Enhanced physics-informed neural networks (PINNs) for high-order power grid dynamics
Fuente:
arXiv
Saved in:
| Main Author: | |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913540056547328 |
|---|---|
| author | Nair, Vineet Jagadeesan |
| author_facet | Nair, Vineet Jagadeesan |
| contents | We develop improved physics-informed neural networks (PINNs) for high-order and high-dimensional power system models described by nonlinear ordinary differential equations. We propose some novel enhancements to improve PINN training and accuracy and also implement several other recently proposed ideas from the literature. We successfully apply these to study the transient dynamics of synchronous generators. We also make progress towards applying PINNs to advanced inverter models. Such enhanced PINNs can allow us to accelerate high-fidelity simulations needed to ensure a stable and reliable renewables-rich future grid. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_07527 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Enhanced physics-informed neural networks (PINNs) for high-order power grid dynamics Nair, Vineet Jagadeesan Machine Learning Systems and Control We develop improved physics-informed neural networks (PINNs) for high-order and high-dimensional power system models described by nonlinear ordinary differential equations. We propose some novel enhancements to improve PINN training and accuracy and also implement several other recently proposed ideas from the literature. We successfully apply these to study the transient dynamics of synchronous generators. We also make progress towards applying PINNs to advanced inverter models. Such enhanced PINNs can allow us to accelerate high-fidelity simulations needed to ensure a stable and reliable renewables-rich future grid. |
| title | Enhanced physics-informed neural networks (PINNs) for high-order power grid dynamics |
| topic | Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2410.07527 |