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SUMMARY:Dynamic Distribution Network Reconfiguration with Generation and L
 oad Uncertainty - Vincent Wong - University of British Columbia
DTSTART:20230707T120000Z
DTEND:20230707T130000Z
UID:TALK202447@talks.cam.ac.uk
CONTACT:114742
DESCRIPTION:Given the uncertainty in load demand and renewable energy sour
 ces\, the distribution network reconfiguration (DNR) problem is a stochast
 ic mixed-integer nonlinear optimization program with a running time that s
 cales exponentially with the number of sectional and tie line switches. St
 ochastic optimization techniques require knowledge of the stochastic proce
 sses of the uncertain parameters\, which may not be available in practice.
  In this seminar\, we introduce a deep reinforcement learning algorithm to
  solve the DNR problem by determining the optimal network configuration us
 ing a deep neural network architecture.\n\nVincent Wong is a Professor in 
 the Department of Electrical and Computer Engineering at the University of
  British Columbia\, Vancouver\, Canada. His research areas include protoco
 l design\, optimization\, and resource management of communication network
 s\, with applications to the Internet\, wireless networks\, smart grid\, m
 obile edge computing\, and Internet of Things. Dr. Wong is the Editor-in-C
 hief of the IEEE Transactions on Wireless Communications.
LOCATION:FW 11\, William Gates Building. Zoom link: https://cl-cam-ac-uk.z
 oom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&amp\;from=addon 
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