Abstract—Transient (rotor-angle) stability under severe disturbances is critical for the secure operation of modern power systems. Increasing uncertainty associated with operating conditions necessitates probabilistic approaches beyond conventional deterministic simulations. This paper proposes a probabilistic transient stability assessment framework based on repeated electrodynamic physical experiments interpreted as a physical implementation of the Monte Carlo process. Single-machine and multi-machine systems are investigated under three-phase short circuits and varying power transfer levels. The maximum rotor angle deviation is treated as a random variable, and its statistical characteristics are evaluated. The results show that the dispersion of rotor-angle responses increases from approximately 2–4% under moderate operating conditions to significantly higher values near the stability boundary, with an additional 25–30% increase observed in multi-machine systems due to inter-machine coupling effects. This leads to widening confidence intervals and a transition from deterministic to probabilistic stability margins. The proposed framework provides experimentally derived probabilistic characteristics for validation of Electromagnetic Transient(EMT)and Root Mean Square (RMS)simulation tools and supports uncertainty-aware transient stability assessment and risk-informed power system operation.

Index Terms—transientstability, probabilistic assessment, electrodynamic physical modeling, Monte Carlo method, rotor angle deviation, uncertainty quantification, power systems, multi-machine systems

Cite: Sona V. Rzayeva, Nijat S. Mammadov, Ilduza A. Guseynova, Mirfatma M. Javadova, Gulaga A. Aleskerov, and Abderrahim Zemmit, "A Physical Monte Carlo Framework for Probabilistic Transient Stability Assessment of Power Systems," International Journal of Electrical and Electronic Engineering & Telecommunications, vol. 15, no. 5, pp. 357-366, 2026. doi: 10.18178/ijeetc.15.5.357-366

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).