Real-time congestion control using cascaded LSTM deep neural networks for deregulated power markets

Real-time congestion control using cascaded LSTM deep neural networks for deregulated power markets

Abstract In deregulated power markets (DPMs), transmission-line congestion has become more severe and frequent than in traditional power systems. This congestion hinders electricity markets from operating in normal competitive equilibrium. The independent system operator (ISO) is responsible for imp...

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Bibliographic Details
Main Authors: G. Madhu Mohan, T. Anil Kumar, A. Srujana, Yasser Fouad, Alexey Mikhaylov, Nora Baranyai, Kitmo, Ch. Rami Reddy
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Congestion management
Long-term short memory
Deep neural network
Generation rescheduling
Optimization
Deregulation
Online Access:https://doi.org/10.1038/s41598-025-14640-6
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https://doi.org/10.1038/s41598-025-14640-6

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