Physics-informed neural network for dynamic energy flow calculation in integrated electricity and gas systems

@article{shangyang2026,
  title        = {{Physics-informed neural network for dynamic energy flow calculation in integrated electricity and gas systems}},
  author       = {Shangyang He et al.},
  journal      = {Applied Energy},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.apenergy.2026.127374},
}

TY  - JOUR
TI  - Physics-informed neural network for dynamic energy flow calculation in integrated electricity and gas systems
AU  - al., Shangyang He et
JO  - Applied Energy
PY  - 2026
ER  -

Shangyang He et al. (2026). Physics-informed neural network for dynamic energy flow calculation in integrated electricity and gas systems. *Applied Energy*. https://doi.org/https://doi.org/10.1016/j.apenergy.2026.127374

Shangyang He et al.. "Physics-informed neural network for dynamic energy flow calculation in integrated electricity and gas systems." *Applied Energy* (2026). https://doi.org/https://doi.org/10.1016/j.apenergy.2026.127374.

Physics-informed neural network for dynamic energy flow calculation in integrated electricity and gas systems
Shangyang He et al. · Applied Energy · 2026
https://doi.org/https://doi.org/10.1016/j.apenergy.2026.127374