Deep Reinforcement Learning for Power System Stability Control and Operation

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Event Details
  • Date/Time:
    • Thursday October 21, 2021
      11:00 am - 12:00 pm
  • Location: Online
  • Phone:
  • URL:
  • Email:
  • Fee(s):
    N/A
  • Extras:
Contact

Luke Harrison

Summaries

Summary Sentence: Join us to find out about Deep Reinforcement Learning (DRL) and its application to Power Systems Operation and Control, the drawbacks, and the solutions.

Full Summary: Join us to find out about Deep Reinforcement Learning (DRL) and its application to Power Systems Operation and Control, the drawbacks, and the solutions.  

Hosted by IEEE PES

Join us to find out about Deep Reinforcement Learning (DRL) and its application to Power Systems Operation and Control, the drawbacks, and the solutions.  

DRL has been extensively applied in domains such as gaming and robotics, but has issues with sample inefficiency, scalability, adaptability and trustworthiness. Dr. Huang will share their work on development of new DRL algorithms using physical understanding of the grid, and tools for power system emergency control and corrective operation.

Dr. Qiuhua Huang is currently a senior power system research engineer at Pacific Northwest National Laboratory (PNNL). He leads and manages several U.S. DOE-funded projects, including a major ARPA-E OPEN project on intelligent real-time grid emergency control.

Online Location: https://gatech.webex.com/gatech/j.php?MTID=m0af9065fc3aeb183565a7148d6fefbfa

Additional Information

In Campus Calendar
Yes
Groups

General

Invited Audience
Graduate students, Undergraduate students
Categories
Student sponsored
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Status
  • Created By: Kristen Bailey
  • Workflow Status: Published
  • Created On: Oct 18, 2021 - 8:43pm
  • Last Updated: Oct 18, 2021 - 8:43pm