  The prioritization of restoration actions after large power system outages
plays a key role in how quickly power can be restored. It has been shown that
fast and intuitive heuristics for restoration prioritization most often result
in low-quality restoration plans. Meanwhile, mathematical optimization tools
that find high-quality restoration plans are too slow to be applied to
restoration planning problems of practical interest. This work makes a
significant step in closing this quality vs compute time gap by proposing the
Recursive Restoration Refinement heuristic for power system restoration. This
heuristic is shown to produce near-optimal restoration plans up to 1,000 times
faster than other state-of-the-art solution methods on a range of test cases
with up to 500 buses and 700 damaged components. The potential impact of this
new heuristic is demonstrated by a preliminary analysis of the key features of
high-quality restoration plans. The recursive restoration refinement algorithm
and other methods explored in this work have been made available as part of the
open-source software package, PowerModelsRestoration, to support ongoing
research in power restoration algorithms.
