设计弹性配电网
Designing Resilient Electrical Distribution Grids
摘要：
现代社会严重依赖工程基础设施网络提供的服务。当发生自然灾害（如飓风桑迪）时，这些网络提供服务的能力往往会因为网络组件的物理损坏而降低。其中最关键的网络之一是电力，中压配电电路往往遭受最严重的破坏。然而，对这些配电网进行适当的升级可以大大提高事后网络性能。我们制定了一个最佳的配电网设计问题，作为一个两阶段，随机混合整数规划与自然灾害的破坏情况建模为一组随机事件。我们开发和调查的一个确切的和几个启发式算法的基础上分解，是人工智能和运筹学社区开发的技术的混合动力车的易处理性。我们提供的计算证据表明，这些算法有显着的好处相比，商业，混合整数规划软件。
英文摘要：
Modern society is critically dependent on the services provided by engineered infrastructure networks. When natural disasters (e.g. Hurricane Sandy) occur, the ability of these networks to provide service is often degraded because of physical damage to network components. One of the most critical of these networks is electric power, with medium voltage distribution circuits often suffering the most severe damage. However, well-placed upgrades to these distribution grids can greatly improve post-event network performance. We formulate an optimal electrical distribution grid design problem as a two-stage, stochastic mixed-integer program with damage scenarios from natural disasters modeled as a set of stochastic events. We develop and investigate the tractability of an exact and several heuristic algorithms based on decompositions that are hybrids of techniques developed by the AI and operations research communities. We provide computational evidence that these algorithms have significant benefits when compared with commercial, mixed-integer programming software.
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。
