SGER: Characterizing Power Systems with Tools from Complex Networks

摘要S网络的脆弱性和风险缓解措施的有效性在很大程度上取决于其结构。这项合作研究的目的是为大规模电力网络开发新的结构措施，基于拓扑和电气属性，并找到电力网络结构和脆弱性之间的联系。由此产生的措施将使用两个主要地区输电运营商的潮流数据进行验证。智力价值复杂网络和图论领域的研究表明，网络的S拓扑可以极大地影响其性能和脆弱性。以前的研究试图利用文献中关于随机图、小世界和无标度网络的现有工具来测量电网的结构和识别脆弱性，但结果喜忧参半，而且不一致。混淆的部分原因是对电网拓扑的关注，而忽视了控制电路中流动的基尔霍夫-S定律。由于脆弱性在很大程度上是流动行为的函数，一套正确的电力网络结构指标需要纳入这些物理定律。这项工作将通过开发同时考虑网络拓扑和支配流量的物理规律的脆弱性度量来解决现有文献中的这一缺陷。更广泛的影响这项工作提出了一种测量和检测电网脆弱性的全新思路。如果成功，这一努力将为工具提供智力基础，有助于显著提高美国电力基础设施的可靠性和效率。此外，这项工作将提高佛蒙特州大学和宾夕法尼亚州立大学在电力系统和复杂网络方面跨越传统学科界限的教育能力。该项目还将支持在密歇根大学开发一个新的跨学科能源系统实验室，该实验室正在设计中，以吸引更多不同类型的学生学习能源系统工程。

AbstractA network?s vulnerability and the effectiveness of risk mitigation measures depend highly on its structure. The goal of this collaborative research is to develop new structural measures for large-scale electric power networks, based on both topological and electrical properties, and to find connections between the structure and vulnerability of electricity networks. The resulting measures will be validated using power-flow data of two major regional transmission operators. Intellectual MeritResearch in the area of complex networks and graph theory shows that a network?s topology can dramatically affect its performance and vulnerability. Previous studies have attempted to measure the structure of power grids and identify vulnerabilities using existing tools from the literature on random graphs, small-world and scale-free networks, but the results have been mixed and inconsistent. Part of the confusion results from a focus on grid topology, ignoring Kirchoff?s Laws, which govern flows in electrical circuits. Since vulnerability is largely a function of flow behavior, a correct set of structural metrics for power networks needs to incorporate these physical laws. This work will address this shortcoming in the existing literature through the development of vulnerability measures that consider both network topology and the physical laws that govern flow. Broader ImpactsThis work proposes a fundamentally new way of thinking about measuring and detecting vulnerability in power networks. If successful, this effort will provide the intellectual foundation for tools contributing to significant improvement of the reliability and efficiency of the US electricity infrastructure. Additionally this work will increase the capacity for education in power systems and complex networks, across traditional disciplinary lines, at the University of Vermont and Penn State University. The project will also support the development of a new cross-disciplinary energy systems laboratory at UVM, which is being designed to attract a more diverse pool of students to energy systems engineering.