Energy Management Optimization of Fuel Cell Hybrid Ship Based on Particle Swarm Optimization Algorithm

Xin Peng, Hui Chen and Cong Guan ()
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Xin Peng: Shenzhen Research Institute, Wuhan University of Technology, Shenzhen 518000, China
Hui Chen: Shenzhen Research Institute, Wuhan University of Technology, Shenzhen 518000, China
Cong Guan: Shenzhen Research Institute, Wuhan University of Technology, Shenzhen 518000, China

Energies, 2023, vol. 16, issue 3, 1-15

Abstract: In order to optimize the energy management strategy and solve the problem of the power quality degradation of fuel cell hybrid electric ships, a particle swarm optimization algorithm based energy management strategy is proposed in this paper. Taking a fuel cell ship as the target ship, a system simulation model is built in Matlab/Simulink to verify the proposed energy management strategy. Through simulations and comparisons, the bus voltage curve of the optimized hybrid power system fluctuates more gently, and the voltage sag is smaller. The amplitude of the voltage fluctuation under maneuvering conditions is reduced by 55% compared with that of the original ship. The charging and discharging process of the composite energy storage system is optimized under maneuvering conditions, the power quality of the marine power grid is improved, and the use of the energy management strategy can extend the service life of the battery.

Keywords: fuel cell; hybrid ship; energy management strategy; particle swarm optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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