Research Of Power Transformer's Condition Analysis And Maintenance Decision-Making

The power transformer is one of the most important equipment of the power system. The power distribution reliability and safety of power system is directly affected by the transformer whether it can run or not. Maintenance control becomes more and more important when the capacity of power system becomes more and more large and the requirement of the power distribution reliability to the customers becomes more and more strict. The ratio of the maintenance costs in the power costs is increasing. Under the condition maintenance structure, the most important thing is how to choose rational maintenance program and exact maintenance schedule in order to save maintenance costs.A new method based on probabilistic neural networks (PNN) to transformer fault diagnosis is presented, the major features of the probabilistic neural networks stems from its modular architecture design and can be easily extended to adapt to a changing environment by incremental learning. The genetic algorithm is introduced to train the smoothing factor of PNN in order to increase the accuracy of diagnosis. Firstly, the improvement of grey situation decision, superiority evaluation, TOPSIS are introduced into this paper, and the grey situation decision method was been retrofitted by fuzzy pattern recognition. Using the social choice function, the power transformer condition maintenance synthetic decision-making method is formed by the consolidation and re-collation of the result of three decision-making method mentioned above. Secondly, the condition maintenance evaluation index structure is established including the requirement of safety, reliability, economy and others, the weights of the evaluation index are determined by analytic hierarchy process. Finally, two different instances are simulated by the power transformer condition maintenance synthetic decision-making method, and this method is proved to be correct. The power transformer online diagnosis and maintenance decision-making system is developed by the theory mentioned above.