Browsing by Author "Rodríguez, C."
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Item Fast and reliable fault analysis in complex power systems(Institute of Electrical and Electronics Engineers Inc., 1993) Rodríguez, C.; Martín, J. I.; Ruiz, C.; Lafuente, A.; Rementería, S.; Pérez, J.; Muguerza, J.; Tamura, Y.; Suzuki, H.; Mori, H.; SGNeural network approaches to the design of diagnosis systems for electrical networks have to cope with serious problems derived from the large size of such systems, which makes modularity the obvious solution. A modular approach which is based on functional criteria and provides scalability and adaptability to topological changes is presented. The hypotheses generated by the neural system are justified by a competitive system which detects simple or simultaneous disturbances. This approach allows for a parallel, distributed implementation.Item Fault analysis with modular neural networks(1996-02) Rodríguez, C.; Rementería, S.; Martín, J. I.; Lafuente, A.; Muguerza, J.; Pérez, J.; SGAutomatic fault diagnosis in power systems presents real challenges to computing technologies. As an alternative approach to expert systems, several neural network solutions have been proposed recently. In this paper a modular, neural network-based solution to power systems alarm handling and fault diagnosis is described that overcomes the limitations of 'toy' alternatives constrained to small and fixed-topology electrical networks. In contrast to monolithical diagnosis systems, the neural network-based approach presented here fulfills the scalability and dynamic adaptability requirements of the application. Mapping the power grid onto a set of interconnected modules that model the functional behaviour of electrical equipment provides the flexibility and speed demanded by the problem. The way in which the neural system is conceived allows full scalability to real-size power systems.