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DESCRIPTION:Abstract: In the past decade\, Information and Communication Te
 chnologies (ICT) have enabled the modernization of the power grid and have
  led to many advances in smart grid technologies. Smart grid communication
 s facilitate a large number of grid operations\, including advanced meteri
 ng\, fault monitoring\, microgrid control\, transactive energy systems and
  so on. In parallel to advances in smart grids\, communication technologie
 s have been continuously evolving to provide better service to mobile user
 s and vertical industries. Recently\, machine learning has showed promisin
 g performance improvements in communication networks as well as smart grid
  operations. In this talk\, we introduce novel AI-based tools that will al
 low a P2P energy trading platform\, consisting of microgrids\, to become a
  part of the future transactive energy systems. The energy trading platfor
 m relies on robust smart grid communications. We will show our recent resu
 lts on low-latency communications that use reinforcement learning to suppo
 rt communication needs of such energy trading platforms.\n\nSpeaker(s): Me
 like Erol-Kantarci\, \n\nVirtual: https://events.vtools.ieee.org/m/281103
LOCATION:Virtual: https://events.vtools.ieee.org/m/281103
ORGANIZER:mohammed.eltayeb@csus.edu
SEQUENCE:12
SUMMARY:Recent advances in Smart Grid Communications
URL;VALUE=URI:https://events.vtools.ieee.org/m/281103
X-ALT-DESC:Description: <br /><p>Abstract: In the past decade\, Information
  and Communication Technologies (ICT) have enabled the modernization of th
 e power grid and have led to many advances in smart grid technologies. Sma
 rt grid communications facilitate a large number of grid operations\, incl
 uding advanced metering\, fault monitoring\, microgrid control\, transacti
 ve energy systems and so on. In parallel to advances in smart grids\, comm
 unication technologies have been continuously evolving to provide better s
 ervice to mobile users and vertical industries. Recently\, machine learnin
 g has showed promising performance improvements in communication networks 
 as well as smart grid operations. In this talk\, we introduce novel AI-bas
 ed tools that will allow a P2P energy trading platform\, consisting of mic
 rogrids\, to become a part of the future transactive energy systems. The e
 nergy trading platform relies on robust smart grid communications. We will
  show our recent results on low-latency communications that use reinforcem
 ent learning to support communication needs of such energy trading platfor
 ms.</p>
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