Pol Paradell, Yannis Spyridis, Alba Colet, A. Ivanova, J. Domínguez-García, Achilleas Sesis, G. Efstathopoulos
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Increasing resilience of power systems using intentional islanding; a comparison of Binary genetic algorithm and deep learning based method
Several algorithms combining qualitative and quantitative components are currently used for splitting a large interconnected power grid into islands as a measure to provide the best reconfiguration option when a fault appears. The aim of this article is to compare the clustering results of a binary genetic algorithm and a deep learning based method in order to identify the differences and to find in which cases it is rather better applicable each of the techniques.
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