  We consider the unit commitment (UC) problem that employs the alternating
current optimal power flow (ACOPF) constraints, which is formulated as a
mixed-integer nonlinear programming problem and thus challenging to solve in
practice. We develop a new scalable algorithm based on alternating direction
method of multiplier (ADMM), which enables quickly finding a good feasible
solution of the UC-ACOPF problem. Our algorithm employs the component-based
decomposition that solves a large number of independent small subproblems, each
of which represents an individual grid component (e.g., generator, bus, and
transmission line), as well as the UC subproblem. We implement the algorithm in
Julia, as part of the existing package \texttt{ExaAdmm.jl}, which can
efficiently run on GPUs as well as CPUs. The numerical results are reported by
using IEEE test instances.
