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基于3种SOGI-GD-FLL算法的储能变换器虚拟惯量设计与评估OA

Virtual Inertia Design and Evaluation of Energy Storage Converter Based on Three SOGI-GD-FLL Algorithms

中文摘要英文摘要

现有基于电网频率微分信号(grid frequency differential signal,GFDS)检测的储能变换器(energy storage converter,ESC)虚拟惯量控制方法中,基于梯度下降(gradient descent,GD)算法的二阶广义积分器-锁频环(second-order generalized integrator-frequency locked loop,SOGI-FLL)(简称"SOGI-GD-FLL")因能有效提取GFDS,成为关键技术之一.目前针对GD算法下的不同GFDS检测方法及其虚拟惯量控制性能,仍缺乏系统性评估.为此,提出2种不同于典型SOGI-GD-FLL控制结构的GFDS检测算法.首先,通过重新配置其输出信号的数学运算关系构建2种GFDS检测算法的控制回路;然后,同步给出3种算法的小信号数学模型以及参数设计方法;最后,利用 MATLAB/Simulink仿真及实验进行对比评估,结果验证了3种SOGI-GD-FLL算法均能实现对GFDS的准确检测,并为ESC的虚拟惯量控制提供可靠输入.

Among the existing virtual inertia control methods for energy storage converters(ESCs)based on the grid frequency differential signal(GFDS)detection,the second-order generalized integrator-frequency locked loop(SOGI-FLL)on the basisi of the gradient descent(GD)(abbreviated as SOGI-GD-FLL)algorithm has become one of the key technologies due to its effective extraction of GFDS.However,systematic evaluation of different GFDS detection methods under the GD algorithm and their virtual inertia control performance is still insufficient.Therefore,two GFDS detection algorithms different from the typical SOGI-GD-FLL control structure are proposed.Firstly,the control loops for two GFDS detection algorithms by reconfiguring the mathematical relationship of their output signals are constructed.Then,the small-signal mathematical models and parameter design methods for all three algorithms are simultaneously present.Finally,the MATLAB/Simulink simulation and experimental comparison results verify that the three SOGI-GD-FLL algorithms can accurately detect GFDS and provide reliable input for the virtual inertia control of ESC.

兰玉洁;石荣亮;李美姝

桂林理工大学 广西高校先进制造与自动化技术重点实验室,广西 桂林 541006桂林理工大学 广西高校先进制造与自动化技术重点实验室,广西 桂林 541006桂林理工大学 广西高校先进制造与自动化技术重点实验室,广西 桂林 541006

信息技术与安全科学

虚拟惯量二阶广义积分器-锁频环电网频率微分信号数学模型参数设计

virtual inertiasecond-order generalized integrator-frequency locked loop(SOGI-FLL)grid frequency differential signal(GFDS)mathematical modelparameter design

《广东电力》 2026 (8)

54-63,10

国家自然科学基金项目(52467022)广西自然科学基金项目(2025GXNSFAA069219)

10.3969/j.issn.1007-290X.2026.08.006

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