A New Power System Fault Diagnosis Method Based on Rough Set Theory and Quantum Neural Network

This paper proposed a novel fault diagnosis scheme for estimating the fault section of power system by using hybrid rough set and quantum neural network (RSQNN). The RSQNN approach is developed basing the rough set attributes reduction and quantum neural network recognition. The efficiency and fault tolerance of RSQNN scheme used for fault diagnosis is evaluated in simulation studies, which show promising results that the faults section can be accurately diagnosed in complex power grid and imperfect/uncertain fault information condition.