Transmission Network Fault Diagnosis Based On Timed Fuzzy Petri Net

At present,scholars in power system fault diagnosis research achieved a lot,but as the system becomes larger,the complexity of the structure becomes higher When the system fails,there are still interference factors.Such as the loss of fault information,false information,incomplete signals or changes in the inevitable conditions on the scene.The Petri net method can intuitively and accurately describe the discrete dynamic behavior of events that are widely used in power grid fault diagnosis.This thesis first elaborates the basic working principle of Petri net,and combines it with power system to establish a model suitable for fault diagnosis of power grid.In the classification of Petri nets,fuzzy Petri net are used because of their simple reasoning,graphical and visual expression.The fuzzy Petri net used to establish the mathematical model,and the existing models are improved.A nine-tuple fuzzy Petri net model is established.Improved model corrects the weights of input arcs and output arcs,improves the diagnostic performance of the fuzzy Petri nets.Secondly,the timing constraints are added to the fuzzy Petri net model,and initial probability of the library is corrected by protection and circuit breaker action process checked.After the faulty component 1i judged,the protection and circuit breaker action information is evaluated to obtain information such as rejection,misoperation,error or loss report.Finally,through the example analysis of a practical transmission network system and a 220kV typical transmission network,the software Tina is used for simulation verification.Resules show that the misjudgment probability of non-faulty components is effectively reduced and improve the accuracy of diagnosis thrugh this method in the absence of information.