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EN
The results of two applications of multi-objective genetic algorithms to the analysis and optimization of electrical transmission networks are reported to show the potential of these combinational optimization schemes in the treatment of highly interconnected, complex systems. In a first case study, an analysis of the topological structure of an electrical power transmission system of literature is carried out to identify the most important groups of elements of different sizes in the network. The importance is quantified in terms of group closeness centrality. In the second case study, an optimization method is developed for identifying strategies of expansion of an electrical transmission network by addition of new lines of connection. The objective is that of improving the transmission reliability, while maintaining the investment cost limited.
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