This research was funded by Science and technology projects of State Grid Zhejiang Electric Power Co., Ltd. 2021ZK37 (Research on partition coordinated self-healing recovery technology of power system based on artificial intelligence).

Mobile emergency resources (MERs) are critical to the resilience of distribution systems for an emergency response to natural disasters. However, after disasters, the communication network of MERs may be unreliable. For example, the communication topology switches in different modes randomly. The conventional centralized control algorithms may not converge. As a result, the instability of frequency and voltage happened. To alleviate the impacts of the unreliable communication network on the second control performance, this paper regards the distribution system after disasters as multiple microgrids. A distributed secondary control algorithm is designed to regulate frequency and voltage in islanded microgrids over switching communication topologies. The algorithm is guaranteed to converge in a fixed time. Case studies are carried out to demonstrate the effectiveness and robustness of the proposed control algorithm under switching communication topologies.INDEX TERMS Mobile emergency resources (MERs), resilience, switching topologies, distributed control.

Pre-dispatch is an important way for distribution networks to cope with typhoon weather, enhance resilience and reduce economic losses. In order to accurately describe the faults and consequences of components’ failure in the distribution network, this paper establishes a pre-dispatch model to cope with typhoon weather based on line failures consequence analysis. First, Monte Carlo simulation is used to sample the typical fault scenarios of vulnerable lines. According to the location of switchgear, the distribution network is partitioned and a block breaker correlation matrix is established. Combined with the line fault status, a fault consequence model of distribution lines related to the pre-dispatching strategy is established. Then, the objective function is given to minimize the sum of the cost of the pre-dispatch operation and the power outage, and then establish a pre-dispatch model for the distribution network. In order to reduce the computational complexity, PH (Progressive Hedging) algorithm is used to solve the model. Finally, the IEEE-69 test system is used to analyze the effectiveness of the method. The results show that the proposed dispatching model can effectively avoid potential risks, reduce system economic losses and improve the resilience of power grids.

This paper proposes a power system state estimation method combining the Monte Carlo method and the SCADA/PMU hybrid measurement state estimation algorithm. Quantify the impact of load uncertainty on the state estimation results to reduce the influence of power system measurement error. The results show that the method takes into account the uncertainty of load measurement and the influence of flexible load, and accurately estimate the operating state of the power system.

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