233 citations · 428 across the 11 of their papers we have counts for
7 papers · 1 filter
Stiffness-Aware Decentralized Dynamic State Estimation for Inverter-Dominated Power Systems
Xingyu Zhao, Marcos Netto, Junbo Zhao
Dynamic state estimation (DSE) is becoming increasingly important for monitoring inverter-dominated power systems. Due to their cascading control structures, inverter-based resourc…
Propagating Parameter Uncertainty in Power System Nonlinear Dynamic Simulations Using a Koopman Operator-Based Surrogate Model
Yijun Xu, Marcos Netto, Lamine Mili
We propose a Koopman operator-based surrogate model for propagating parameter uncertainties in power system nonlinear dynamic simulations. First, we augment the a priori known stat…
A mode-in-state contribution factor based on Koopman operator and its application to power system analysis
Kenji Takamichi, Yoshihiko Susuki, Marcos Netto +1
This paper proposes a mode-in-state contribution factor for a class of nonlinear dynamical systems by utilizing spectral properties of the Koopman operator and sensitivity analysis…
Measurement placement in electric power transmission and distribution grids: Review of concepts, methods, and research needs
Marcos Netto, Venkat Krishnan, Yingchen Zhang +1
Sensing and measurement systems are quintessential to the safe and reliable operation of electric power grids. Their strategic placement is of ultimate importance because it is not…
A robust extended Kalman filter for power system dynamic state estimation using PMU measurements
Marcos Netto, Junbo Zhao, Lamine Mili
This paper develops a robust extended Kalman filter to estimate the rotor angles and the rotor speeds of synchronous generators of a multimachine power system. Using a batch-mode r…
On analytical construction of observable functions in extended dynamic mode decomposition for nonlinear estimation and prediction
Marcos Netto, Yoshihiko Susuki, Venkat Krishnan +1
We propose an analytical construction of observable functions in the extended dynamic mode decomposition (EDMD) algorithm. EDMD is a numerical method for approximating the spectral…
Data-Driven Participation Factors for Nonlinear Systems Based on Koopman Mode Decomposition
Marcos Netto, Yoshihiko Susuki, Lamine Mili
This paper develops a novel data-driven technique to compute the participation factors for nonlinear systems based on the Koopman mode decomposition. Provided that certain conditio…