  The day-ahead energy and reserve management with transmission restrictions
and voltage security limits is a challenging task for large-scale power systems
in the presence of real-time variations caused by the uncertain demand and the
fluctuating power output of renewable energy sources (RESs). The proposed
formulation in this work supports joint scheduling of energy and reserve to
promote an economic and reliable operation. To improve its scalability, a
two-stage iterative optimization algorithm is proposed based on Bender's
decomposition framework. Therewith, the optimal schedule is computed subject to
the feasibility of AC network constraints (AC-NCs) at predetermined uncertain
realizations. A convex relaxation is applied to AC-NCs to support the
convergence of the algorithm. Moreover, the integration of RESs is often
limited by transmission congestion issues in existing grids. For such grids, AC
to DC conversion schemes can be viable and attractive options for capacity
expansion. In this study, we adopt a hybrid AC/DC transmission grid (HTG)
architecture with a specific topology to improve the effective utilization of
the grid capacity and accommodate more demand and RESs, which is showcased via
simulations on a large-scale network. Moreover, HTG induces exactness of the
convex relaxation of AC-NCs, supporting the validity of the optimal schedule.
