  As renewable energy sources replace traditional power sources (such as
thermal generators), uncertainty grows while there are fewer controllable
units. To reduce operational risks and avoid frequent real-time emergency
controls, a preparatory schedule of renewable generation curtailment is
required. This paper proposes a novel two-stage robust generation dispatch
(RGD) model, where the preparatory curtailment schedule is optimized in the
pre-dispatch stage. The curtailment schedule will then influence the variation
range of real-time renewable power output, resulting in a decision-dependent
uncertainty (DDU) set. In the re-dispatch stage, the controllable units adjust
their outputs within the reserve capacities to maintain power balancing. To
overcome the difficulty in solving the RGD with DDU, an adaptive
column-and-constraint generation (AC\&CG) algorithm is developed. We prove that
the proposed algorithm can generate the optimal solution in finite iterations.
Numerical examples show the advantages of the proposed model and algorithm, and
validate their practicability and scalability.
