Neural networks for topology determination of power systems

The authors describe a parallel distributed topology classifier. The idea is to determine the system configuration in a very fast way, even in the presence of incorrect or unavailable switch/breaker status and analog measurements. A new supervised learning algorithm suitable for very large training sets is introduced.<<ETX>>