An Adaptive Dynamic Model for Reducing the Size of A Power System for Large Variations in the Operating Point using LSTM RNNs

Aththanayake, L; Hosseinzadeh, N; Gargoom, Ameen; Ranaweera, Kanishka; Pathirana, Pubudu

An Adaptive Dynamic Model for Reducing the Size of A Power System for Large Variations in the Operating Point using LSTM RNNs

conference contribution

posted on 2025-04-15, 22:44 authored by L Aththanayake, N Hosseinzadeh, Ameen GargoomAmeen Gargoom, Kanishka RanaweeraKanishka Ranaweera, Pubudu PathiranaPubudu Pathirana

An Adaptive Dynamic Model for Reducing the Size of A Power System for Large Variations in the Operating Point using LSTM RNNs

History

Volume

00

Pagination

1-6

Location

Wollongong, N.S.W

Start date

2023-12-03

End date

2023-12-06

ISBN-13

9781665471640

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

ETFG 2023 : Proceedings of the 2023 IEEE International Conference on Energy Technologies for Future Grids

Event

Energy Technologies for Future Grids. Conference (2023 : Wollongong, N.S.W)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Publication URL

http://dx.doi.org/10.1109/etfg55873.2023.10407684

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An Adaptive Dynamic Model for Reducing the Size of A Power System for Large Variations in the Operating Point using LSTM RNNs

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