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Marcos Netto
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Power system dynamic state estimation: Motivations, definitions, methodologies, and future work
J Zhao, A Gómez-Expósito, M Netto, L Mili, A Abur, V Terzija, I Kamwa, ...
IEEE Transactions on Power Systems 34 (4), 3188-3198, 2019
5842019
A robust iterated extended Kalman filter for power system dynamic state estimation
J Zhao, M Netto, L Mili
IEEE Transactions on Power Systems 32 (4), 3205-3216, 2016
4172016
Roles of dynamic state estimation in power system modeling, monitoring and operation
J Zhao, M Netto, Z Huang, SS Yu, A Gómez-Expósito, S Wang, I Kamwa, ...
IEEE Transactions on Power Systems 36 (3), 2462-2472, 2020
1542020
Power system inertia estimation: Review of methods and the impacts of converter-interfaced generations
B Tan, J Zhao, M Netto, V Krishnan, V Terzija, Y Zhang
International Journal of Electrical Power & Energy Systems 134, 107362, 2022
1112022
A robust data-driven Koopman Kalman filter for power systems dynamic state estimation
M Netto, L Mili
IEEE Transactions on Power Systems 33 (6), 7228-7237, 2018
1102018
Data-driven participation factors for nonlinear systems based on Koopman mode decomposition
M Netto, Y Susuki, L Mili
IEEE Control Systems Letters 3 (1), 198-203, 2018
492018
A robust extended Kalman filter for power system dynamic state estimation using PMU measurements
M Netto, J Zhao, L Mili
2016 IEEE Power and Energy Society General Meeting (PESGM), 1-5, 2016
422016
Robust data filtering for estimating electromechanical modes of oscillation via the multichannel prony method
M Netto, L Mili
IEEE Transactions on Power Systems 33 (4), 4134-4143, 2017
372017
On Analytical Construction of Observable Functions in Extended Dynamic Mode Decomposition for Nonlinear Estimation and Prediction
M Netto, Y Susuki, V Krishnan, Y Zhang
IEEE Control Systems Letters 5 (6), 1868-1873, 2021
352021
A robust prony method for power system electromechanical modes identification
M Netto, L Mili
2017 IEEE Power & Energy Society General Meeting, 1-5, 2017
312017
Robust Koopman operator-based Kalman filter for power systems dynamic state estimation
M Netto, L Mili
2018 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2018
222018
State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data
FRS Sevilla, Y Liu, E Barocio, P Korba, M Andrade, F Bellizio, J Bos, ...
International Journal of Electrical Power & Energy Systems 137, 107772, 2022
182022
Robust Dynamic Mode Decomposition
AH Abolmasoumi, M Netto, L Mili
IEEE Access 10, 65473-65484, 2022
102022
A hybrid framework combining model-based and data-driven methods for hierarchical decentralized robust dynamic state estimation
M Netto, V Krishnan, L Mili, Y Susuki, Y Zhang
2019 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2019
102019
Robust identification, estimation, and control of electric power systems using the Koopman operator-theoretic framework
M Netto
Virginia Tech, 2019
102019
Automated construction of clear-sky dictionary from all-sky imager data
P Shaffery, A Habte, M Netto, A Andreas, V Krishnan
Solar Energy 212, 73-83, 2020
82020
Propagating Parameter Uncertainty in Power System Nonlinear Dynamic Simulations Using a Koopman Operator-Based Surrogate Model
Y Xu, M Netto, L Mili
IEEE Transactions on Power Systems 37 (4), 3157-3160, 2022
62022
Measurement placement in electric power transmission and distribution grids: Review of concepts, methods, and research needs
M Netto, V Krishnan, Y Zhang, L Mili
IET Generation, Transmission & Distribution 16 (5), 805-838, 2022
62022
Real-time modal analysis of electric power grids–the need for dynamic state estimation
M Netto, V Krishnan, L Mili, P Sharma, V Ajjarapu
2020 International Conference on Probabilistic Methods Applied to Power …, 2020
42020
A general decentralized dynamic state estimation with synchronous generator magnetic saturation
B Tan, J Zhao, M Netto
IEEE Transactions on Power Systems 38 (1), 960-963, 2022
32022
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