  The discrete unit commitment problem with min-stop ramping constraints
optimizes the daily production of thermal power plants (coal, gas, fuel units).
For this problem, compact Integer Linear Programming (ILP) formulations have
been designed to solve exactly small instances and heuristically real-size
instances. This paper investigates whether Dantzig-Wolfe reformulation allows
to improve the previous exact method and matheuristics. The extended ILP
formulation is presented with the column generation algorithm to solve its
linear relaxation. The experimental results show that the Dantzig-Wolfe
reformulation does not improve the quality of the linear relaxation of the
tightest compact ILP formulations. Computational experiments suggest also a
conjecture which would explain such result: the compact ILP formulation of
min-stop ramping constraints would be tight. Such results validate the quality
of the exact methods and matheuristics based on compact ILP formulations
previously designed.
