Johannes Rueß

Data-Driven Graph Convolutional Neural Networks for Power System Contingency Analysis

We develop a graph convolutional neural network for power system contingency analysis. In contrast to other methods, the proposed architecture is purely data-driven and does not require knowledge of the power grid’s underlying topology. Instead, the estimation of multiple correlation-based graphs en…