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2021 IEEE Workshop on Machine Learning for Power Systems (Slides)

Fangxing Fran Li, Jin Zhao, Junbo Zhao, Pengwei Du, Spyros Chatzivasileiadis, C.Y. Chung, Anurag K. Srivastava

  • PES
    Members: Free
    IEEE Members: $11.00
    Non-members: $15.00
    Pages/Slides: 211
Webinar 17 Nov 2021

Machine Learning (ML) has been one of the emerging areas in the community of electric power systems in recent years. In this workshop, leading experts in this area from research and industrial organizations presented six topics related to machine learning for power systems using various techniques in ML such as convolutional neural networks, deep neural networks, physics-inspired deep learning, and performance guarantee in neural networks. These ML techniques were applied to solve a variety of power grid applications including security assessment, optimization, control, grid reliability, transient stability, and event detection and classifications.

Chairs:
Fangxing Fran Li
Primary Committee:
Power System Operation, Planning and Economics Committee (PSOPE)
Sponsor Committees:
Technologies and Innovation Subcommittee, TF on Machine Learning for Power Systems

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