【目的】 基于虚拟同步发电机（virtual synchronous generator，VSG）控制的构网型（grid-forming，GFM）储能变流器能够有效为系统提供电压和频率支撑，但目前研究较少考虑新能源装置接入弱电网场景下VSG储能变流器的支撑能力。【方法】 以光伏系统和VSG储能系统为基础，分析其与弱电网之间的稳定性规律。首先建立了弱电网下光伏系统和VSG储能系统的小信号模型；其次采用特征值分析法，详细分析了系统中光伏出力变化、短路比（short circuit ratio，SCR）变化对系统特征值的影响；然后，通过研究振荡模态和参与因子，找出其中影响系统稳定性的高灵敏度控制参数；接着，在临界稳定状态下通过研究主导模态的根轨迹，提出改善系统稳定性的控制参数调整方法。最后，在MATLAB/Simulink构建的时域仿真模型验证了理论分析的有效性。【结果】仿真结果表明，在光伏出力波动（0.5~2.0 p.u.）和电网短路比变化（SCR为0.6~2.0）的多种工况下，所建小信号模型能准确识别出对系统稳定性具有显著影响的控制参数。通过实施所提参数调整方案，系统光伏输出从1.2 p.u.增加到2.0 p.u.，SCR=0.6时依然保持稳定。【结论】光伏系统出力变化时，VSG储能系统内外环q轴PI参数和光伏系统内外环q轴PI参数具有高灵敏度；SCR变化时，VSG储能系统内外环q轴PI参数具有高灵敏度，通过对不同灵敏度的控制参数进行有序调整，提高系统的静态稳定性，为高比例新能源电网的稳定性提升提供了有效解决方案。

[Objective] Grid-forming control （GFM） energy storage converters based on virtual synchronous generator （VSG） control can effectively provide voltage and frequency support for the system； however， current research has rarely considered the support capability of VSG energy storage converters in the scenario of new energy devices connected to weak power grids. [Methods] This study analyzed the stability laws between photovoltaic systems， VSG energy storage systems， and weak electricity grids. First， small signal models for photovoltaic and VSG energy storage systems under weak AC grids were established. Second， the eigenvalue analysis method was used to comprehensively analyze the impact of changes in photovoltaic output and SCR on the system's eigenvalues. Third， we identified the high-sensitivity control parameters that affect system stability by studying the oscillation modes and participation factors. Finally， a method for adjusting control parameters to improve system stability was proposed by studying the root locus of the dominant mode at the critical steady state. Finally， the accuracy of the stability impact law of the system was verified through a MATLAB/Simulink simulation under different operating conditions. The time-domain simulation model constructed using MATLAB/Simulink verified the effectiveness of the theoretical analysis. [Results] The simulation results showed that the small signal model established in this paper can accurately identify the control parameters that significantly impact system stability under various operating conditions， such as photovoltaic output fluctuations （0.5~2.0 p.u.） and changes in grid short-circuit ratio （SCR=0.6~2.0）. By implementing the proposed parameter adjustment scheme， the photovoltaic output of the system increased from 1.2 p.u. to 2.0 p.u. and remained stable at SCR=0.6. [Conclusions] When the output of the photovoltaic system changes， the q-axis pi parameters of the VSG energy storage system and the photovoltaic system have high sensitivity； when SCR changes， the internal and external q-axis pi parameters of the VSG energy storage system have high sensitivity. Orderly adjustment of the control parameters with different sensitivities improved the static stability of the system， thereby providing an effective solution for improving the stability of a high proportion of new energy grids.