常规发电机组比例降低导致受端电网无功支撑及抗干扰能力不足，电网安全稳定运行面临巨大挑战。为保证大扰动故障后电网电压稳定，提出一种计及构网型储能(grid-forming energy storage, GFM-ES)、调相机(synchronous condenser, SC)和负荷等多类型资源协调的受端电网电压稳定紧急控制策略。首先，构建考虑并网控制模式的构网型储能机电暂态模型，在电力系统分析综合程序(power system analysis software package, PSASP)中搭建自定义模块以模拟其动态特性。其次，建立基于压缩-激发-卷积神经网络(squeeze-and-excitation convolutional neural network, SE-CNN)的电网电压稳定水平预测模型，揭示复杂多变运行场景下控制措施量与电压稳定水平之间的映射关系。最后，分析多类型控制资源的无功调节特性，采用控制灵敏度指标评估不同控制对象对系统电压稳定水平的提升效果，据此提出电网电压稳定紧急控制协同策略，并在受端电网仿真系统中验证了所提策略的有效性。

With the decrease in the conventional synchronous generators, the secure and stable operation of receiving-end power grid faces challenges due to the insufficient reactive power support and disturbance rejection capability. In order to ensure voltage stability of the power system under severe faults, a voltage stability emergency control strategy is proposed to coordinate multiple types of regulation resources including grid-forming energy storage (GFM-ES) synchronous condenser (SC), and load shedding. Firstly, an electromechanical transient model of the GFM-ES is constructed, and a custom module is built in power system analysis software package (PSASP) to simulate its dynamic characteristics. Secondly, a system voltage stability prediction model based on squeeze-and-excitation convolutional neural network (SE-CNN) is established to map control quantity and voltage stability level under variable operating scenarios. Finally, the reactive power regulation characteristics of the multiple control resources are analyzed. Control sensitivity indices are employed to evaluate their enhancement effect on the voltage stability level, forming the basis for a coordinated emergency control strategy. The effectiveness of the proposed strategy is verified in a receiving-end power grid simulation system.