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随着可再生能源融合到传统电力系统中,电力系统的惯性显著降低,从而使系统对运行过程中受到的扰动非常敏感.本文提出了一种基于扰动的惯性估计方法,揭示了可再生能源对系统惯性的影响.然后,本文利用高斯过程回归方法对受扰动后的电力系统动态过程进行预测.大量实验表明,数据驱动的方法有效地估计了系统的惯性,并预测了受干扰后电网的动态运行情况.实验结果也为设计和提高系统惯性提供了参考.“,”With the integration of renewable energy resources, the inertia of power systems significantly reduces, thereby making the system sensitive to operational disturbances. A disturbance-based method is presented herein to estimate inertia, uncovering the influence of renewables on system-resilient operations. The Gaussian process regression method is then used to predict the power system trajectory after disturbance. Extensive tests demonstrate the data-driven method mathematically estimates the inertia of the system as well as predicts the dynamics operations of power grids subject to disturbances. Numerical results also offer insights into the enhancement of system resilience by strategically designing the inertia of power systems.