BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:A Unified Framework for Stochastic Optimization in Energy - Warren
  Powell (Princeton University)
DTSTART:20190107T113000Z
DTEND:20190107T123000Z
UID:TALK116737@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:A Unified Framework for Stochastic Optimization in Energy<br> 
 Warren B. Powell<br> Dept. of Operations Research and Financial Engineerin
 g<br> Princeton University<br> <br> Energy systems offer a variety of form
 s of uncertainty that have to be accommodated to ensure a reliable source 
 of power.  The modeling of these sequential decision problems under uncert
 ainty has lacked the kind of canonical framework long enjoyed by determini
 stic problems.  I will introduce a modeling framework that is completely g
 eneral\, which involves three mathematical challenges: 1) machine learning
  (there are up to five classes of learning problems)\, 2) uncertainty mode
 ling\, and 3) designing policies\, which are functions for making decision
 s.  There are two fundamental strategies for creating policies\, each of w
 hich further divides into two subclasses\, creating four classes of polici
 es.  These four (meta)classes of policies are universal\, in that any meth
 od used to solve a sequential decision problem will be drawn from this set
 .  The four classes are illustrated in the context of several applications
  in energy systems.  An energy storage application is then used to demonst
 rate that each of the four classes of policies might be best depending on 
 the characteristics of the data.  <br> <br> <br>
LOCATION:Seminar Room 1\, Newton Institute
END:VEVENT
END:VCALENDAR