Reliability evaluation based on modified latin hypercube sampling and minimum load-cutting method

As its sampling frequency is independent of the scale of the system, Monte-Carlo simulation is widely applied to reliability evaluation of generation and transmission system, which is a complex large system. However, it takes a relatively long period to obtain a higher accurate reliability index. This paper points out that, the combination of Importance sampling method and Discrete Latin Hypercube sampling method is able to reduce the variance of the sample space and uniformly sample it simultaneously, which improves the convergence of Monte-Carlo simulation. Besides, the combination of sensitivity analysis and linear programming in the process of overload correction is able to guarantee the solution optimality as well as improve the solving speed. Finally, the practicability of the proposed algorithm is verified with the case study in IEEE RTS79 and RTS96.