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SUMMARY:The Role of Prediction And Real-time Learning in Online Optimizati
 on and Control - Na Li (Harvard University)
DTSTART:20190502T090000Z
DTEND:20190502T100000Z
UID:TALK123580@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Uncertainties place a key challenge in transforming the grid i
 nto one with a large renewable energy integration and active users&#39\; p
 articipation. The volatile renewable generation constantly introduces dist
 urbance to the grid operation\; while the stochastic user behavior makes i
 t difficult to use demand as a reliable resource for balancing real-time s
 upply-demand. This talk will present two lines of work to address these is
 sues. Firstly\, we will study how to use a short term prediction\, e.g.\, 
 renewable energy\, to improve the performance for online optimization and 
 control\, e.g\, economic dispatch with ramping cost. Then\, we will study 
 how to use real-time learning to design residential demand response progra
 ms for achieving grid reliability while balancing the exploitation and exp
 loration of the uncertain user behavior.
LOCATION:Seminar Room 1\, Newton Institute
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