Power Failure Cascade Prediction using Graph Neural Networks

arXiv:2404.16134v1 Announce Type: cross
Abstract: We consider the problem of predicting power failure cascades due to branch failures. We propose a flow-free model based on graph neural networks that predicts grid states at every generation of a cascade process given an initial contingency and power injection values. We train the proposed model using a cascade sequence data pool generated from simulations. We then evaluate our model at various levels of granularity. We present several error metrics that gauge the model's …

abstract arxiv cs.lg cs.sy eess.sy every failure flow free graph graph neural networks grid networks neural networks power prediction process train type values