  We consider a two-stage generation scheduling problem comprising a forward
dispatch and a real-time re-dispatch. The former must be conducted facing an
uncertain net demand that includes non-dispatchable electricity consumption and
renewable power generation. The latter copes with the plausible deviations with
respect to the forward schedule by making use of balancing power during the
actual operation of the system. Standard industry practice deals with the
uncertain net demand in the forward stage by replacing it with a good estimate
of its conditional expectation (usually referred to as a point forecast), so as
to minimize the need for balancing power in real time. However, it is well
known that the cost structure of a power system is highly asymmetric and
dependent on its operating point, with the result that minimizing the amount of
power imbalances is not necessarily aligned with minimizing operating costs. In
this paper, we propose a bilevel program to construct, from the available
historical data, a prescription of the net demand that does account for the
power system's cost asymmetry. Furthermore, to accommodate the strong
dependence of this cost on the power system's operating point, we use
clustering to tailor the proposed prescription to the foreseen net-demand
regime. By way of an illustrative example and a more realistic case study based
on the European power system, we show that our approach leads to substantial
cost savings compared to the customary way of doing.
