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西安交通大学电气工程学院,陕西省西安市 710049
Received:17 June 2025,
Revised:2025-11-07,
Online First:16 June 2026,
Published:10 August 2026
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赵博衍,秦玉文,段超等.跟网-构网混联系统虚拟惯量与阻尼参数协同优化方法[J].电力系统自动化,2026,50(15):238-255.
ZHAO Boyan,QIN Yuwen,DUAN Chao,et al.Collaborative Optimization Method for Virtual Inertia and Damping Parameter of Grid-following/Grid-forming Hybrid Systems[J].Automation of Electric Power Systems,2026,50(15):238-255.
赵博衍,秦玉文,段超等.跟网-构网混联系统虚拟惯量与阻尼参数协同优化方法[J].电力系统自动化,2026,50(15):238-255. DOI: 10.7500/AEPS20250617002.
ZHAO Boyan,QIN Yuwen,DUAN Chao,et al.Collaborative Optimization Method for Virtual Inertia and Damping Parameter of Grid-following/Grid-forming Hybrid Systems[J].Automation of Electric Power Systems,2026,50(15):238-255. DOI: 10.7500/AEPS20250617002.
高比例新能源经电力电子设备接入显著削弱了电力系统的振荡阻尼能力和整体惯量水平。构网型变流器虽可主动提供系统惯量与阻尼支撑,但安全稳定特性受到多机参数非线性耦合影响,增大了设备惯量和阻尼配置难度。为此,文中提出一种融合矩阵摄动理论与交替优化机制的多变流器虚拟惯量与阻尼协同优化方法。首先,构建包含小干扰同步稳定性、频率安全性及设备物理极限的多约束非线性、非光滑优化模型,随后采用交替更新机制将其分解为虚拟惯量和阻尼的独立优化问题。然后,基于矩阵摄动理论推导特征值对参数的灵敏度表达式,将非光滑独立优化问题转化为可迭代求解的线性子问题序列,同时提出基于特征值二阶灵敏度的信赖域自适应步长策略,提升收敛效率与稳定性。算例验证表明,所提方法在构网型变流器接入位置、数量变化及潮流波动等多种鲁棒性挑战下均能显著提升小干扰稳定性,且优化效果与效率均优于传统方法。
The high proportion of renewable energy connected through power electronic equipment significantly weakens the oscillation damping capability and overall inertia level of the power system. Although grid-forming converters can actively provide system inertia and damping support
their security and stability characteristics are influenced by nonlinear coupling of multi-machine parameters
increasing the difficulty in configuring device inertia and damping. To address this
this paper proposes a multi-converter virtual inertia and damping collaborative optimization method integrating the matrix perturbation theory and alternating optimization mechanism. First
a multi-constraint nonlinear and nonsmooth optimization model is constructed
encompassing small-signal synchronous stability
frequency security
and device physical limits. Subsequently
an alternating update mechanism is employed to decompose it into independent optimization problems for virtual inertia and damping. Then
based on the matrix perturbation theory
the sensitivity expressions of eigenvalues to parameters are derived
transforming the nonsmooth independent optimization problem into a iteratively solvable sequence of linear subproblems. Additionally
a trust-region adaptive step size strategy based on eigenvalue second-order sensitivity is proposed to enhance convergence efficiency and stability. Case studies demonstrate that the proposed method significantly improves small-signal stability under various robustness challenges
including changes in grid-forming converter connection locations
quantities
and power flow fluctuations
with both optimization effectiveness and efficiency surpassing traditional methods.
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