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A Submodular Optimization Approach to Controlled Islanding under Cascading Failure

机译:级联失效下控制孤岛的次模优化方法

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Cascading failures occur when the power system is subject to a significant disturbance, such as tripping one or more transmission lines. Such failures can severely impact power system stability, potentially leading to widespread outages. One proposed approach for mitigating cascading failures is to partition the system into internally stable islands (a process known as controlled islanding). Selecting a subset of transmission lines to trip to form desired islands is inherently a combinatorial optimization problem. Current approaches for selecting such subsets, however, rely on computationally expensive heuristics that do not provide optimality guarantees. In this paper, we propose a submodular optimization approach for controlled islanding. Our approach has two stages. In the first stage, generators are assigned to each island based on existing methods such as slow coherency theory in order to ensure that each island is dynamically stable. In the second stage, we determine which edges to cut in order to minimize the generator-load imbalance within each island to ensure that a stable steady-state operating point exists. We relax the problem of minimizing imbalance to a supermodular minimization problem with a matroid constraint, implying that a greedy algorithm gives a provable optimality bound of 1/2. Our results are demonstrated using the IEEE 39-bus New England Test System.
机译:当电力系统遭受重大干扰(例如使一条或多条传输线跳闸)时,会发生级联故障。这样的故障会严重影响电力系统的稳定性,并可能导致大范围的停电。缓解级联故障的一种建议方法是将系统划分为内部稳定的孤岛(此过程称为受控孤岛)。选择传输线的一个子集跳闸以形成所需的孤岛本质上是一个组合优化问题。然而,用于选择此类子集的当前方法依赖于计算上昂贵的启发式方法,该启发式方法不提供最优性保证。在本文中,我们提出了一种用于受控孤岛的亚模优化方法。我们的方法分为两个阶段。在第一阶段,将根据现有方法(例如慢相干理论)将生成器分配给每个岛,以确保每个岛都是动态稳定的。在第二阶段,我们确定要切割的边缘,以最大程度地减少每个岛内的发电机负载不平衡,以确保存在稳定的稳态工作点。我们将将不平衡最小化的问题放宽为带有拟阵约束的超模最小化问题,这意味着贪婪算法给出了可证明的1/2的最优界。使用IEEE 39总线新英格兰测试系统证明了我们的结果。

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