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arXiv Machine Learning By Md Obaidur Rahman, Junjie Qin, Vassilis Kekatos

AC Power Flow Contingency Analysis Using a Single Deep Neural Network

Read the original on arXiv Machine Learning →

The paper introduces a method that uses a single deep neural network, trained only on basecase AC power flow data, to predict post-contingency operating states for any single-line outage. It frames this prediction as a fixed-point iteration and provides sufficient convergence conditions, certifying them via semidefinite programming. Numerical experiments on the IEEE 118-bus system show that the certified conditions hold for all tested contingencies and that accurate state estimates are achieved in only a few iterations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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