Paper Citation Record · LEDGER

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI

As of 10 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2607.03485.

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pith.paper-citation-record.v1
2607.03485 v1

Coverage vector

measured 43 of 43 reference resolution

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Outbound references

Observation bb0c1f53-ffca-42bd-829d-4a9b6a487fd6 · outbound

This paper cites The renewable energy role in the global energy transformations,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI The renewable energy role in the global energy transformations,

Reference 1

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Observation af2884f8-15cf-4cd0-8716-d332037c7ac8 · outbound

This paper cites Eremia and M.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Eremia and M

Reference 2

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Observation 1c4dc067-4f60-431e-a21b-b599495b261d · outbound

This paper cites Final report on the grid incident in spain and portugal on 28 april 2025,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Final report on the grid incident in spain and portugal on 28 april 2025,

Reference 3

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Observation 391f70be-a40b-4f98-afef-409706d51783 · outbound

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Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Unresolved cited work

Reference 4

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Observation 5341b033-7d85-4d7e-bff0-c0b55673ef0d · outbound

This paper cites Definition and classification of power system stability–revisited & extended,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Definition and classification of power system stability–revisited & extended,

Reference 5

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Observation e7f53316-5ddd-4ad5-afa2-14e74d3148e0 · outbound

This paper cites Kundur,Power System Stability and Control.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Kundur,Power System Stability and Control

Reference 6

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Observation b43a5cc2-0330-4992-920d-95e76032831c · outbound

This paper cites Countdown to Collapse: Stability Dynamics Ob- served Before the 2025 Iberian Power System Blackout,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Countdown to Collapse: Stability Dynamics Ob- served Before the 2025 Iberian Power System Blackout,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-12T02:10:46.137764Z

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Observation 5eea8fa6-34a5-420e-a402-8ecf9d64f53c · outbound

This paper cites Marconato,Electric Power Systems - Vol.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Marconato,Electric Power Systems - Vol

Reference 8

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Observation a2637598-e057-49a5-aae2-9320618df1ad · outbound

This paper cites Sendai: A hierarchical sparse-measurement, efficient data assimilation framework,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Sendai: A hierarchical sparse-measurement, efficient data assimilation framework,

Reference 9

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Observation a7a59cbd-0d0b-42fa-87c4-312ced25b2f0 · outbound

This paper cites Discovering governing equations from data by sparse identification of nonlinear dynamical systems,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Discovering governing equations from data by sparse identification of nonlinear dynamical systems,

Reference 10

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Observation 59f5a3eb-c1cd-49b9-964a-3ce74a289835 · outbound

This paper cites Parsimony as the ultimate regularizer for physics-informed machine learning,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Parsimony as the ultimate regularizer for physics-informed machine learning,

Reference 11

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Observation 07fa06bb-f033-44b6-ae67-87024d2efc76 · outbound

This paper cites Estimation of inter-area modes during ambient operation using the Eigen-system realization algorithm,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Estimation of inter-area modes during ambient operation using the Eigen-system realization algorithm,

Reference 12

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Observation ab053cf1-2a35-44dc-beae-e86f2a1752a7 · outbound

This paper cites New signal subspace approach to estimate the inter-area oscillatory modes in power system using TLS-ESPRIT algorithm,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI New signal subspace approach to estimate the inter-area oscillatory modes in power system using TLS-ESPRIT algorithm,

Reference 13

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Observation a45df512-ab9d-48ae-acaa-8b96a19e6493 · outbound

This paper cites An adaptive tls-esprit algorithm based on an s-g filter for analysis of low frequency oscillation in wide area measurement systems,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI An adaptive tls-esprit algorithm based on an s-g filter for analysis of low frequency oscillation in wide area measurement systems,

Reference 14

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Observation 927ae848-d5b7-4a3e-a373-c25a2dfb8ba7 · outbound

This paper cites Real-time tracking of electromechanical oscilla- tions in ENTSO-e continental european synchronous area,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Real-time tracking of electromechanical oscilla- tions in ENTSO-e continental european synchronous area,

Reference 15

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Observation 47f2acfb-0b09-4628-bd8d-b88c514a9e18 · outbound

This paper cites Use of ARMA block processing for estimating stationary low-frequency electromechanical modes of power systems,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Use of ARMA block processing for estimating stationary low-frequency electromechanical modes of power systems,

Reference 16

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Observation efb556c4-194e-4b4d-a097-3be1b4c30520 · outbound

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Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Unresolved cited work

Reference 17

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Observation 8525964e-bd5a-493c-8ebd-7c31ea127115 · outbound

This paper cites A dynamic mode decomposition framework for global power system oscillation analysis,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI A dynamic mode decomposition framework for global power system oscillation analysis,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-12T02:10:46.137764Z

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Observation 870c9316-e75f-44be-835e-83ff9e7a8615 · outbound

This paper cites Practical implementation and operational experience of dynamic mode decomposition in wide-area monitoring systems of italian power system,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Practical implementation and operational experience of dynamic mode decomposition in wide-area monitoring systems of italian power system,

Reference 19

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Observation aed38916-be7d-4557-be26-d23f5d45c343 · outbound

This paper cites A review of machine learning approaches to power system security and stability,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI A review of machine learning approaches to power system security and stability,

Reference 20

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Observation fef6358c-eecc-4b30-9d8c-c25784a54ef9 · outbound

This paper cites A unified online deep learning prediction model for small signal and transient stability,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI A unified online deep learning prediction model for small signal and transient stability,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-12T02:10:46.137764Z

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Observation 7ab6c517-4043-4c6d-bdb8-17c26ef61732 · outbound

This paper cites Identification of oscillatory modes in power system using deep learning approach,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Identification of oscillatory modes in power system using deep learning approach,

Reference 22

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Observation 38980156-93f4-4723-945f-df8bc5bbe627 · outbound

This paper cites Deep learning-based models for predicting poorly damped low-frequency modes of oscillations,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Deep learning-based models for predicting poorly damped low-frequency modes of oscillations,

Reference 23

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Observation 7c2aa467-40f4-4f13-83cd-78b7e3f438fb · outbound

This paper cites A data-driven method for fast and accurate identifica- tion of the wideband oscillations in renewable power systems,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI A data-driven method for fast and accurate identifica- tion of the wideband oscillations in renewable power systems,

Reference 24

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Observation 34185c60-6b7d-4c20-bd7b-4f583433ccc0 · outbound

This paper cites A machine learning-based framework for fast prediction of wide-area remedial control actions in interconnected power systems,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI A machine learning-based framework for fast prediction of wide-area remedial control actions in interconnected power systems,

Reference 25

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Observation ff05067b-1b88-4882-883a-c5b6a28cbe76 · outbound

This paper cites An online data-driven method to locate forced oscillation sources from power plants based on sparse identification of nonlinear dynamics (SINDy),.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI An online data-driven method to locate forced oscillation sources from power plants based on sparse identification of nonlinear dynamics (SINDy),

Reference 26

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Observation 7c2ff6d7-8167-4dfe-bb1d-6f5294abb1e2 · outbound

This paper cites Deep reinforcement learning-based approach for proportional resonance power system stabilizer to prevent ultra-low-frequency oscillations,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Deep reinforcement learning-based approach for proportional resonance power system stabilizer to prevent ultra-low-frequency oscillations,

Reference 27

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Observation 3d3095e0-7b2d-413b-b225-f1d592ee72eb · outbound

This paper cites Measurement-driven damping control based on the deep transfer reinforcement learning to suppress sub-synchronous oscillations in a large-scale renewable power system,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Measurement-driven damping control based on the deep transfer reinforcement learning to suppress sub-synchronous oscillations in a large-scale renewable power system,

Reference 28

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Observation 5a1fe014-a41b-433b-9602-46fa4f6785dd · outbound

This paper cites Fractional order pid-pss design using hybrid deep learning approach for damping power system oscillations,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Fractional order pid-pss design using hybrid deep learning approach for damping power system oscillations,

Reference 29

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Observation 80d5100e-604e-4c00-b7d5-a39cc987e6d1 · outbound

This paper cites Frequency-adaptive power system modeling for multiscale simulation of transients,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Frequency-adaptive power system modeling for multiscale simulation of transients,

Reference 30

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Observation 66aedebf-9490-4678-8f83-9f28ee8978f3 · outbound

This paper cites Multi-resolution dynamic mode decomposition for foreground/background separation and object tracking,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Multi-resolution dynamic mode decomposition for foreground/background separation and object tracking,

Reference 31

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Observation 8af26f31-047e-4786-aaf2-b2bd4b81f4b8 · outbound

This paper cites Discovering time-varying aerodynamics of a prototype bridge by sparse identification of nonlinear dynamical systems,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Discovering time-varying aerodynamics of a prototype bridge by sparse identification of nonlinear dynamical systems,

Reference 32

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Observation 91b6d5da-9567-4738-84ba-274a79902ac3 · outbound

This paper cites Sensing with shallow recurrent decoder networks,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Sensing with shallow recurrent decoder networks,

Reference 33

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This paper cites A Shallow Recurrent Decoder for Dynamic State Estimation with a Limited Number of PMUs in Power Systems.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI A Shallow Recurrent Decoder for Dynamic State Estimation with a Limited Number of PMUs in Power Systems

Reference 34

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Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Detecting strange attractors in turbulence,

Reference 35

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Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Sparse identification of nonlinear dynamics and koopman operators with shallow recurrent decoder networks,

Reference 36

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Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Gate-variants of gated recurrent unit (gru) neural networks,

Reference 37

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Observation d64af424-a098-4ad8-a0fe-13cd3417c791 · outbound

This paper cites Learning phrase representations using rnn encoder– decoder for statistical machine translation,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Learning phrase representations using rnn encoder– decoder for statistical machine translation,

Reference 38

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Observation 07111f5a-1a94-47a8-99c6-bb3a4be786d5 · outbound

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Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Data-driven discovery of coordinates and governing equations,

Reference 39

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Observation ca025e64-6efa-48e6-a800-e4289e01b3ef · outbound

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Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Bayesian autoencoders for data- driven discovery of coordinates, governing equations and fundamental constants,

Reference 40

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Observation 2ef94960-5eed-4b73-8e6d-3f615c1d8845 · outbound

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Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Passive mode-locking by use of waveguide arrays,

Reference 41

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Observation e816afd0-c3d2-4e16-882c-6d8f6cc956ef · outbound

This paper cites A survey of convolutional neural networks: analysis, applications, and prospects,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI A survey of convolutional neural networks: analysis, applications, and prospects,

Reference 42

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Observation 8b7402b2-e34c-4ca4-8565-181096ee475f · outbound

This paper cites Analysis of CE inter-area oscillation of 1st December 2016,.

Data-Driven Discovery of Multiscale Power System Oscillation Governing Equations Using SINDy-SENDAI Analysis of CE inter-area oscillation of 1st December 2016,

Reference 43

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