Networked microgrids (NMGs) enhance the resilience of power systems by enabling mutual support among microgrids via dynamic boundaries. While previous research has optimized the locations of mobile energy storage (MES) devices, the critical aspect of MES capacity sizing has been largely neglected, despite its direct impact on costs. This paper introduces a two-stage optimization framework for MES sizing, pre-positioning, and re-allocation within NMGs. In the first stage, the capacity sizing and pre-positioning of MES devices are optimized before a natural disaster. In the second stage, the re-allocation and active power output of MES devices are adjusted post-disaster, with boundary switches operated based on the damage scenarios. The framework restores unserved loads by either forming isolated microgrids using MES or re-establishing connections between microgrids via smart switches. The proposed framework is modeled mathematically and solved using a customized progressive hedging algorithm. Extensive experiments on modified IEEE 33-node and 69-node systems demonstrate the model’s effectiveness and applicability in improving system resilience.

Distributed generators and microgrids are of great importance for the stable operation of power systems when failures occur. The major work of this paper is proposing an optimal topological design model of preset connection lines, aiming at a distributed power generation network based on different nodal invulnerability requirements. Moreover, the important innovation of this paper lies in that the perspective is shifted from the system to an individual node of a different type. When a node malfunction occurs, the faulty node can be connected to its neighbor nodes by closing a switch to achieve energy exchange. The distributed generation network consists of a series of nodes that can realize self-sufficiency and can be classified into three types with different levels of importance according to their tasks. The nodes of different types must meet different requirements of destructibility. In this paper, a mixed-integer linear programming model is formulated to solve the optimal topology design problem. In addition, this paper also analyzes the influence of changing nodal power generation capacity and nodal type, and the simulation results show the practicability of the proposal.

With the aggravation and evolution of global warming, natural disasters such as hurricanes occur more frequently, posing a great challenge to large-scale power systems. Therefore, the pre-position and reconfiguration of the microgrid defense resources by means of Mobile Energy Storage Vehicles (MEVs) and tie lines in damaged scenarios have attracted more and more attention. This paper proposes a novel two-stage optimization model with the consideration of MEVs and tie lines to minimize the shed loads and the outage duration of loads according to their proportional priorities. In the first stage, tie lines addition and MEVs pre-position are decided prior to a natural disaster; in the second stage, the switches of tie lines and original lines are operated and MEVs are allocated from staging locations to allocation nodes according to the specific damaged scenarios after the natural disaster strikes. The proposed load restoration method exploits the benefits of MEVs and ties lines by microgrid formation to pick up more critical loads. The progressive hedging algorithm is employed to solve the proposed scenario-based two-stage stochastic optimization problem. Finally, the effectiveness and superiority of the proposed model and applied algorithm are validated on an IEEE 33-bus test case.