Realizable machine learning in resilient power grids: from lab developments to industrial applications
Goran Strbac, Zhaoyu Wang, Hong Chen, Akansha Jain, Jin Zhao, Yannan Sun
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PES
IEEE Members: $25.00
Non-members: $40.00Pages/Slides: 15
In recent years, significant efforts have been devoted to developing machine learning (ML) techniques for efficient and resilient powers system operation and control. Although the academic side has developed various advanced techniques, there is still a gap between lab-based ML and industrial applications. In this panel, the focus will be given to the existing gap between academic ML research and real-world application, and the possible solutions. Advanced lab-based ML techniques, the current ML application situation, and the needs from the industrial side will be highlighted in this panel. Experts from USA, UK, Germany, Sweden and Ireland, both academia and industry, will share their original ideas and insights to this challenging and inspiring topic.
Chairs:
Jin Zhao, Bo Chen
Primary Committee:
PSOPE – Bulk Power System Operations Subcommittee