A new open-source toolbox trains physics-informed neural networks for power system components and demonstrates a 9th-order synchronous machine with AVR and governor, reaching 2.26e-3 mean absolute error with fast inference.
Artificial neural networks for solving ordinary and partial differential equations,
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Toolbox for Developing Physics Informed Neural Networks for Power Systems Components
A new open-source toolbox trains physics-informed neural networks for power system components and demonstrates a 9th-order synchronous machine with AVR and governor, reaching 2.26e-3 mean absolute error with fast inference.