Visible to the public Cascading Failure Initially from Power Grid in Interdependent Networks

TitleCascading Failure Initially from Power Grid in Interdependent Networks
Publication TypeConference Paper
Year of Publication2017
AuthorsChen, L., Yue, D., Dou, C., Ge, H., Lu, J., Yang, X.
Conference Name2017 IEEE Conference on Energy Internet and Energy System Integration (EI2)
Date Publishednov
ISBN Number978-1-5386-1427-3
KeywordsBlackouts, cascading failure, communication network, Communication networks, complex networks, composability, compositionality, coupling networks, degree distribution, failure analysis, Fragmentation, giant component, inter-network, interdependent networks, intranetwork, Mathematical model, Metrics, Nickel, power engineering computing, power grid, power grid system, power grid vulnerability analysis, power grids, power system, power system faults, Power system protection, power system reliability, pubcrawl, resilience, Resiliency, Robustness, smart power grids
Abstract

The previous consideration of power grid focuses on the power system itself, however, the recent work is aiming at both power grid and communication network, this coupling networks are firstly called as interdependent networks. Prior study on modeling interdependent networks always extracts main features from real networks, the model of network A and network B are completely symmetrical, both degree distribution in intranetwork and support pattern in inter-network, but in reality this circumstance is hard to attain. In this paper, we deliberately set both networks with same topology in order to specialized research the support pattern between networks. In terms of initial failure from power grid or communication network, we find the remaining survival fraction is greatly disparate, and the failure initially from power grid is more harmful than failure initially from communication network, which all show the vulnerability of interdependency and meantime guide us to pay more attention to the protection measures for power grid.

URLhttps://ieeexplore.ieee.org/document/8245336/
DOI10.1109/EI2.2017.8245336
Citation Keychen_cascading_2017