A Quantum-Enhanced Power Flow and Optimal Power Flow based on Combinatorial Reformulation

This study introduces the Adiabatic Quantum Power Flow (AQPF) and Adiabatic Quantum Optimal Power Flow (AQOPF) algorithms to solve power flow (PF) and optimal power flow (OPF) problems, respectively. These algorithms utilize a novel combinatorial optimization reformulation of classical PF and OPF problems, and hence, enable their implementation on Ising machines, e.g., quantum and quantum-inspired hardware. The experiments are conducted on standard test cases ranging from 4-bus to 1354-bus systems, using D-Wave's Advantage system (QA), D-Wave's quantum-classical hybrid solver (HA), Fujitsu's Digital Annealer V3 (DAv3), and Fujitsu's Quantum-Inspired Integrated Optimization software (QIIO). The annealers are systematically evaluated based on: (i) full and partitioned formulations, (ii) ability to handle ill-conditioned cases, and (iii) scalability. The results are benchmarked against the Newton-Raphson numerical method (NR) and suggest that AQPF and AQOPF can serve as effective solvers or complementary tools to classical methods to address unsolved challenges in large-scale modern power systems.