Study For Techno-Economic Life Of Power Transformer Considering Condition Assessment And Insulation Life Assessment

As valuable asset of the electric power, power transformer need proper follow-up maintenance and returned planning to ensure the reliability and economy during operation. The current planning is often based on the reliability of the transformer, which lead to a lot of transformer operation or decommissioning at the wrong time. At the same time, the development plans are rarely planned from an economic perspective to assess the economic life of the transformer, which caused the high economic loss. Therefore, management to improve the level of power enterprises has a great significance on the actual operation of the transformer state.Through the accelerated aging test by using FDS, various conditions on the insulating paper polymerization degree can be calculated. Considering transformer operation historical load data and the insulation of the running time life assessment data, the solid insulation aging of insulation life assessment model is established. Through calculating the actual transformer insulation life, the life of the proposed evaluation model is effective.Making a connection between the index and missing index, which is used in the adjustment method of the interconnectedness of transformer insulation condition index of fuzziness using set pair for processing. Different index can evaluate the different information reflected by fusion. Transformer insulation condition assessment model is established. Instance evaluation result shows that the model is correct and effective.In the transformer running state, the failure rate and terminates due to maintenance of probability distribution are calculated by Monte Carlo simulation. On the basis of cost and annual operation cost,the quantitative prediction of economic life is finished during the period of transformer insulation life. Results of example show that the prediction model of transformer has a guiding significance on the operational decisions and the planning of the future substation transformation.