Search Results for author:
Found 3 papers, 1 papers with code
Data-driven AC Optimal Power Flow with Physics-informed Learning and Calibrations
Due to the nonconvex nature of the Alternating Current Optimal Power Flow (ACOPF) problem and the need for operations with better granularity in the modern smart grid, system operators require a more efficient and reliable ACOPF solver.
Complex Graph Laplacian Regularizer for Inferencing Grid States
In order to maintain stable grid operations, system monitoring and control processes require the computation of grid states (e. g. voltage magnitude and angles) at high granularity.
A Data-Driven Approach for Generating Synthetic Load Patterns and Usage Habits
Today's electricity grid is rapidly evolving to become highly connected and automated.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
