Quantum Distribution System Reliability Assessment

The reliability assessment is becoming an inevitable part of distribution systems in lights of uncertainty output of integrated distributed energy resources (DERs). The Monte Carlo Simulation (MCS) approach is a broadly used method in replacing the analytical methods in reliability evaluation. The accuracy of this method, however, highly depends on the sampling size, and hence, a complicated system with large amount of components requires a large sampling size and thereby computational effort. In this paper, for the first time, the idea of quantum computing (QC) is introduced in power system reliability evaluation to achieve the convergence speed-up compared to the conventional methods with the same number of samples. The main contributions of this paper include: 1) the innovative development of a quantum model for reliability assessment; 2) achieving the quadratic speed up using QC compared to the classical MCS method; 3) utilization of quantum amplitude estimation (QAE) algorithm to calculate the reliability indices. Different scenarios are tested in a radial distribution system to show the efficacy of QC.