Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Netto, Marcos"'
We devise a novel formulation and propose the concept of modal participation factors to nonlinear dynamical systems. The original definition of modal participation factors (or simply participation factors) provides a simple yet effective metric. It f
Externí odkaz:
http://arxiv.org/abs/2409.10105
Autor:
Netto, Marcos
The study of nonlinear dynamical systems via the spectrum of the Koopman operator has emerged as a paradigm shift, from the Poincaré's geometric picture that centers the attention on the evolution of states, to the Koopman operator's picture that fo
Externí odkaz:
http://hdl.handle.net/10919/87728
Publikováno v:
in IEEE Transactions on Power Systems, vol. 37, no. 4, pp. 3157-3160, July 2022
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 state-space model by reformulating parameters deemed uncertain as pseudo-s
Externí odkaz:
http://arxiv.org/abs/2304.00147
Publikováno v:
Nonlinear Theory and Its Applications, IEICE, vol. 13, issue 2, pp. 409-414, 2022
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. Using eigenfunctions of the Koopman operator for a target nonlinear
Externí odkaz:
http://arxiv.org/abs/2205.10984
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 economically viable to install measurement systems on every node and
Externí odkaz:
http://arxiv.org/abs/2105.14917
This paper develops a robust dynamic mode decomposition (RDMD) method endowed with statistical and numerical robustness. Statistical robustness ensures estimation efficiency at the Gaussian and non-Gaussian probability distributions, including heavy-
Externí odkaz:
http://arxiv.org/abs/2105.09869
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 regression form, the filter processes together predicted state vector a
Externí odkaz:
http://arxiv.org/abs/2104.02045
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 properties of the Koopman operator. The choice of observable function
Externí odkaz:
http://arxiv.org/abs/2008.12874
Autor:
Zhao, Junbo, Netto, Marcos, Huang, Zhenyu, Yu, Samson Shenglong, Gomez-Exposito, Antonio, Wang, Shaobu, Kamwa, Innocent, Akhlaghi, Shahrokh, Mili, Lamine, Terzija, Vladimir, Meliopoulos, A. P. Sakis, Pal, Bikash, Singh, Abhinav Kumar, Abur, Ali, Bi, Tianshu, Rouhani, Alireza
Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time-synchronized measurements, and the advances in the capability, scalabilit
Externí odkaz:
http://arxiv.org/abs/2005.05380
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 conditions are satisfied, it is shown that the proposed technique generalizes
Externí odkaz:
http://arxiv.org/abs/1806.01344