基于灰狼算法的复合电源能量管理

Energy management of compound power supply based on grey wolf algorithm

  • 摘要:
    目的 为了提高复杂工况下的船舶电能质量,针对由电池−超级电容作为复合储能系统的燃料电池船,提出一种基于小波分解的能量管理策略。
    方法 首先,采用小波分解和模糊逻辑控制对船舶负载功率进行分配,同时优化电池的充放电过程;然后,采用灰狼算法对复合储能系统的参数进行优化,从而使能量管理策略与设备参数相匹配;最后,在Matlab/Simulink平台中搭建船舶动力系统模型,进行仿真实验验证。
    结果 仿真结果表明:该能量管理策略可以有效抑制燃料电池的输出功率波动,实现了各设备之间功率的合理分配,其优化后的母线电压波动降低了23.19%。
    结论 研究成果可对船舶电能质量的优化设计提供参考。

     

    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.

     

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