Distribution system reliability assessment using sequential multilevel Monte Carlo method

The paper proposes a new time sequential multilevel Monte Carlo (MLMC) method for estimating distribution system reliability. Usually, the reliability indices of a distribution system are accurately assessed by sequential Monte Carlo simulation (MCS). A disadvantage of sequential MCS is the computational burden which may be prohibitive for achieving a high accuracy. The aim of the proposed method is to enhance the computational efficiency of sequential MCS. The basic idea of MLMC is to use the stochastic differential equations (SDE) based approximation of the reliability indices with multiple timesteps. In MLMC method, a large number of simulations are performed on the coarse grid levels at a low cost and few on the fine grids at a high cost in such a way which can reduce the overall variance of the reliability indices estimators of MCS for the desired accuracy. Comparisons with the analytical and sequential MCS methods are carried out on a small distribution system to demonstrate the effectiveness of the proposed method. The results verify that the proposed method gives acceptable values of reliability indices by reducing their calculation time compared to sequential MCS.