Learning goals¶
See how the three book applications connect in one operating-point loop
Distinguish finished teaching labs from a long-horizon digital-twin programme
Avoid claiming a finished twin or protection-grade automation
Reading¶
The three applications in one loop¶
Identification → calibrated parameters / model
↓
Dynamics → fast trajectories (simulator or SciML surrogate)
↓
Stability → TSA label and CCT (or other) margin
↓
Decision → contingency screen, planning study, operator attentionLabs practice pieces of this loop on a transparent SMIB plant:
| Piece | Typical lab |
|---|---|
| Reference trajectories | Lab 1 |
| Surrogate vs physics-informed forward model | Lab 2 |
| Parameter recovery | Lab 3 |
| Learned dynamics generalization | Lab 4 |
| CCT and false-safe honesty | Lab 5 |
Building toward a measurement-informed twin¶
A grid digital twin, in this teaching sense, is a living model of the dynamics, not a 3D plant replica:
Grid / PMU-like measurements
→ parameter / model update (Identification)
→ dynamic model
→ physics-informed or hybrid surrogate (Dynamics)
→ security margins such as CCT (Stability)
→ operator-facing or planning decisionThat programme is a long-term research direction. Published teaching evidence in this book is strongest on Foundations + classical SMIB SciML tasks. Treat the twin loop as aspiration and synthesis, not as a claim that the course already ships a twin.
Honesty rules¶
Finite-horizon CCT searches are planning-oriented unless otherwise certified.
Surrogates inherit the criterion and plant of their training / reference data.
Converter-rich and cyber-physical extensions belong in later electives after Labs 1–5 run.
Further reading¶
Stability: CCT, surrogates, direct methods
Stability definitions Kundur et al., 2004Hatziargyriou et al., 2021; optional research code Poulose, 2026
Common misconceptions¶
“Digital twin means a visualization of substations.”
“Finishing Lab 5 means the twin loop is done.”
Collapsing binary TSA accuracy with operational margin decisions.
- Kundur, P., Paserba, J., Ajjarapu, V., Andersson, G., Bose, A., Canizares, C., Hatziargyriou, N., Hill, D. J., Stankovic, A., Taylor, C., Van Cutsem, T., & Vittal, V. (2004). Definition and Classification of Power System Stability IEEE/CIGRE Joint Task Force on Stability Terms and Definitions. IEEE Transactions on Power Systems, 19(3), 1387–1401. 10.1109/TPWRS.2004.825981
- Hatziargyriou, N., Milanovic, J., Rahmann, C., Ajjarapu, V., Canizares, C., Erlich, I., Hill, D., Hiskens, I., Kamwa, I., Pal, B., Pourbeik, P., Sanchez-Gasca, J., Stankovic, A., Van Cutsem, T., Vittal, V., & Vournas, C. (2021). Definition and Classification of Power System Stability – Revisited & Extended. IEEE Transactions on Power Systems, 36(4), 3271–3281. 10.1109/TPWRS.2020.3041774
- Poulose, A. (n.d.). Unified physics-informed neural surrogate SMIB TSA/CCT benchmark. GitHub repository. Retrieved October 14, 2026, from https://github.com/albert8943/unified-physics-informed-neural-surrogate-smib-tsa-cct-benchmark