  This paper aims to implement and evaluate the performance of quantum
computing on solving combinatorial optimization problems arising from the
operations of the power grid. To this end, we construct a novel mixed integer
conic programming formulation for the reconfiguration of radial distribution
network in response to faults in distribution lines. Comparing to existing bus
injection model in the literature, our formulation based the branch flows model
is theoretically equivalent without needing non-explainable variables, thus
being more numerically stable. The network reconfiguration model is then used
as a benchmark to evaluate the performance of quantum computing algorithms in
real quantum computers. It shows that while current quantum computing
algorithms with fast execution time in quantum computers can be a promising
solution candidate, its heuristic nature stem from its theoretical foundation
should be considered carefully when applying into power grid optimization
problems.
