Temporal decomposition is a potential approach to relieve the computation cost of power system multi-interval scheduling problems, such as economic dispatch. In this form of decomposition, the ...

We use machine learning to lossily compress tens to hundreds of measurements simultaneously, providing a route to insight about complex systems through information decomposition. Abstract One of the ...

Model predictive control (MPC) has been widely used to control and operate complex systems. However, the efficient implementation of MPC depends on the efficient solution of the underlying ...

To address this, distributed machine learning (ML) systems play a crucial role. Using a multi-tier architecture, these systems analyze real-time data to predict energy demands and manage power ...