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20212024
most citedData-Driven Estimation of Failure Probabilities in Correlated Structure-Preserving Stochastic Power System Models

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.CE20241 cited

Data-Driven Estimation of Failure Probabilities in Correlated Structure-Preserving Stochastic Power System Models

Hongli Zhao, Tyler E. Maltba, D. Adrian Maldonado +2

We propose a data-driven approach for propagating uncertainty in stochastic power grid simulations and apply it to the estimation of transmission line failure probabilities. A redu…

math.OC2023

Centralized calibration of power system dynamic models using variational data assimilation

Ahmed Attia, D. Adrian Maldonado, Emil Constantinescu +1

This paper presents a novel centralized, variational data assimilation approach for calibrating transient dynamic models in electrical power systems, focusing on load model paramet…

math.OC2023

Efficient Computation of Power System Maximum Transient Linear Growth

Daniel Adrian Maldonado, Emil Constantinescu, Junbo Zhao +1

Existing methods to determine the stability of a power system to small perturbations are based on eigenvalue analysis and focus on the asymptotic (long-term) behavior of the power…

math.NA2021

Implicit Extensions of an Explicit Multirate Runge-Kutta Scheme

Emil M. Constantinescu

We propose a new method that extends conservative explicit multirate methods to implicit explicit-multirate methods. We develop extensions of order one and two with different stabi…

math.DS2021

Efficient high-dimensional variational data assimilation with machine-learned reduced-order models

Romit Maulik, Vishwas Rao, Jiali Wang +6

Data assimilation (DA) in the geophysical sciences remains the cornerstone of robust forecasts from numerical models. Indeed, DA plays a crucial role in the quality of numerical we…