A Rolling Projective Integration Method for Stochastic Dynamic Simulation of Active Distribution Networks

The stochastic property of active distribution networks (ADNs) has been becoming more and more significant due to the integration of a large number of distributed generators (DGs) and the popularization of the advanced load control technologies. This randomness has brought non-negligible influences on the planning, operation and computation of ADNs. Therefore, an accurate and highly efficient simulation method considering the effects of stochastic disturbances is of great importance for the analysis of the stochastic property of ADNs. This paper proposed a rolling projective integration method (RPIM) considering the stochastic and multi-time scale property of ADNs at the same time. The proposed method combines the deterministic projective integration method and the mixed stochastic numerical integration algorithms. Meanwhile, a rolling approach designed for the multi-trajectory simulation was also presented to improve the statistical accuracy of the proposed RPIM. Case studies based on the low-voltage ADN benchmark show the feasibility and effectiveness of the proposed method, which is verified through the comparison with the deterministic simulation method and the Euler-Maruyama method.