An active distribution network is an important development trend of the power grid with widespread use of the distributed generation. The reliability of the active distribution network is not negligible due to the uninterruptible power supply. In the paper, the reliability evaluation method of the active distribution network is proposed in detail, based on combining the roulette wheel selection and the sequential Monte Carlo algorithm. The uncertainty of both the distribution generation and the load is taken into consideration based on the power probability distribution and the working state in the presented model. Furthermore, the IEEE-RBTS Bus 6 is used to verify the validity of the proposed method. The result shows that the new energy access improves the availability and the reliability of the active distribution network.

This work presents an improved self-adaptive power distribution approach for the microgrid in five modes under different pandemic conditions in a typical tourism water village in Northern China. Differently from the other studies, this work concentrates on satisfying the specific power supply requirements under the COVID-19 background, with the maximum value of the composite index as the object function. Composite index includes not only the economic factors, but also some compulsive factors to ensure the requested power supply of the residents/tourists. The improved particle swarm optimization method which employs the modified weighted factor and the elite strategy is utilized to optimize the power dispatching of the microgrid. Moreover, the impact of the pandemic has been fully considered by comparing the power dispatching before and after the pandemic. The case study in Baiyangdian Region confirms the effectiveness of the proposed method. With this method, the optimal power dispatching is determined under different modes.