Reliability assessment of distribution grids with DG via quasi-sequential Monte Carlo simulation.

• A new quasi-sequential Monte Carlo simulation (QS-MCS) method properly designed to the reliability assessment of distribution grids with renewable DG and other time-dependent events is proposed. • ew test functions are described and discussed to calculate the usual distribution reliability indices. • The computational efficiency of the proposed QS-MCS is similar to non-sequential-based tools, but its accuracy and modeling flexibility are at the same level as sequential-MCS tools. • The reliability indices of two distribution systems, a test system and a real distribution network from Brazil, are evaluated under the presence of renewable DG sources. • The algorithm is built using object-oriented programming and all the results obtained are compared and validated to those evaluated by a Sequential-MCS tool. The increasing insertion of distributed generation (DG) in distribution systems has profoundly altered the typical structure of these grids. In general, renewable DG resources are intermittent and make the reliability performance evaluation of distribution networks more complex. Thus, it is essential to have an efficient method and models capable of adequately representing the stochastic characteristics of load, generation and grid, including the protection system response. The proposed quasi-sequential Monte Carlo simulation (QS-MCS) aims to capture in detail the behavior of these characteristics, just like sequential or chronological simulations do, but with the same simplicity and performance of non-sequential simulations. Based on new unbiased test functions, distribution reliability indices are calculated to cope with the insertion of DG considering two systems, and discussions are raised about the flexibility, accuracy and computational efficiency of the proposed method. [ABSTRACT FROM AUTHOR]