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SUMMARY:Distributionally robust chance-constrained generation expansion pl
 anning - Jalal Kazempour (Technical University of Denmark)
DTSTART:20190321T134500Z
DTEND:20190321T143000Z
UID:TALK121426@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:This talk addresses a centralized generation expansion plannin
 g problem\, accounting for both long- and short-term uncertainties. The lo
 ng-term uncertainty (demand growth) is modeled via a set of scenarios\, wh
 ile the short-term uncertainty (wind power) is considered using moment-bas
 ed ambiguity sets. In the expansion stage\, the optimal units to be built 
 are selected among discrete options. In the operational stage\, a detailed
  representation of unit commitment constraints is considered. To make this
  problem tractable\, we solve it in linear decision rules\, and use a tigh
 t relaxation approach to covexify the unit commitment constraints. The res
 ulting model is a distributionally robust chance-constrained optimization\
 , which eventually recasts as a mixed-integer second-order cone program. W
 e consider the IEEE 118-bus test system as a case study\, and explore the 
 performance of the proposed model using an out-of-sample analysis.
LOCATION:Seminar Room 1\, Newton Institute
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