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

Xinyu Zhao, Yunxiao Zhang, Xueying Cui, Le Wan, Jinlong Qiu, Erfa Shang, Yongchang Zhang and Haisen Zhao ()
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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

Sustainability, 2023, vol. 15, issue 13, 1-17

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.

Keywords: hybrid energy storage system; wind power suppression; charge–discharge time sequence optimization; wavelet packet decomposition; fuzzy optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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