  The highly non-convex AC optimal power flow problem is known to scale very
poorly with respect to the number of lines and buses. To achieve improved
computational speed and scalability, we apply a distributed optimization
algorithm, the so-called Augmented Lagrangian based Alternating Direction
Inexact Newton (ALADIN) method. However, the question of how to optimally
partition a power grid for use in distributed optimization remains open in the
literature. In the present paper, we compare four partitioning strategies using
the standard IEEE 9, 14, 30, 39, 57, 118, 300 bus models as the performance
benchmark. To this end, we apply the graph partitioners KaFFPa and METIS as
well as two spectral clustering methods to the aforementioned bus models. For
larger grids, KaFFPa yields the best results on average.
