Novel Data-Driven Distributed Learning Framework for Solving AC Power Flow for Large Interconnected Systems

Novel Data-Driven Distributed Learning Framework for Solving AC Power Flow for Large Interconnected Systems

Recent advancement in power systems induces complexity in large-scale interconnected systems and poses challenges in performing security assessment studies at various operating conditions. Traditional model-based methods are computationally intensive and may not meet the requirements for real-time a...

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Bibliographic Details
Main Authors: Bharat Vyakaranam, Kaveri Mahapatra, Xinya Li, Heng Wang, Pavel Etingov, Zhangshuan Hou, Quan Nguyen, Tony Nguyen, Nader Samaan, Marcelo Elizondo, Todd Hay
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Access Journal of Power and Energy
Subjects:
Contingency screening
security assessment
deep convolutional neural networks (DCNNs)
feature selection
machine learning (ML)
deep learning (DL)
Online Access:https://ieeexplore.ieee.org/document/9468991/

Internet

https://ieeexplore.ieee.org/document/9468991/

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