Network hierarchy evolution and system vulnerability in power grids

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The seldom addressed network hierarchy property and its relationship with vulnerability analysis for power transmission grids from a complex-systems point of view are given in this paper. We analyze and compare the evolution of network hierarchy for the dynamic vulnerability evaluation of four different power transmission grids of real cases. Several meaningful results suggest that the vulnerability of power grids can be assessed by means of a network hierarchy evolution analysis. First, the network hierarchy evolution may be used as a novel measurement to quantify the robustness of power grids. Second, an antipyramidal structure appears in the most robust network when quantifying cascading failures by the proposed hierarchy metric. Furthermore, the analysis results are also validated and proved by empirical reliability data. We show that our proposed hierarchy evolution analysis methodology could be used to assess the vulnerability of power grids or even other networks from a complex-systems point of view.Peer ReviewedPostprint (author's final draft

Planning Sensitivities for Building Contingency Robustness and Graph Properties into Large Synthetic Grids

Interest in promoting innovation for large, high-voltage power grids has driven recent efforts to reproduce actual system properties in synthetic electric grids, which are fictitious datasets designed to be large, complex, realistic, and totally public. This paper presents new techniques based on system planning sensitivities, integrated into a synthesis methodology to mimic the constraints used in designing actual grids. This approach improves on previous work by explicitly quantifying each candidate transmission line’s contribution to contingency robustness, balancing that with geographic and topological metrics. Example synthetic grids build with this method are compared to actual transmission grids, showing that the emulated careful design also achieves observed complex network properties. The results shed light on how the underlying graph structure of power grids reflects the engineering requirements of their design. Moreover, the datasets synthesized here provide researchers in many fields with public power system test cases that are detailed and realistic