Benchmarks and Resource Estimation of a Quantum Algorithm for Unit Commitment

Unit commitment is an optimization problem whose combinatorial nature makes it an interesting problem for quantum computers to solve. NISQ-era quantum computers have made significant progress; however, they are still limited in computational ability due to noisy physical implementations. Nonetheless, several algorithms have been proposed to solve problems in the energy sector such as unit commitment. We perform a benchmark and resource estimation analysis on one of these algorithms, specifically QAOA. In this approach the unit commitment problem is formulated as a QUBO, which is then solved on a quantum computer. We obtain benchmark results for emulated near-term hardware. Furthermore, we use quantum resource estimation to obtain the required physical qubit counts and runtimes to run the algorithm on an ideal, fault-tolerant quantum computer. Our results display both the performance of intermediate-scale hardware, and the demanding physical requirements quantum computers will have to meet to realize these algorithms with practical utility.