电功率系统风险和脆弱性分析物理流模型的拓扑性能指标替代
Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems
摘要：
关键的基础设施系统必须既强大又有复原力，以确保社会的运转。为了提高这些系统的性能，我们经常使用风险和漏洞分析来发现和解决系统的弱点。这种分析的一个关键组成部分是准确确定系统中各种故障的负面后果的能力。存在许多数学和模拟模型，可以用于这一目的。然而，有相对较少的研究比较使用不同的建模方法在关键基础设施的全面风险分析的背景下的影响。因此，在本文中，我们建议这些模型的分类，从简单的面向拓扑的模型，先进的物理流为基础的模型。在这里，我们专注于电功率系统，并提出了一项研究，旨在了解在风险分析的背景下使用的模型的简单性和保真度之间的权衡。具体而言，本文的目的是比较性能的措施，实现了一系列的方法通常用于风险和脆弱性分析的电功率系统和评估，如果更简化的拓扑措施可以结合使用统计方法被用作物理流模型的代理。我们的工作结果提供了指导，以适当的模型或模型组合时使用的分析大规模的关键基础设施系统，在使用更先进的模型时，模拟时间很快变得不可逾越，严重限制了可以执行的分析范围。
英文摘要：
Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses. A critical component of such analyses is the ability to accurately determine the negative consequences of various types of failures in the system. Numerous mathematical and simulation models exist which can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. Thus in this paper, we suggest a classification of these models, which span from simple topologically-oriented models to advanced physical flow-based models. Here, we focus on electric power systems and present a study aimed at understanding the tradeoffs between simplicity and fidelity in models used in the context of risk analysis. Specifically, the purpose of this paper is to compare performances measures achieved with a spectrum of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if more simplified topological measures can be combined using statistical methods to be used as a surrogate for physical flow models. The results of our work provide guidance as to appropriate models or combination of models to use when analyzing large-scale critical infrastructure systems, where simulation times quickly become insurmountable when using more advanced models, severely limiting the extent of analyses that can be performed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
