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The Predictive Model Of Faulty Gas In220kV Transformer Based On Gray Theory

Posted on:2015-03-25Degree:MasterType:Thesis
Country:ChinaCandidate:H HuangFull Text:PDF
GTID:2252330428997362Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Electricity has become the main form of energy conversion and utilization, in social life energy directly promote the development of human civilization, and the power system is the major carriers of the electricity’s transmission, distribution and utilization, the power system distribute throughout every corner of society that maintain the production and daily life of human beings.With the increasement of the world’s population, and the gradual development in society and economy, the power system is becoming not only more complex, but also more extensive coverage in area. With the continuous improvement of the transmission technology, EHV transmission has been unable to meet the growing demand of China’s southern and eastern region, send the coal and wind resources in west china through long-distance transmission grid is in great need. Under this background, the state grid proposed development of "UHV" technology. The development of UHV technology has been incorporated into the National Development Plan and the long-term national "five" plan to become an important national energy strategy. The power system of our country is stepping forward to the direction of large units, large power system, high-voltage level and long-distance transmission, Considering the storage of electricity is not easy, the instability will also increase in large scale grid., this trend will undoubtedly bring up a greater challenge to the grid’s safety, reliability and stability.As the main equipment of the conversion of voltage level, if there is a failure in power transformer, it will require a long time to repair, and compared with the exclusion of fault in lines is more complex, it also cost a great need of resources of staffing and money. With the development of our country and the increasing social consumption of electricity, the level and capacity of power transformer is also rising. Once the malfunction of large power transformer cause power outages, it will bring inestimable impaction on industrial production and people’s lives. So if we can use some monitoring technologies to make predictions of the changes in large power transformer as early as possible, and find the latent failures may exist in it, in this way we could make an early maintenance plans to exclusive the fault, greatly improve the reliability of transformer and reduce the probability of occurrence of the power system blackouts, which has positive significance for the safety and stability in operation of the grid.The failure in power transformer is show up in the ways of light, electricity, heat and chemical reactions. And the fault type in oil-immersed transformer can be reflected by the presence of special gases inside the transformer oil. Therefore, this paper based on the principle of transformer oil dissolved gas (DGA), firstly study the applications of various forecasting techniques to predict the dissolved gases in the transformer oil, and concerned the good prediction accuracy of gray system theory, then make an research of the modeling process, data processing, precision inspection in gray system theory, and the gray and multivariate prediction model has been improved from two aspects. At last use the MATLAB modeling and simulation software to verify that the improved prediction model has indeed improved prediction accuracy than traditional models.
Keywords/Search Tags:large power transformer, dissolved gas analysis (DGA), failure prediction, gray theory
PDF Full Text Request
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