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  <title><![CDATA[Deep Reinforcement Learning for Power System Stability Control and Operation]]></title>
  <body><![CDATA[<p>Join us to find out about Deep Reinforcement Learning (DRL) and its application to Power Systems Operation and Control, the drawbacks, and the solutions.&nbsp;&nbsp;</p>

<p>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&nbsp;development of new DRL algorithms using physical understanding of the grid, and tools for power system emergency control and corrective operation.&nbsp;</p>

<p>Dr.&nbsp;Qiuhua&nbsp;Huang&nbsp;is currently a senior power system research engineer at Pacific Northwest National Laboratory (PNNL).&nbsp;He leads and manages several U.S. DOE-funded projects, including a major ARPA-E OPEN project on intelligent real-time grid emergency control.</p>

<p><strong>Online Location:</strong> <a href="https://gatech.webex.com/gatech/j.php?MTID=m0af9065fc3aeb183565a7148d6fefbfa">https://gatech.webex.com/gatech/j.php?MTID=m0af9065fc3aeb183565a7148d6fefbfa</a></p>
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      <value><![CDATA[Dr. Qiuhua Huang is currently a senior power system research engineer at Pacific Northwest National Laboratory (PNNL). ]]></value>
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      <value><![CDATA[<p>Dr.&nbsp;Qiuhua&nbsp;Huang&nbsp;is currently a senior power system research engineer at Pacific Northwest National Laboratory (PNNL).&nbsp;</p>
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      <value><![CDATA[2021-11-11T11:00:00-05:00]]></value>
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      <value><![CDATA[<p><a href="mailto:lharrison48@gatech.edu">Luke Harrison</a></p>
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