Robust Topology Design of Complex Infrastructure Systems

级联故障 停电 稳健性(进化) 网络拓扑 电力系统 可靠性工程 计算机科学 电力系统保护 复杂网络 分布式计算 网格 拓扑(电路) 工程类 功率(物理) 计算机网络 物理 万维网 电气工程 基因 化学 量子力学 生物化学 数学 几何学
作者
Joseph Piacenza,Scott Proper,Mir Abbas Bozorgirad,Christopher Hoyle,Irem Y. Tumer
出处
期刊:ASCE-ASME journal of risk and uncertainty in engineering systems, [ASM International]
卷期号:3 (2) 被引量:6
标识
DOI:10.1115/1.4036152
摘要

Abstract Optimizing the topology of complex infrastructure systems can minimize the impact of cascading failures due to an initiating failure event. This paper presents a model-based design approach for the concept-stage robust design of complex infrastructure systems, as an alternative to modern network analysis methods. This approach focuses on system performance after cascading has occurred and examines design tradeoffs of the resultant (or degraded) system state. In this research, robustness is classically defined as the invariability of system performance due to uncertain failure events, implying that a robust network has the ability to meet minimum performance requirements despite the impact of cascading failures. This research is motivated by catastrophic complex infrastructure system failures such as the August 13th Blackout of 2003, highlighting the vulnerability of systems such as the North American power grid (NAPG). A mathematical model was developed using an adjacency matrix, where removing network connections simulates uncertain failure events. Performance degradation is iteratively calculated as failures cascade throughout the system, and robustness is measured by the lack of performance variability over multiple cascading failure scenarios. Two case studies are provided: an extrapolated IEEE 14 test bus and the Oregon State University (OSU) campus power network. The overarching goal of this research is to understand key system design tradeoffs between robustness, performance objectives, and cost, and explore the benefits of optimizing network topologies during the concept-stage design of these systems (e.g., microgrids).

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