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2022 IEEE Transactions on Industrial Informatics  
Zheng 305 Deep Belief Network Enabled Surrogate Modeling for Fast Preventive Control of Power System Transient Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  ...  Chen 185 Surrogate-Assisted Cooperation Control of Network-Connected Doubly Fed Induction Generator Wind Farm With Maximized Reactive Power Capacity . . . . . . . . . . . . . . . . . . . . . . . Z.  ... 
doi:10.1109/tii.2021.3113150 fatcat:h3dbl4itlrcophunkw4jstg44y

Analytic Deep Learning-based Surrogate Model for Operational Planning with Dynamic TTC Constraints [article]

Gao Qiu, Youbo Liu, Junyong Liu, Junbo Zhao, Lingfeng Wang, Tingjian Liu, Hongjun Gao
2020 arXiv   pre-print
The increased penetration of wind power introduces more operational changes of critical corridors and the traditional time-consuming transient stability constrained total transfer capability (TTC) operational  ...  The key idea is to resort to the deep learning for developing a computationally cheap surrogate model to replace the original time-consuming differential-algebraic constraints related to TTC.  ...  Thus, the consideration of transient stability constraints in the TTC model is mandatory to prevent the system from instability in the presence of severe faults.  ... 
arXiv:2006.16186v1 fatcat:d7upvtdazrf3fcpc3rirzd56ym

Surrogate‐assisted optimal re‐dispatch control for risk‐aware regulation of dynamic total transfer capability

Gao Qiu, Youbo Liu, Junyong Liu, Lingfeng Wang, Tingjian Liu, Hongjun Gao, Shafqat Jawad
2021 IET Generation, Transmission & Distribution  
set of differential-algebraic equations (DAEs) to verify transient stability constraints.  ...  First, a deep belief network (DBN) is employed to establish the total transfer capability predictor and surrogate the computation-intensive differential-algebraic equations in original optimal power flow  ...  Restricted Boltzmann machine and deep belief network Among quantities of deep learning, deep belief network (DBN) has demonstrated several salient merits, for example, automatic feature selection, raw  ... 
doi:10.1049/gtd2.12147 fatcat:fkciixhxafb43djjoqhxutvaum

A Data-driven Method for Transient Stability Margin Prediction Based on Security Region

Jun An, Jiachen Yu, Zonghan Li, Yibo Zhou, Gang Mu
2020 Journal of Modern Power Systems and Clean Energy  
Transient stability assessment (TSA) based on security region is of great significance to the security of power systems.  ...  In this paper, we propose a novel methodology for the assessment of online transient stability margin.  ...  The development of fast and accurate methodologies for online transient stability assessment (TSA) is one of the major research topics in power system operation and control.  ... 
doi:10.35833/mpce.2020.000457 fatcat:fku5viwtkfe4hpw6eexpigijwe

Artificial Intelligence Techniques for Power System Transient Stability Assessment

Petar Sarajcev, Antonijo Kunac, Goran Petrovic, Marin Despalatovic
2022 Energies  
This has negative repercussions on the transient stability of power systems.  ...  The purpose of this paper is to review the state-of-the-art regarding the application of artificial intelligence to the power system transient stability assessment, with a focus on different machine, deep  ...  Zhou et al. treated the transient stability of a large-scale hybrid AC/DC power grid with the use of deep belief networks [77] .  ... 
doi:10.3390/en15020507 fatcat:xxqdvuydgzadbfsa2mnpmihvmq

2020 Index IEEE Transactions on Power Systems Vol. 35

2020 IEEE Transactions on Power Systems  
., Assessing the Impact of VSC-HVDC on the Interdependence of Power System Dynamic Performance in Uncertain Mixed AC/DC Systems; TPWRS Jan. 2020 63-74 Moeini, A., see Rimorov, D., TPWRS Sept. 2020 3825  ...  ., +, TPWRS May 2020 1695-1706 Preventive-Corrective Coordinated Transient Stability Dispatch of Power Systems With Uncertain Wind Power.  ...  ., +, TPWRS Nov. 2020 4272-4284 Preventive-Corrective Coordinated Transient Stability Dispatch of Power Systems With Uncertain Wind Power.  ... 
doi:10.1109/tpwrs.2020.3040894 fatcat:jjw2rnzr2re6fejvariekzr5uy

2021 Index IEEE Transactions on Power Systems Vol. 36

2021 IEEE Transactions on Power Systems  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., TPWRS July 2021 3153-3162 Delay-Based Decoupling of Power System Models for Transient Stability Analysis.  ... 
doi:10.1109/tpwrs.2021.3125235 fatcat:n3ecyy2flnapzjz7clyrp7sx4a

A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic [article]

Barbara Cunha
2022 arXiv   pre-print
Finally, the so-called ML-based surrogate models provide fast alternatives to costly simulations, enabling robust and optimized product design.  ...  System identification and control design are leveraged by ML techniques in Active Noise Control and Active Vibration Control.  ...  Other important NN architectures that are not discussed here are Boltzmann machines, deep belief networks, and generative adversarial networks.  ... 
arXiv:2204.06362v1 fatcat:ayn6cpcn7nd65hum3z4fspxwrm

2021 Index IEEE Transactions on Industrial Informatics Vol. 17

2021 IEEE Transactions on Industrial Informatics  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  ., +, TII Jan. 2021 596-605 Evolutionary Deep Belief Network for Cyber-Attack Detection in Industrial Automation and Control System.  ... 
doi:10.1109/tii.2021.3138206 fatcat:ulsazxgmpfdmlivigjqgyl7zre

Defense Advanced Research Projects Agency (Darpa) Fiscal Year 2016 Budget Estimates

Department Of Defense Comptroller's Office
2015 Zenodo  
control with fast-switching power modulation.  ...  -Develop a mathematically rigorous virtual stability theory for AI-enabled systems analogous to the (conventional) stability theory developed for dynamical systems.  ... 
doi:10.5281/zenodo.1215366 fatcat:cqn5tyfixjanzp5x3tgfkpedri

Defense Advanced Research Projects Agency (Darpa) Fiscal Year 2015 Budget Estimates

Department Of Defense Comptroller's Office
2014 Zenodo  
DARPA seeks to improve the analysis of large neural data sets by creating interfaces that will allow researchers to generate new models across multiple scales.  ...  The budget request details the proposed investments $80 million to develop new sets of tools for imaging and analytics of neural and synaptic brain activities that will improve diagnosis and care of wounded  ...  -Perform propulsion and power system scaled model bench testing. -Design and develop subscale flight models for configuration viability and control law validation.  ... 
doi:10.5281/zenodo.1215345 fatcat:fjzhmynqjbaafk67q2ckcblj2m

2022 Review of Data-Driven Plasma Science [article]

Rushil Anirudh, Rick Archibald, M. Salman Asif, Markus M. Becker, Sadruddin Benkadda, Peer-Timo Bremer, Rick H.S. Budé, C.S. Chang, Lei Chen, R. M. Churchill, Jonathan Citrin, Jim A Gaffney (+51 others)
2022 arXiv   pre-print
It is now becoming impractical for humans to analyze all the data manually.  ...  Fueled by some of the most challenging problems such as fusion energy, plasma processing of materials, and fundamental understanding of the universe through observable plasma phenomena, it is expected  ...  A variety of function approximators, ranging from polynomials to deep neural networks, have shown promise for approximating optimization-based control laws with surrogates that can be evaluated on fast  ... 
arXiv:2205.15832v1 fatcat:fxsl6gl3fncnhpoj76defxoc3a

2022 Roadmap on Neuromorphic Computing and Engineering [article]

Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano (+47 others)
2022 arXiv   pre-print
This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors.  ...  These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain.  ...  This new class of extremely low-power and lowlatency artificial intelligence systems could, In a world where power-hungry deep learning techniques are becoming a commodity, and at the same time, environmental  ... 
arXiv:2105.05956v3 fatcat:pqir5infojfpvdzdwgmwdhsdi4

Applications and Techniques for Fast Machine Learning in Science [article]

Allison McCarn Deiana, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik, Maurizio Pierini (+74 others)
2021 arXiv   pre-print
In this community review report, we discuss applications and techniques for fast machine learning (ML) in science -- the concept of integrating power ML methods into the real-time experimental data processing  ...  The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for  ...  This would ideally lead to a mature AI-enabled comprehensive control system for ITER and future reactors that feature integration with full pilot-plant system models.  ... 
arXiv:2110.13041v1 fatcat:cvbo2hmfgfcuxi7abezypw2qrm

2021 Index IEEE Transactions on Cybernetics Vol. 51

2021 IEEE Transactions on Cybernetics  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  Zhang, X., +, TCYB July 2021 3616-3629 Belief networks A Joint Graphical Model for Inferring Gene Networks Across Multiple Sub-populations and Data Types.  ... 
doi:10.1109/tcyb.2021.3139447 fatcat:myjx3olwvfcfpgnwvbuujwzyoi
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