Accelerated State Evaluation and Latin Hypercube Sequential Sampling for Composite System Reliability Assessment

This paper proposes improvements in the sequential Monte Carlo (MC) simulation based approaches for reliability evaluation of composite generation and transmission systems. The main idea is to compute a threshold load level to facilitate the process of state evaluation, which is very time-consuming mainly due to optimal power flow computations. Two main sampling techniques namely random sampling (RS) and Latin Hypercube sampling (LHS) are applied to the proposed sequential MC simulation technique. Their performances in terms of simulation time as well as solution accuracy are compared. Case studies using the IEEE Reliability Test System (IEEE RTS) are utilized to demonstrate the performance of the proposed approach. Reliability indices including loss of load probability, expected unserved energy, loss of load frequency and duration are estimated. It is shown that the proposed approach considerably reduces the computational requirements during state evaluation, and that the application of LHS can further decrease the simulation time and required sample size to reach convergence.