A data-driven dynamic model for inverter-based resources in power grids is proposed, which couples neural networks with a physical inverter interface, enabling the model output to follow physical laws and significantly improving the accuracy of grid stability studies.
- Ke Yang
- Xin Wang
- Quanyuan Jiang
