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Clustering-Coefficient Based Resiliency Approach for Smart Grid

机译：智能电网集群系数的弹性方法

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Maintaining a power grid's functions is of paramount importance to grid operators as power is essential to almost all aspects of daily human activities. Grid resiliency keeps services up to the customers even upon failure incidences. A modernized power grid should balance the power load and overcome the fault state by minimizing its impact. Resiliency researchers have proposed many schemes for post-failure grid incidents. However, there is not yet an overall framework that combines both in-depth analyses of low-level topological characteristics to evaluate the existing grid resiliency and then improve it whenever required. In this paper, we present microlevel topological and resilience analysis of multiple IEEE bus systems. We propose a two-phase resilience framework for the smart power grid: the resiliency evaluation and the resiliency enhancement. While the first phase provides empirical evidence of the sufficiency of exploring a limited number of backup power lines upon an incident, the second phase employs clustering coefficient as a key indicator to enhance grid resiliency. We implement our proposed framework, validate it and show its effectiveness using the IEEE 14-bus system.
机译：维护电网的功能对于电网运营商至关重要，因为电力对于几乎是日常人类活动的各个方面至关重要。网格弹性即使在故障发生故障时也会使服务能够保持服务。现代化的电网应通过最小化其影响来平衡电力负载并克服故障状态。弹性研究人员提出了失效后网格事件的许多方案。但是，还没有整体框架，这些整体框架将深入分析的低级拓扑特性进行了深入分析，以评估现有的网格弹性，然后在需要时改善它。本文介绍了多个IEEE总线系统的MicroLevel拓扑和弹性分析。我们为智能电网提出了一个两相的弹性框架：弹性评估和弹性增强。虽然第一阶段提供了在入射时探索有限数量的备用电源线的经验证据，但第二阶段采用聚类系数作为提高网格弹性的关键指示。我们实施了我们提出的框架，验证了它并使用IEEE 14-Bus系统显示其有效性。

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