J]. Electrotechnical application, 2019, 38(1): 16-22, 47.
[9] 马速良, 蒋小平, 马会萌, 等. 平抑风电波动的混合储能系统的容量配置[J]. 电力系统保护与控制, 2014, 42(8):108-114.
MA S L, JIANG X P, MA H M, et al.Capacity configuration of the hybrid energy storage system for wind power smoothing[J]. Power system protection and control, 2014(8): 108-114.
[10] 国家电网公司. 光伏电站接入电网技术规定[S]. 北京: 中国电力出版社, 2011.
Grid State.Technical regulations about PV plant connect to grid[S]. Beijing: China Electric Power Press, 2011.
[11] AN X, YANG J J.Denoising of hydropower unit vibration signal based on variational mode decomposition and approximate entropy[J]. Transactions of the Institute of Measurement & Control, 2016, 38(3): DOI: 10.117710142331215592064.
[12] 颜晨煜, 樊艳芳, 姚波. 采用自适应变分模态分解的混合储能平滑光伏出力波动控制策略[J]. 高电压技术, 2019, 45(6): 1898-1906.
YAN C Y, FAN Y F, YAO B.Hybrid energy storage control strategy with adaptive variational mode decomposition to smooth photovoltaic output fluctuation[J]. High voltage engineering, 2019, 45(6): 1898-1906.
[13] 徐帆, 常建华, 刘秉刚, 等.基于VMD的激光雷达回波信号去噪方法研究[J]. 激光与红外, 2018, 48(11):1443-1448.
XU F, CHANG J H, LIU B G, et al.De-noising method research for lidar echo signal based on variational mode decomposition[J]. Laser & infrared, 2018, 48(11): 1443-1448.
[14] MANDUHU M, JONES M W.A work efficient parallel algorithm for exact euclidean distance transform[J]. IEEE transactions on image processing, 2019, 28(11): DOI: 10.1109/TIP.20192916741.
[15] 张晴. 平抑风电波动的混合储能容量配置和经济性评估[D]. 长沙: 湖南大学, 2017.
ZHANG Q.Hybrid energy storage capacity allocation and economic evaluation for wind power fluctuation mitigation[D]. Changsha: Hunan University, 2017.
[16] YANG X S, DEB S.Cuckoo search via levy flights[C]//NaBic 2009: Proceedings of World Congress on Nature and Biologically Inspired Computing, Coimbatore, India, 2009: 210-214.
[17] TUSHAR K S, SUSHREE C P, MANAS R K. An adaptive cuckoo search based algorithm for placement of relay nodes in wireless body area networks[J]. Journal of King Saud University-Computer and Information Sciences, 2019: DOI: 10.10161J. jksuci. 2019.11.002.
[18] 李亚楠, 王倩, 宋文峰, 等. 混合储能系统平滑风电出力的变分模态分解-模糊控制策略[J]. 电力系统保护与控制, 2019, 47(7): 58-65.
LI Y N, WANG Q, SONG W F, et al.Variable mode decomposition fuzzy control strategy for smooth wind power output of hybrid energy storage system[J]. Power system protection and control, 2019, 47(7): 58-65.