  With rapid integration of power sources with uncertainty, robustness must be
carefully considered in the transmission constrained unit commitment (TCUC)
problem. The overall computational complexity of the robust TCUC methods is
closely related to the vertex number of the uncertainty set. The vertex number
is further associated with 1) the period number in the scheduling horizon as
well as 2) the number of nodes with uncertain injections. In this paper, a
column merging method (CMM) is proposed to reduce the computation burden by
merging the uncertain nodes, while still guar-anteeing the robustness of the
solution. By the CMM, the transmission constraints are modified, with the
parameters obtained based on an analytical solution of a uniform approximation
problem, so that the computational time is negligi-ble. The CMM is applied
under a greedy-algorithm based framework, where the number of merged nodes and
the ap-proximation error can be well balanced. The CMM is designed as a
preprocessing tool to improve the solution efficiency for robust TCUC problems
and is compatible with many solution methods (like two-stage and multi-stage
robust optimi-zation methods). Numerical tests show the method is effective.
