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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
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    References listed on IDEAS

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    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).
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    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.

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