4.7 Article

Electrical and topological drivers of the cascading failure dynamics in power transmission networks

期刊

RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 175, 期 -, 页码 196-206

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2018.03.011

关键词

Power grids; Vulnerability assessment; Cascading failures; DC power flow; Sensitivity analysis; Probabilistic performance metrics

资金

  1. Politecnico di Milano, Rice University
  2. U.S. National Science Foundation [CMMI-1436844, CMMI-1541033]
  3. U.S. Department of Defense through its Army Research Office [W911NF-13-1-0340]
  4. Data Analysis and Visualization Cyberinfrastructure - NSF [OCI-0959097]
  5. Directorate For Engineering [1436845] Funding Source: National Science Foundation
  6. Divn Of Social and Economic Sciences [1541033] Funding Source: National Science Foundation

向作者/读者索取更多资源

To systematically study key factors affecting cascading failures in power systems, this paper advances algorithms for generating synthetic power grids with realistic topological and electrical features, while computationally quantifying how such factors influence system performance probabilistically. Key parameters affecting line outages and power losses during cascading failures include line redundancy, load/generator layout and re-dispatch strategies. Our study combines a synthetic power grid generator with a direct current (DC) cascading failure simulator. The impact of each of the factors and their interactions unravel useful insights for interventions aimed at reducing the probabilities of large blackouts on existing and future power systems. Moreover, conclusions drawn from a spectrum of different power grid topologies and electrical configurations offer more generality than typically attained when studying specific test cases. Line redundancy and distributed generation appear as the most efficacious parameters for reducing the probabilities of large power losses and multiple line overloads, although the effect decays with network density. Also, re-dispatch strategies are critical on the distribution of the cascading failure size in terms of line failures. These and related results provide the basis for probabilistic analyses and future design of evolving power transmission systems under uncertainty. (C) 2018 Published by Elsevier Ltd.

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