Community detection in national-scale high voltage transmission networks using genetic algorithms. (October 2018)

• Record Type: Journal Article
• Authors: Guerrero, Manuel; Montoya, Francisco G.; Baños, Raúl; Alcayde, Alfredo; Gil, Consolacíon
• Is Part Of: Advanced engineering informatics. Volume 38(2018)
• Page Start: 232
• Page End: 241
• Publication Date: 2018-10
• Subjects: Electric power system -- Power grid -- High voltage transmission networks -- Contingency analysis -- Community detection -- Genetic algorithms; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2018.07.001
• Languages: English
• ISSNs: 1474-0346

Abstract

Graphical abstract: Highlights: The community detection problem is applied in national-scale power grids. Real power grids (Italy, France, Germany, Iberian peninsula and Texas) are evaluated. Genetic algorithms are able to obtain any number of communities in a fast way. Topological information of national-scale power grids is analyzed. These methods allow to study the vulnerabilities of real power grids. Abstract: The large-scale interconnection of electricity networks has been one of the most important investments made by electric companies, and this trend is expected to continue in the future. One of the research topics in this field is the application of graph-based analysis to identify the characteristics of power grids. In particular, the application of community detection techniques allows for the identification of network elements that share valuable properties by partitioning a network into some loosely coupled sub-networks (communities) of similar scale, such that nodes within a community are densely linked, while connections between different communities are sparser. This paper proposes the use of competitive genetic algorithms to rapidly detect any number of community structures in complex grid networks. Results obtained in several national- scale high voltage transmission networks, including Italy, Germany, France, the Iberian peninsula (Spain and Portugal), Texas (US), and the IEEE 118 bus test case that represents a portion of the American Electric Power System (in the Midwestern US), show the good performance of genetic algorithms to detect communities in power grids. In addition to the topological analysis of power grids, the implications of these results from an engineering point of view are discussed, as well as how they could be used to analyze the vulnerability risk of power grids to avoid large-scale cascade failures.