Low-Rank and Lifted Semidefinite Programming for Mixed-Integer Polynomial Power Grid Optimization
The research tested if a local solver could find the guaranteed global optimum for a complex, nonconvex power grid optimization problem (AC-OTS). By combining low-rank semidefinite programming with moment-based lifting techniques, the study found that this hybrid approach successfully yields exact, globally optimal solutions to the mixed-integer polynomial problem.