World's first practical power flow algorithm operating on today's noisy quantum computers

Abstract

Power flow is an indispensable foundation for power system analytics. Under the deep penetration of renewables, modern power system analytics often becomes intractable because it needs to run an enormous amount of power flow analyses to quantify the impact of uncertainties. Unlike classical power flow methods that scale polynomially with the system size, quantum computing enables using logarithmically-scaled number of qubits to solve linear equations in power flow analysis. Thus, quantum power flow (QPF) provides a promising direction to make today's intractable power system analytics tractable. However, a major obstacle to the development of a practical quantum power flow algorithm lies in the fact that today's mainstream quantum computers are still noisy-intermediate-scale quantum (NISQ) devices whose capability is restricted by the limited number of qubits and considerable noises. To bridge this gap, Stony Brook University establishes a variational quantum power flow that allows for practical and noise-resilient power flow analysis on today's NISQ devices.