Fast and reliable fault analysis in complex power systems

Neural 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.