Abstract
This paper develops a novel dynamic correction method for the reliability assessment of large oil-immersed power transformers. First, with the transformer oil-paper insulation system (TOPIS) as the target of evaluation and the winding hot spot temperature (HST) as the core point, an HST-based static ageing failure model is built according to the Weibull distribution and Arrhenius reaction law, in order to describe the transformer ageing process and calculate the winding HST for obtaining the failure rate and life expectancy of TOPIS. A grey target theory based dynamic correction model is then developed, combined with the data of Dissolved Gas Analysis (DGA) in power transformer oil, in order to dynamically modify the life expectancy calculated by the built static model, such that the corresponding relationship between the state grade and life expectancy correction coefficient of TOPIS can be built. Furthermore, the life expectancy loss recovery factor is introduced to correct the life expectancy of TOPIS again. Lastly, a practical case study of an operating transformer has been undertaken, in which the failure rate curve after introducing dynamic corrections can be obtained for the reliability assessment of this transformer. The curve shows a better ability of tracking the actual reliability level of transformer, thus verifying the validity of the proposed method and providing a new way for transformer reliability assessment. This contribution presents a novel model for the reliability assessment of TOPIS, in which the DGA data, as a source of information for the dynamic correction, is processed based on the grey target theory, thus the internal faults of power transformer can be diagnosed accurately as well as its life expectancy updated in time, ensuring that the dynamic assessment values can commendably track and reflect the actual operation state of the power transformers.
Highlights
Large oil-immersed power transformers are crucial links between the generators of a power system and the transmission lines and between lines of different voltage levels [1]
First, it can be calculated that the life expectancy of the transformer before overhaul has been reduced to 23.016 years, as shown in Figure 11, from this failure rate curve without considering the effect of oil filtering, the equivalent hot spot temperature (HST) can be obtained as 130.66 ◦ C it can be analyzed from this curve that if the effect of maintenance is not taken into account, the failure rate in the sixth year has reduced 0.1%, which shows that the internal insulation situation has begun to deteriorate and the failure rate is rising rapidly
Obtained using traditional traditional methods, a novel concept of dynamic correction is introduced to the reliability traditional methods, concept of dynamic correction is introduced to the reliability methods, a novel conceptaofnovel dynamic correction is introduced to the reliability assessment of the large assessment the oil-immersed power transformers the based on which, assessment of of the large large oil-immersed power transformers for the first first time, basedas onthe which, with oil-immersed power transformers for the first time, based onfor which, withtime, the transformer oil-paper insulation system (TOPIS)
Summary
Large oil-immersed power transformers are crucial links between the generators of a power system and the transmission lines and between lines of different voltage levels [1]. The grey target theory is employed to process these DGA data, which can dynamically correct the base model so as to ensure the evaluation better tracking the actual reliability level of transformer and accurately reflect its ageing process This has been verified in this paper via the analysis of the actual data of Jiangmen Power Supply Bureau in China Southern Power Grid and the results of the practical case study show that the built model can well track the operational status of transformer.
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