基于神经网络的电力电子资源主导型电力系统不确定性感知稳定性分析

Machine learning (ML) technologies have significant potential in accelerating stability screening of modern power systems that are dominated by inverter-based resources. Nonetheless, neural network (NN)-based analysis methods cannot guarantee accurate and reliable stability predictions for unseen operating scenarios (OSs), posing safety risks. To address this limitation, this letter proposes an ap...