Research Article | | Peer-Reviewed

Research on Wind Energy Fluctuation Stabilization and Hybrid Energy Storage Capacity Optimization Strategy Based on EWD

Received: 28 November 2023     Accepted: 13 December 2023     Published: 22 December 2023
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Abstract

With the increase of installed capacity of wind power in China, the randomness and fluctuation of wind power output power make the grid frequency modulation more difficult. To solve this problem, a hybrid energy storage system composed of lithium batteries and super-capacitors is used to stabilize the wind power output. This study focuses on the smoothing strategies and capacity configuration methods of hybrid energy storage system, which is of great significance to increase its utilization rate and reduce energy storage capacity. An empirical wavelet decomposition method is used to decompose the wind farm output power data and obtain the charging and discharging instructions of hybrid energy storage system. For the smoothing power of energy storage system, high frequency decomposition is carried out with the lowest cost as the target to obtain the capacity optimization strategy of different types of energy storage. This study also analyzes the typical 8-day output power data of a wind farm and optimizes the power and capacity allocation of lithium battery and supercapacitor through combining numerical examples with wind power system grid power calculation. The numerical examples verify the effectiveness of the proposed smoothing method and capacity optimization algorithm.

Published in International Journal of Energy and Power Engineering (Volume 12, Issue 6)
DOI 10.11648/j.ijepe.20231206.13
Page(s) 100-108
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

Wind Power Fluctuation, Hybrid Energy Storage System (HESS), Empirical Wavelet Decomposition (EWD), Empirical Mode Decomposition (EMD), Wavelet Decomposition

References
[1] Wen Yun feng, Yang Wei feng, Wang Rong hua, et al. Review and prospects of constructing a 100% renewable energy power system [J]. Proceedings of the Chinese Society of Electrical Engineering, 2020, Vol. 40, Iss. 6, pp. 1843-1856.
[2] Chen Guoping, Li Mingjie, Xu Tao, et al. Study on Technical Bottleneck of New Energy Development [J]. Proceedings of the CSEE, 2017, 37 (1), pp. 20—26.
[3] Jannati M, Hosseinian S H, Vahidi B, et al. A Survey on Energy Storage Resources Configurations in Order to Propose an Optimum Configuration for Smoothing Fluctuations of Future Large wind Power Plants [J]. Renewable and Sustainable Energy Reviews, 2014, 29, pp. 158-172.
[4] Li Jianlin, Ma Huimeng, Hui Dong. Present Development Condition and Trends of Energy Storage Technology in the Integration of Distributed Renewable Energy [J]. Transactions of China Electrotechnical Society, 2016, 31 (14), pp. 1-10.
[5] Tian Jun, Zhu Yongqiang, Chen Caihong. Application of energy storage technologies in distributed generation [J]. Electrical Engineering, 2010, 11 (8), pp. 28-32.
[6] Qiao Liang bo, Zhang Xiao hu, Sun Xian zhong, et al. Advances in battery-supercapacitor hybrid energy storage system [J]. Energy Storage Science and Technology, 2022, Vol. 11, Iss. 1, pp. 98-106.
[7] Francisco D G, Andreas S, Oriol G B, et al. A Review of Energy Storage Technologies for Wind Power Applications [J]. Renewable & Sustainable Energy Reviews, 2012, Vol. 16, Iss. 4, pp. 2154-2171.
[8] Pang Ming, Shi Yikai1, et al. An Optimal Sizing Hybrid Energy Storage System for Smoothing the Output Fluctuations of Wind Power [J]. Journal of Northwestern Polytechnical University, 2016, Vol. 34, Iss. 3, pp. 493-498.
[9] Wu Xin, Li Yangtao1, et al. Capacity Configuration Method of Hybrid Energy Storage System Based on Improved Wavelet Packet Decomposition [J]. Journal of solar energy, 2023, Vol. 44, Iss. 8, pp. 23-29.
[10] Li Jie, Yang Lin. Wind power storage capacity configuration based on wavelet transform and chance constrained programming [J]. POWER DSM, 2021, Vol. 23, Iss. 2, pp. 37-42.
[11] Guo Tingting, Liu You bo, Zhao Jun bo, et al. A dynamic wavelet-based robust wind power smoothing approach using hybrid energy storage system [J]. International Journal of Electrical Power &Energy Systems, 2020, 116, 0142-0615.
[12] Sun Cheng chen, Yuan Yue, et al. Capacity Optimization of Hybrid Energy Storage System in Microgrid Using Empirical Mode Decomposition and Neural Network [J]. Automation of Electric Power Systems, 2015, Vol. 39, Iss. 8, pp. 19-26.
[13] Huang N E. New Method for Nonlinear and Nonstationary Time Series Analysis: Empirical Mode Decomposition and Hilbert Spectral Analysis [J]. Proceedings of SPIE-The International Society for Optical Engineering, 2000, pp. 197-209.
[14] Wang Tao, Zhang Bing. Application of Improved Empirical Transform in Fault Feature Extraction of Bearings [J]. Railway Lowcomtive & Car, 2019, Vol. 39, Iss. 5, 116, pp. 53-58.
[15] Zhou Hao, Jia Min ping. Analysis of rolling bearing fault diagnosis based on EMD and kurtosis Hilbert envelope demodulation [J]. Journal of Mechanical & Electrical Engineering, 2014, Vol. 31, Iss. 9, 116, pp. 1139-1167.
Cite This Article
  • APA Style

    Lv, Z., Wang, Z., An, C. (2023). Research on Wind Energy Fluctuation Stabilization and Hybrid Energy Storage Capacity Optimization Strategy Based on EWD. International Journal of Energy and Power Engineering, 12(6), 100-108. https://doi.org/10.11648/j.ijepe.20231206.13

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    ACS Style

    Lv, Z.; Wang, Z.; An, C. Research on Wind Energy Fluctuation Stabilization and Hybrid Energy Storage Capacity Optimization Strategy Based on EWD. Int. J. Energy Power Eng. 2023, 12(6), 100-108. doi: 10.11648/j.ijepe.20231206.13

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    AMA Style

    Lv Z, Wang Z, An C. Research on Wind Energy Fluctuation Stabilization and Hybrid Energy Storage Capacity Optimization Strategy Based on EWD. Int J Energy Power Eng. 2023;12(6):100-108. doi: 10.11648/j.ijepe.20231206.13

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  • @article{10.11648/j.ijepe.20231206.13,
      author = {Zhaorui Lv and Zhiyong Wang and Changhe An},
      title = {Research on Wind Energy Fluctuation Stabilization and Hybrid Energy Storage Capacity Optimization Strategy Based on EWD},
      journal = {International Journal of Energy and Power Engineering},
      volume = {12},
      number = {6},
      pages = {100-108},
      doi = {10.11648/j.ijepe.20231206.13},
      url = {https://doi.org/10.11648/j.ijepe.20231206.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20231206.13},
      abstract = {With the increase of installed capacity of wind power in China, the randomness and fluctuation of wind power output power make the grid frequency modulation more difficult. To solve this problem, a hybrid energy storage system composed of lithium batteries and super-capacitors is used to stabilize the wind power output. This study focuses on the smoothing strategies and capacity configuration methods of hybrid energy storage system, which is of great significance to increase its utilization rate and reduce energy storage capacity. An empirical wavelet decomposition method is used to decompose the wind farm output power data and obtain the charging and discharging instructions of hybrid energy storage system. For the smoothing power of energy storage system, high frequency decomposition is carried out with the lowest cost as the target to obtain the capacity optimization strategy of different types of energy storage. This study also analyzes the typical 8-day output power data of a wind farm and optimizes the power and capacity allocation of lithium battery and supercapacitor through combining numerical examples with wind power system grid power calculation. The numerical examples verify the effectiveness of the proposed smoothing method and capacity optimization algorithm.
    },
     year = {2023}
    }
    

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  • TY  - JOUR
    T1  - Research on Wind Energy Fluctuation Stabilization and Hybrid Energy Storage Capacity Optimization Strategy Based on EWD
    AU  - Zhaorui Lv
    AU  - Zhiyong Wang
    AU  - Changhe An
    Y1  - 2023/12/22
    PY  - 2023
    N1  - https://doi.org/10.11648/j.ijepe.20231206.13
    DO  - 10.11648/j.ijepe.20231206.13
    T2  - International Journal of Energy and Power Engineering
    JF  - International Journal of Energy and Power Engineering
    JO  - International Journal of Energy and Power Engineering
    SP  - 100
    EP  - 108
    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.20231206.13
    AB  - With the increase of installed capacity of wind power in China, the randomness and fluctuation of wind power output power make the grid frequency modulation more difficult. To solve this problem, a hybrid energy storage system composed of lithium batteries and super-capacitors is used to stabilize the wind power output. This study focuses on the smoothing strategies and capacity configuration methods of hybrid energy storage system, which is of great significance to increase its utilization rate and reduce energy storage capacity. An empirical wavelet decomposition method is used to decompose the wind farm output power data and obtain the charging and discharging instructions of hybrid energy storage system. For the smoothing power of energy storage system, high frequency decomposition is carried out with the lowest cost as the target to obtain the capacity optimization strategy of different types of energy storage. This study also analyzes the typical 8-day output power data of a wind farm and optimizes the power and capacity allocation of lithium battery and supercapacitor through combining numerical examples with wind power system grid power calculation. The numerical examples verify the effectiveness of the proposed smoothing method and capacity optimization algorithm.
    
    VL  - 12
    IS  - 6
    ER  - 

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Author Information
  • Mechanical and Electrical Engineering Division, Wenhua College, Wuhan, China

  • The Fourth Military Representative Office, NEO, Shanghai, China

  • Mechanical and Electrical Engineering Division, Wenhua College, Wuhan, China

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