School of Engineering, University of Vermont, Burlington, Vermont 05405, USA.
Chaos. 2010 Sep;20(3):033122. doi: 10.1063/1.3489887.
In order to identify the extent to which results from topological graph models are useful for modeling vulnerability in electricity infrastructure, we measure the susceptibility of power networks to random failures and directed attacks using three measures of vulnerability: characteristic path lengths, connectivity loss, and blackout sizes. The first two are purely topological metrics. The blackout size calculation results from a model of cascading failure in power networks. Testing the response of 40 areas within the Eastern U.S. power grid and a standard IEEE test case to a variety of attack/failure vectors indicates that directed attacks result in larger failures using all three vulnerability measures, but the attack-vectors that appear to cause the most damage depend on the measure chosen. While the topological metrics and the power grid model show some similar trends, the vulnerability metrics for individual simulations show only a mild correlation. We conclude that evaluating vulnerability in power networks using purely topological metrics can be misleading.
为了确定拓扑图模型在建模电力基础设施脆弱性方面的有效性,我们使用三种脆弱性指标来衡量电网对随机故障和定向攻击的易感性:特征路径长度、连通性损失和停电规模。前两个是纯粹的拓扑指标。停电规模的计算结果来自电网级联故障模型。对美国东部电网的 40 个区域和一个标准 IEEE 测试案例对各种攻击/故障向量的响应进行测试表明,使用所有三种脆弱性指标,定向攻击会导致更大的故障,但最可能造成破坏的攻击向量取决于所选择的指标。虽然拓扑指标和电网模型显示出一些相似的趋势,但单个模拟的脆弱性指标之间仅存在轻度相关性。我们的结论是,仅使用拓扑指标评估电网脆弱性可能会产生误导。