Tuesday, 13:45 - 14:10 h, Room: MA 549


Diego Klabjan
Day ahead stochastic unit commitment with demand response and load shifting

Coauthors: Frank Schneider, Ulrich Thonemann


High costs for fossil fuels and increasing shares of intermittent energy sources are imposing big
challenges on power grid management. Uncertainty in generation as well as in demand for electric
energy call for
flexible generation capacity and stochastic optimization of generation schedules.
Emerging smart grid technology is one component believed to be a successful tool to increase
efficiency in power generation and to mitigate effects of increasing uncertainty. We
focus on the potential of demand side resources (DSRs) that can be dispatched to reduce load
at peak times. We present a stochastic dynamic programming model for the unit commitment
problem in a day ahead market and include dispatch decisions for DSRs. We model the effect of
load shifting to previous and subsequent periods that must be taken into account when making
dispatch decisions. We also present an approximate dynamic programming algorithm embedded
in a decomposition algorithm that enables us to capture effects of DSR dispatch on previous
periods and to solve both problems concurrently. Lower bounds on the optimal solution are


Talk 2 of the invited session Tue.2.MA 549
"Stochastic programming applications in energy systems" [...]
Cluster 18
"Optimization in energy systems" [...]


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