Micro-grid Fault Diagnosis Technology Research Based On Fuzzy Petri Net

With the development of the country and the progress of the society, customers are raising a higher requirement on reliability and stability of the supply of electricity. And the requirement of the reliability on Micro-gird is rising too as its spring-up. To insure the safe and stable operation of micro-grid, fault-diagnosis system of micro-grid is becoming a research hotspot.This article is built a fault diagnosis model based on Petri net. The model is combined with fuzzy Petri net and ant colony algorithm to improve the learning ability of the model. To improve the speed and accuracy of algorithm, this article has imported the subsection exchange ant colony algorithm. And the algorithm has been used in simulation platform.Firstly, this article has studied researches on fault diagnosis, and has analyzed algorithms they have used. It has also introduced some of the algorithms such as fault tree analysis, BP neural network, particle swarm optimization and Petri net. Then, it summarized some expansions of Petri net. To improve its learning ability, it determined to combine Petri net with intelligent algorithm. And subsection exchange ant colony algorithm is finally to be used in the model. In experiments the subsection exchange ant colony algorithm has improved the speed and accuracy of fault diagnosis system. At last, the article has built a wind turbine fault diagnosis system on Matlab with Petri net optimized by subsection exchange ant colony algorithm. It also has built a simulation system on power system analysis platform and has a good result.