Artificial Neural Network-Based Nonlinear Black-Box Modeling of Synchronous Generators-Reference-Cited by-同舟云学术

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Artificial Neural Network-Based Nonlinear Black-Box Modeling of Synchronous Generators

Published:2023-03 Issue:3 Volume:19 Page:2826-2837
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Micev Mihailo¹^ORCID,Ćalasan Martin¹^ORCID,Radulović Milovan¹,Aleem Shady H. E. Abdel²^ORCID,Hasanien Hany M.³^ORCID,Zobaa Ahmed F.⁴^ORCID

Affiliation:

1. Faculty of Electrical Engineering, University of Montenegro, Podgorica, Montenegro

2. Valley High Institute of Engineering and Technology, Qalyubia, Egypt

3. Faculty of Engineering, Ain Shams University, Cairo, Egypt

4. Electronic and Electrical Engineering Department, Brunel University London, Uxbridge, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/9424/10064202/09813409.pdf?arnumber=9813409

Reference30 articles.

1. An Adaptive Bayesian Parameter Estimation of a Synchronous Generator Under Gross Errors

2. Synchronous machine model parameters estimation by a time-domain identification method

3. Constrained Iterated Unscented Kalman Filter for Dynamic State and Parameter Estimation

4. Robust Cubature Kalman Filter for Dynamic State Estimation of Synchronous Machines Under Unknown Measurement Noise Statistics

5. Neural Networks for Modelling and Control of Dynamic Systems

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3. Methods for Determining Losses and Parameters of Cylindrical-Rotor Medium-Power Synchronous Generators;Electronics;2024-07-14

4. Black-Box Modeling of Synchronous Generators Using Feedforward Neural Networks;2023 22nd International Symposium on Power Electronics (Ee);2023-10-25

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