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Fast Inverter Control by Learning the OPF Mapping using Sensitivity-Informed Gaussian Processes
Adjusting inverter injection setpoints for distributed energy resources can be an effective grid control mechanism.
Inferring power system dynamics from synchrophasor data using Gaussian processes
Synchrophasor data provide unprecedented opportunities for inferring power system dynamics, such as estimating voltage angles, frequencies, and accelerations along with power injection at all buses.
Kernel-Based Learning for Smart Inverter Control
Leveraging a linearized grid model and given anticipated data scenarios, inverter rules are jointly designed at the feeder level to minimize a convex combination of voltage deviations and ohmic losses via a linearly-constrained quadratic program.
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