Multi-BP expert system for fault diagnosis of powersystem

Fault diagnosis and assessment is a crucial and difficult problem for power system. Back propagation neural network expert system (BPES) is an often used method in fault diagnosis. However, with the layer numbers increasing, BPES becomes time consuming and even hard to converge. To solve this problem, we divide the whole networks into many sub-BP groups within a short depth and then propose a novel Multi-BP expert system (MBPES) based method for power system fault diagnosis. We use two real power system data sets to test the effectiveness of MBPES. Experimental results show that MBPES obtains higher accuracy than two commonly used methods.

► This work proposes a novel MBPES based method for power system fault diagnosis.
► Construction algorithm and training algorithm of MBPES are developed in the paper.
► MBPES is efficient and obtains higher accuracy than two commonly used methods.