With the spatial flexibility exchange across the network, mobile energy storage systems (MESSs) offer promising opportunities to elevate power distribution system resilience against emergencies. Despite the remarkable growth in integration of renewable energy sources (RESs) in power distribution systems (PDSs), most recovery and restoration strategies do not unlock the full potential in such resources due to their inherent uncertainty and stochasticity. This paper develops a novel restoration mechanism in PDSs for routing and scheduling of MESSs integrated with stochastic RESs to achieve agile system response and recovery in facing the aftermath of high-impact low-probability (HILP) incidents. The proposed integrated model is presented as a non-convex non-linear stochastic optimization formulation with joint probabilistic constraints (JPCs). The problem is equivalently reformulated to a tractable mixed-integer linear programming (MILP) model that can be solved by commercial off-the-shelf solvers. Case studies on the IEEE 33-node and 123-node test systems demonstrate the effectiveness and scalability of the proposed framework in boosting the system resilience. This is achieved via effective routing and scheduling of MESSs jointly managed with dynamic network reconfiguration in presence of stochastic RESs.

中文翻译：

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用于配电网弹性的移动储能系统的不确定性感知部署

通过网络上的空间灵活性交换，移动储能系统 (MESS) 为提高配电系统对紧急情况的恢复能力提供了有希望的机会。尽管可再生能源 (RES) 在配电系统 (PDS) 中的整合显着增长，但由于其固有的不确定性和随机性，大多数恢复和恢复策略并没有释放这些资源的全部潜力。本文在 PDS 中开发了一种新的恢复机制，用于与随机 RES 集成的 MESS 的路由和调度，以在面对高影响低概率 (HILP) 事件的后果时实现敏捷的系统响应和恢复。所提出的集成模型表示为具有联合概率约束 (JPC) 的非凸非线性随机优化公式。该问题等效地重新表述为一个易于处理的混合整数线性规划 (MILP) 模型，该模型可以由商业现成的求解器解决。IEEE 33 节点和 123 节点测试系统的案例研究证明了所提议框架在提高系统弹性方面的有效性和可扩展性。这是通过在随机 RES 存在的情况下通过动态网络重新配置联合管理的 MESS 的有效路由和调度来实现的。