Novel hierarchical fault diagnosis approach for smart power grid with information fusion of multi-data resources based on fuzzy petri net

Considering the problem of the complicated structure of smart power grid, the varied topology after fault and multi-data resources of fault information, this paper presents a novel hierarchical fault diagnosis approach for smart power grid with information fusion of multi-data resources based on fuzzy Petri net, which contains diagnosis layers of the switch and the information fusion of multi-data. In the diagnosis layer of switch, the network topology is established based on the information provided by the SCADA system. In the diagnosis layer of the information fusion of multi-data, a smart power grid fault-diagnosis method of directional weighted fuzzy Petri nets using the diagnosis information from fault recorder and WAMS is presented, which considering the information of protection and circuit breaker. Then fault diagnosis is conducted information fusion with the improved D-S evidence theory. Finally, the diagnostic decision is obtained with C-means algorithm. The simulation shows that the method has good adaptability, and in the case of incomplete information, the method can still obtain correct diagnosis results, and has certain universality and fault tolerance ability.