The high-level integration of spatial-dispersed renewable energies can greatly enlarge future smart grid size and complicate system operations. Existing numerical methods based on classical computational oracles may be challenged to fulfill efficiency requirements for future smart grid evaluations, where modern advanced computational technologies, specifically quantum computing, have significant potential to help. In this paper, we discuss applications of quantum computing algorithms toward state-of-the-art smart grid problems. We suggest potential, exponential quantum speedup by the use of the Harrow-Hassidim-Lloyd (HHL) algorithms for solving sparse linear systems of equations in Newton’s method of power-flow problems. However, practical implementations of the algorithm are limited by the noise of quantum circuits, the hardness of realizations of quantum random access memories (QRAM), and the depth of the required quantum circuits. We benchmark the hardware and software requirements from the state-of-the-art power-flow algorithms, including QRAM requirements from hybrid phonon-transmon systems, and explicit gate counting used in HHL for explicit realizations. We also develop near-term algorithms of power flow by variational quantum circuits and implement physical experiments for 6 qubits with a truncated version of power flows.