Collaborative research: Complex dynamics, criticality and cascading events in power system blackouts and communication networks

大型公用事业电力传输系统，如美国西部的电力系统，可以而且确实会遭受连锁事件，导致大范围停电。这些停电严重影响了公众、商业和政府，是国家基础设施的一个漏洞。这个项目没有关注个别停电的详细原因，而是解决了一系列长时间停电的全球、复杂的系统动态。将开发新的模型、模拟和分析方法，以捕捉关键、自组织和连锁故障的本质。将特别关注北美停电数据中以及通常处于临界状态的系统中发生的停电大小的概率分布的功率尾部。这些电力尾巴表明，大规模灾难性停电的可能性比传统风险分析预测的要大得多。该项目将开发新的风险分析方法，并探索操作技术，以减轻重大停电的风险。互联网等通信网络也会出现主要的级联中断，在这一应用中也将继续开展工作，以在一定程度上关注具有社会重要性的大型工程网络中中断的普遍特征。预期的结果是能够理解、统计分析并在一定程度上缓解电力传输和通信网络中的主要连锁中断。科学成果是对复杂系统动力学在工程设计和压力网络分析中的新的理解和新的应用。教育成果包括在多学科团队中培训本科生和研究生。

Large scale utility electrical power transmission systems such as the power system of the Western United States can and do suffer cascading events leading to widespread blackouts. These blackouts severely impact the public, commerce, and government and are a vulnerability in the nation's infrastructure. Rather than focusing on the detailed causes of individual blackouts, this project addresses the global, complex system dynamics of a long series of blackouts. New models, simulation and analysis methods will be developed to capture the essentials of criticality, self-organization and cascading failure. Particular attention will be given to the power tails of probability distributions of blackout sizes that occur in North American blackout data and generally in systems at criticality. These power tails imply that large, catastrophic blackouts are much more likely than predicted by conventional risk analyses. The project will develop new risk analysis methods and explore operating techniques to mitigate the risks of major blackouts. Communication networks such as the Internet also develop major cascading disruptions and work will also be pursued in this application to maintain some focus on universal features of disruptions in large, engineered networks of societal importance. The expected outcomes are the ability to understand, statistically analyze and to some extent mitigate major cascading disruptions in power transmission and communication networks. The scientific outcomes are an improved understanding and new application of complex system dynamics to the engineering and analysis of stressed networks. Educational outcomes include the training of undergraduate and graduate students in a multidisciplinary team.