AI shows promise for flood forecasting and water security in data scarce regions

New research reveals that "foundation models" trained on vast, general time-series data may be able to forecast river flows accurately, even in regions with little or no local hydrological records.
Devdiscourse

From transformers to microgrids: AI expands across critical energy infrastructure

Utilities worldwide are turning to artificial intelligence (AI) and machine learning to stabilize networks, forecast ...
IEEE

Deep learning-Based Fault Detection and Classification in Multi-Bus Power Systems Using MATLAB Diagnostic Feature Designer and Bidirectional LSTM Networks

Abstract: Traditional fault detection systems in power networks face significant challenges in accurately identifying complex fault patterns, particularly in multi-bus configurations with varying ...
IEEE

Predicting Cascading Failures in Power Systems using Machine Learning

Abstract: Cascading failure studies help assess and enhance the robustness of power systems against severe power outages. Onset time is a critical parameter in the analysis and management of power ...