Correlating empirical data and extended topological measures in power grid networks
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Cited by:
- Chen, Chong & Zhou, Xuan & Li, Zhuo & He, Zhiheng & Li, Zhengtian & Lin, Xiangning, 2018. "Novel complex network model and its application in identifying critical components of power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 316-329.
- Lucas Cuadra & Sancho Salcedo-Sanz & Javier Del Ser & Silvia Jiménez-Fernández & Zong Woo Geem, 2015. "A Critical Review of Robustness in Power Grids Using Complex Networks Concepts," Energies, MDPI, vol. 8(9), pages 1-55, August.
- Lucas Cuadra & Miguel Del Pino & José Carlos Nieto-Borge & Sancho Salcedo-Sanz, 2017. "Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms," Energies, MDPI, vol. 10(8), pages 1-31, July.
- Wu, Di & Ma, Feng & Javadi, Milad & Thulasiraman, Krishnaiya & Bompard, Ettore & Jiang, John N., 2017. "A study of the impacts of flow direction and electrical constraints on vulnerability assessment of power grid using electrical betweenness measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 295-309.
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Keywords
complex networks; graph theory; electrical betweenness; entropy degree; topological measures; fat-tailed distribution; maximal information-based statistics; KS test; Kolmogorov-Smirnov; empirical data; power grids; power networks; malfunction data; European power transmission; robustness; bus attacks; dynamic response; network security; critical infrastructures.;All these keywords.
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