IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i13p10412-d1185013.html
   My bibliography  Save this article

Wavelet Packet-Fuzzy Optimization Control Strategy of Hybrid Energy Storage Considering Charge–Discharge Time Sequence

Author

Listed:
  • Xinyu Zhao

    (College of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Yunxiao Zhang

    (College of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Xueying Cui

    (College of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Le Wan

    (College of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Jinlong Qiu

    (College of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Erfa Shang

    (Inner Mongolia Xilin Gol League Dian Tou New Energy Co., Ltd., Xilinhot 026000, China)

  • Yongchang Zhang

    (College of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Haisen Zhao

    (College of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

Abstract

A hybrid energy storage system (HESS) can effectively suppress the high and low-frequency power fluctuations generated by wind farms under the intermittency and randomness of wind. However, for the existing power distribution strategies of HESS, power-type and energy-type energy storage have the problem of inconsistent charge–discharge states in the same time sequence, which makes it difficult to achieve optimal operation in terms of charge–discharge coordination and energy flow. To solve this problem, this study firstly adopts adaptive wavelet packet decomposition (WPD) to decompose the original wind power to acquire grid-connected power and HESS initial distribution power, to ensure that the supercapacitor and battery undertake the corresponding high and low-frequency power fluctuations, respectively; Then, for the inconsistent charge–discharge states, a charge–discharge time sequence optimization strategy based on the consistency index is proposed to correct the initial power distribution of HESS for the first time; Finally, aiming at the stage of charge (SOC) over-limit problem, the fuzzy optimization method is adopted to correct the HESS output power for the second time, which can reduce the unnecessary charge–discharge energy effectively. With typical daily output data of a 100 MW wind farm, the proposed control strategy is verified. The results show that it can make different energy storage technologies synchronously suppress wind power fluctuation in the same time sequence; compared with not considering charge–discharge time sequence optimization, the charge–discharge conversion times of the battery obtained by the proposed method are reduced from 71 to 14 times, and the charge–discharge conversion times of supercapacitor are reduced from 390 to 61 times; The cumulative reduction of unnecessary charge–discharge energy by HESS is 12.12 MWh. Besides, the SOC curves of HESS are controlled at a normal level, thus improving the economy and service life of HESS.

Suggested Citation

  • Xinyu Zhao & Yunxiao Zhang & Xueying Cui & Le Wan & Jinlong Qiu & Erfa Shang & Yongchang Zhang & Haisen Zhao, 2023. "Wavelet Packet-Fuzzy Optimization Control Strategy of Hybrid Energy Storage Considering Charge–Discharge Time Sequence," Sustainability, MDPI, vol. 15(13), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10412-:d:1185013
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/13/10412/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/13/10412/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shi, Jie & Wang, Luhao & Lee, Wei-Jen & Cheng, Xingong & Zong, Xiju, 2019. "Hybrid Energy Storage System (HESS) optimization enabling very short-term wind power generation scheduling based on output feature extraction," Applied Energy, Elsevier, vol. 256(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dimitrios Rimpas & Stavrοs D. Kaminaris & Dimitrios D. Piromalis & George Vokas, 2023. "Real-Time Management for an EV Hybrid Storage System Based on Fuzzy Control," Mathematics, MDPI, vol. 11(21), pages 1-18, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiao, Jucheng & He, Guangyu & Fan, Shuai & Zhang, Siyuan & Wu, Qing & Li, Zuyi, 2020. "Decentralized transfer of contingency reserve: Framework and methodology," Applied Energy, Elsevier, vol. 278(C).
    2. Yunhai Zhou & Pinchao Zhao & Fei Xu & Dai Cui & Weichun Ge & Xiaodong Chen & Bo Gu, 2020. "Optimal Dispatch Strategy for a Flexible Integrated Energy Storage System for Wind Power Accommodation," Energies, MDPI, vol. 13(5), pages 1-18, March.
    3. Li, Hongze & Sun, Dongyang & Li, Bingkang & Wang, Xuejie & Zhao, Yihang & Wei, Mengru & Dang, Xiaolu, 2023. "Collaborative optimization of VRB-PS hybrid energy storage system for large-scale wind power grid integration," Energy, Elsevier, vol. 265(C).
    4. Xiong, Hualin & Egusquiza, Mònica & Alberg Østergaard, Poul & Pérez-Díaz, Juan I. & Sun, Guoxiu & Egusquiza, Eduard & Patelli, Edoardo & Xu, Beibei & Duan, Hongjiang & Chen, Diyi & Luo, Xingqi, 2021. "Multi-objective optimization of a hydro-wind-photovoltaic power complementary plant with a vibration avoidance strategy," Applied Energy, Elsevier, vol. 301(C).
    5. Andrea Mannelli & Francesco Papi & George Pechlivanoglou & Giovanni Ferrara & Alessandro Bianchini, 2021. "Discrete Wavelet Transform for the Real-Time Smoothing of Wind Turbine Power Using Li-Ion Batteries," Energies, MDPI, vol. 14(8), pages 1-32, April.
    6. Barra, P.H.A. & de Carvalho, W.C. & Menezes, T.S. & Fernandes, R.A.S. & Coury, D.V., 2021. "A review on wind power smoothing using high-power energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    7. Ma, Chao & Xu, Ximeng & Pang, Xiulan & Li, Xiaofeng & Zhang, Pengfei & Liu, Lu, 2024. "Scenario-based ultra-short-term rolling optimal operation of a photovoltaic-energy storage system under forecast uncertainty," Applied Energy, Elsevier, vol. 356(C).
    8. Song, Hui & Gu, Mingchen & Liu, Chen & Amani, Ali Moradi & Jalili, Mahdi & Meegahapola, Lasantha & Yu, Xinghuo & Dickeson, George, 2023. "Multi-objective battery energy storage optimization for virtual power plant applications," Applied Energy, Elsevier, vol. 352(C).
    9. Aktaş, Ahmet & Kırçiçek, Yağmur, 2020. "A novel optimal energy management strategy for offshore wind/marine current/battery/ultracapacitor hybrid renewable energy system," Energy, Elsevier, vol. 199(C).
    10. Murphy, C.A. & Schleifer, A. & Eurek, K., 2021. "A taxonomy of systems that combine utility-scale renewable energy and energy storage technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:10412-:d:1185013. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.