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Publishing Language: Chinese

Energy management of compound power supply based on grey wolf algorithm

Hui YI1,2, Hui CHEN1,2( )
School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, China
Key Laboratory of High Performance Ship Technology of Ministry of Education, Wuhan University of Technology, Wuhan 430063, China
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Abstract

Objective

In order to improve the power quality of ships under complex working conditions, an energy management strategy based on wavelet decomposition is proposed for fuel cell ships with a hybrid energy storage system (HESS) consisting of a battery and supercapacitor.

Methods

First, wavelet decomposition and fuzzy logic control are used to distribute the load power of the ship and optimize the charging and discharging process of the battery. Next, grey wolf optimizer （GWO） is used to optimize the parameters of the HESS and ensure that the energy management strategy matches the equipment parameters. Finally, the ship power system model is built using the Matlab/Simulink platform, and the simulation experiment is verified.

Results

The simulation results show that the proposed energy management strategy can effectively suppress the output power fluctuation of the fuel cell and realize rational power distribution among devices, reducing the optimized bus voltage fluctuation by 23.19%.

Conclusion

This study can provide useful references for the optimization design of the power quality of ships.

Keywords

fuel cell-powered vesselshybrid energy storage systemenergy storageenergy managementmultiobjective optimzationwavelet decompositionfuzzy controlgrey wolf optimizer
CLC number: U674.925 Document code: A

References

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Chinese Journal of Ship Research
Volume 20 Issue 3,
June 2025
Pages 249-257
DOI: 10.19693/j.issn.1673-3185.03617

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Cite this article:
YI H, CHEN H. Energy management of compound power supply based on grey wolf algorithm. Chinese Journal of Ship Research, 2025, 20(3): 249-257. https://doi.org/10.19693/j.issn.1673-3185.03617

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Received: 28 October 2023
Revised: 04 February 2024
Published: 17 April 2024
© 2025 Chinese Journal of Ship Research.