基于动力学特性的构网型燃料电池发电系统并网稳定性分析OA
Grid-connected Stability Analysis of Grid-forming Fuel Cell Power Generation Systems Based on Dynamic Characteristics
在能源转型加速推进的背景下,燃料电池构网能力的应用有巨大的潜力.针对构网型燃料电池发电系统的多时间尺度稳定性问题,提出一种基于动力学理论的小信号稳定性分析方法.首先,建立了构网型燃料电池发电系统的小信号模型.其次,通过引入同步分量和阻尼分量的量化指标,构建了系统的动力学模型,揭示了不同运行工况下的稳定性演变规律.然后,采用参与因子分析法与动力学特性相结合的手段,深入剖析了燃料电池内部动态以及电池侧直流电压控制参数与构网型变流器功率同步控制、交流电压控制之间的动态耦合机理.最后,基于MATLAB/Simulink平台的时域仿真和硬件在环实验验证表明,所提出的分析方法能够准确预测系统稳定性边界.
Against the backdrop of the accelerated energy transition,the application of grid-forming capabilities of fuel cells holds great potential.This paper proposes a small-signal stability analysis method based on dynamic theory for the multi-timescale stability problem of grid-forming fuel cell power generation systems.Firstly,a small-signal model of the grid-forming fuel cell power generation system is established.Secondly,by introducing the quantitative indicators of the synchronous component and the damping component,the dynamic model of the system is constructed,revealing the stability evolution law under various operating conditions.Then,by combining the participation factor analysis method with the dynamic characteristics,the internal dynamics of the fuel cell and the dynamic coupling mechanism between the cell-side DC voltage control parameters and the power synchronous control and AC voltage control of the grid-forming converter are deeply analyzed.Finally,the time-domain simulation based on the MATLAB/Simulink platform and the hardware-in-the-loop experiment verification show that the proposed analysis method can accurately predict the stability boundary of the system.
龚梓轩;谢长君;黄云辉;崔建浩;王喆伟;王栋
武汉理工大学自动化学院,湖北省武汉市 430070武汉理工大学自动化学院,湖北省武汉市 430070武汉理工大学自动化学院,湖北省武汉市 430070||武汉理工大学深圳研究院,广东省 深圳市 518000武汉理工大学自动化学院,湖北省武汉市 430070武汉理工大学自动化学院,湖北省武汉市 430070武汉理工大学自动化学院,湖北省武汉市 430070
燃料电池构网多时间尺度小信号稳定性动力学模型耦合
fuel cellgrid-formingmulti-timescalesmall-signal stabilitydynamic modelcoupling
《电力系统自动化》 2026 (16)
100-111,12
国家自然科学基金智能电网联合基金重点资助项目(U24B20103)广东省基础与应用基础研究基金资助项目(2023A1515240052). This work is supported by National Natural Science Foundation of China(No.U24B20103)and Guangdong Basic and Applied Basic Research Foundation(No.2023A1515240052).
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