Evolutionary Algorithms for Community Detection in Continental-Scale High-Voltage Transmission Grids
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Guerrero López, Manuel Alejandro![University of Almería authority University of Almería authority](/themes/Mirage2/images/autoridades/autoridad.png)
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2019-12-03Abstract
Symmetry is a key concept in the study of power systems, not only because the admittance and Jacobian matrices used in power flow analysis are symmetrical, but because some previous studies have shown that in some real-world power grids there are complex symmetries. In order to investigate the topological characteristics of power grids, this paper proposes the use of evolutionary algorithms for community detection using modularity density measures on networks representing supergrids in order to discover densely connected structures. Two evolutionary approaches (generational genetic algorithm, GGA+, and modularity and improved genetic algorithm, MIGA) were applied. The results obtained in two large networks representing supergrids (European grid and North American grid) provide insights on both the structure of the supergrid and the topological differences between different regions. Numerical and graphical results show how these evolutionary approaches clearly outperform to the well-kno...
Palabra/s clave
power grids
supergrids
high-voltage power transmission
complex networks
community detection
modularity
evolutionary algorithms
generational genetic algorithm
modularity and improved genetic algorithm
Louvain modularity algorithm
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