Research On Fault Line Selection In Distribution Network Based On Fuzzy Neural Network

Distribution network system will present the zero sequence voltage in the single-phase grounding fault, while the normal phase voltage increases as the line voltage. Engineering allows the fault to operate in a short time 1~2 hours, but with the construction of power distribution automation, its structure is becoming more and more complex. The hidden dangers of the safe and stable operation need to be solved urgently. Based on the summary of relevant experts and scholars studies, the fuzzy neural network theory are proposed by compromising steady fault line selection methods and transient fault line selection methods to solve single-phase grounding fault line selection problem about non-effectively earthed system. The main works are as follows:(1)The fault line selection theories proposed by the relevant experts and scholars at home and abroad of single-phase grounding fault about the non-effectively earthed system are summarized. Existing fault line selection methods are evaluated. Then, it points out that the development trend of fault line selection methods is the combination of steady and transient fault line selection criteria by the theory of artificial intelligence.(2)The characteristics of steady and transient zero sequence current are analyzed theoretically in isolated neutral system and resonance grounding system about single-phase grounding fault.(3)A multi methods fusion fault line selection based on fuzzy theory is studied. Some fault line selection methods about zero sequence current five times harmonic specific phase method, active component of zero sequence current amplitude about the theory of steady-state line selection criterions and wavelet packet coefficient polarity method, transient energy method about the theory of transient line selection criterions are researched, then the corresponding fault measure membership functions is established. Finally, these four methods are proved to have complementary advantages and disadvantages by the simulation analysis under different fault conditions, which proves the reasonability of the integration for the above methods.(4)A fault line selection method based on BP neural network theory is analyzed and studied, the deficiency of neural network is pointed out. Then, the solution to the optimization of BP neural network by genetic algorithm is used. Analysis the advantages and disadvantages about the fuzzy theory and neural network theory. Then, a new fault selection method was proposed based on the fuzzy theory and GA-BP neural network to fuse multi methods.(5)The methods of fuzzy GA-BP neural network is simulated. The simulation results show that the method is effective. So as to provide an idea and method to solve the problem of fault line selection. Compared with the fuzzy GA-BP neural network and fuzzy BP neural network. The results show that the former has better accuracy than the latter and the genetic algorithm has a good improvement effect to BP neural network.