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Found 3 papers, 3 papers with code
Integrating Physics-Informed Neural Networks into Power System Dynamic Simulations
This paper introduces the first natural step to remove the barriers for using PINNs in time-domain simulations: it proposes the first method to integrate PINNs in conventional numerical solvers.
Scalable Bilevel Optimization for Generating Maximally Representative OPF Datasets
However, generating training datasets that accurately represent the many possible combinations of these active constraints is a particularly challenging task, especially within the realm of nonlinear AC Optimal Power Flow (OPF), since most active constraints cannot be enforced explicitly.
Optimization-Based Exploration of the Feasible Power Flow Space for Rapid Data Collection
This paper provides a systematic investigation into the various nonlinear objective functions which can be used to explore the feasible space associated with the optimal power flow problem.
