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Analysis of cascaded failures in power networks using maximum flow based complex network approach

机译:基于最大流量的复杂网络方法对电力网络级联故障分析

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Power networks can be modeled as networked structures with nodes representing the bus bars (connected to generator, loads and transformers) and links representing the transmission lines. In this manuscript we study cascaded failures in power networks. As network structures we consider IEEE 118 bus network and a random spatial model network with similar properties to IEEE 118 bus network. A maximum flow based model is used to find the central edges. We study cascaded failures triggered by both random and targeted attacks to the edges. In the targeted attack the edge with the maximum centrality value is disconnected from the network. A number of metrics including the size of the largest connected component, the number of failed edges, the average maximum flow and the global efficiency are studied as a function of capacity parameter (edge critical load is proportional to its capacity parameter and nominal centrality value). For each case we identify the critical capacity parameter by which the network shows resilient behavior against failures. The experiments show that one should further protect the network for a targeted attack as compared to a random failure.
机译:电源网络可以被建模为网络结构,其中节点表示汇流条(连接到发电机,负载和变压器)和表示传输线的链路。在此手稿中,我们研究电源网络中的级联失败。作为网络结构,我们考虑IEEE 118总线网络和一个随机空间模型网络,其具有与IEEE 118总线网络类似的属性。最大流动的模型用于找到中央边缘。我们研究随机触发的级联失败和针对性攻击到边缘。在目标攻击中,具有最大中心性值的边缘与网络断开连接。包括最大连接组件的大小的许多度量,失败的边缘的数量,平均最大流量和全局效率是作为容量参数的函数(边缘临界负载与其容量参数和标称中心值成比例) 。对于每种情况,我们识别网络通过该关键容量参数,该参数显示针对失败的弹性行为。实验表明,与随机故障相比,人们应该进一步保护网络以进行目标攻击。

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