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Interpreted as:

title:(Capturing AND Power AND System AND Dynamics AND by AND Physics-Informed AND Neural AND Networks AND and AND Optimization)

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1 Conference paper

Capturing Power System Dynamics by Physics-Informed Neural Networks and Optimization

This paper proposes a tractable framework to determine key characteristics of non-linear dynamic systems by converting physics-informed neural networks to a mixed integer linear program. Our focus is on power system applications. Traditional methods in power systems require the use of a large

Year: 2021

Language: English

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2 Conference paper

Capturing Power System Dynamics by Physics-Informed Neural Networks and Optimization

Misyris, Georgios S.; Stiasny, Jochen; Chatzivasileiadis, Spyros

Proceedings of 60<sup>th</sup> Ieee Conference on Decision and Control — 2021, pp. 4418-4423

This paper proposes a tractable framework to determine key characteristics of non-linear dynamic systems by converting physics-informed neural networks to a mixed integer linear program. Our focus is on power system applications. Traditional methods in power systems require the use of a large

Year: 2021

Language: English

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3 Preprint article

Capturing Power System Dynamics by Physics-Informed Neural Networks and Optimization

This paper proposes a tractable framework to determine key characteristics of non-linear dynamic systems by converting physics-informed neural networks to a mixed integer linear program. Our focus is on power system applications. Traditional methods in power systems require the use of a large

Year: 2021

Language: Undetermined

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