Search

The evaluation of the state of transformer oil-immersed insulation based on the traditional methods becomes unreliable due to the nonuniform aging effect. To address this issue, a novel model for accessing the aging information of transformer oil-immersed insulation at the hotspot is proposed. In this article, frequency-domain spectroscopy (FDS) is selected as the carrier for characterizing the aging states of oil-immersed insulation. The multiobjective function for reversing the FDS of the hotspot is constructed based on the dielectric response equivalent circuit. Then, the nondominated sorting genetic algorithm with the multiconstraint scheme is proposed to solve the multiobjective function, by which the FDS data of the transformer hotspot region are acquired. The verification results indicate that the average standard deviation between the computed FDS of the hotspot region and the measured data is less than 0.26. The contribution of this article is in the exploration of the proposed model as a potential tool to extract the FDS data of the hotspot region. This will promote a more reliable aging evaluation of the transformer oil-immersed paper insulation at the hotspot. [ABSTRACT FROM AUTHOR]

The traditional method for transformer moisture diagnosis is to establish empirical equations between feature parameters extracted from frequency domain spectroscopy (FDS) and the transformer’s moisture content. However, the established empirical equation may not be applicable to a novel testing environment, resulting in an unreliable evaluation result. In this regard, it is acknowledged that FDS combined with machine learning is more suitable for estimating moisture content in a variety of test environments. Nonetheless, the accuracy of the estimation results obtained using the existing method is limited by the algorithm’s inability to generalize. To address this issue, we propose an AdaBoost algorithm-enhanced back-propagation neural network (BP_AdaBoost). This study creates a database by extracting feature parameters from the FDS that characterize the insulation states of the prepared samples. Then, using the BP_AdaBoost algorithm and the newly constructed database, the moisture estimation models are trained. Finally, the results of the estimation are discussed in terms of laboratory and field transformers. By comparing the proposed BP_AdaBoost algorithm to other intelligence algorithms, it is demonstrated that it not only performs better in generalization, but also maintains a high level of accuracy. [ABSTRACT FROM AUTHOR]

The generation and distribution of furfural are significantly affected by moisture content in the insulating paper. However, the diffusion mechanism of furfural under moisture effect is not clear, hence, this study investigates the effect of moisture on the diffusion characteristics of furfural by combining macro experiment and micro molecular dynamics simulation. The simulation results demonstrate that the increased moisture content in paper accelerates the diffusion of furfural from paper to oil, which is also proved by the experimental data. Then, the results of interaction energy analysis indicate that the increase of moisture enhances the van der Waals force between oil and furfural. The present findings are expected to improve the theoretical level of furfural analysis, which will facilitate the aging evaluation of the transformer insulating paper based on furfural. [ABSTRACT FROM AUTHOR]

The space charge effect of transformer insulating paper will distort its internal electric field, and its space charge effect will be more prominent under extremely complex working conditions. At present, the micromechanism of charge transport and electric field distortion characteristics of paperboard are not clear under complex working conditions. So in this article, based on the bipolar carrier transport (BCT) model and the dynamic carrier balance model, the effects of high temperature, aging degree, moisture content, and bent degree on charges accumulation in paperboard are studied under dc high voltage by numerical simulation and the measured data needed for simulation. The results show that the higher temperature strengthens the carrier migration, deepens the injection depth of the charge, and aggravates the distortion of electric field intensity in paperboard. The more extended the aging time of paperboard, the greater the internal trap density and the deeper the trap depth, which lead to charges migration difficultly. Increasing water content in the paperboard will accelerate space charges to reach a steady state, while further increasing it will slow down this process, which is related to the shallow trap getting deeper. When the critical part of paperboard is extruded, many traps are introduced, resulting in charges accumulation seriously. The research results can reference the design of paperboard and the maintenance of transformer insulation system. [ABSTRACT FROM AUTHOR]

The influence of nonuniform aging has not been considered in the prediction of the frequency domain spectroscopy (FDS) of the transformer oil-paper insulation (OPI) when using the finite element method (FEM). Given this issue, the modified simulation model was constructed based on the XY model and FEM. In the current work, the dielectric response property of the pressboards with different aging conditions in the modified model was characterized by its dielectric response parameters measured in the lab. Then the modified simulation model constructed in a 3-D system would be applied to study the effect of both nonuniform aging and the axial geometry on the FDS of OPI. Finally, the feasibility of the proposed models was verified by comparing the measured FDS and the predicted FDS. This article is expected to provide a model for predicting the FDS of the transformer OPI including the effect of nonuniform aging. [ABSTRACT FROM AUTHOR]

Moisture is one of the critical factors to determine the service life of transformers. The moisture inside the transformer oil-immersed insulation could be quantified with feature parameters. This article proposes and develops a genetic algorithm support vector machine (GA-SVM) model to carry out the moisture diagnosis. Present findings reveal that these feature parameters can be obtained by using frequency-domain spectroscopy. Therefore, a novel model for predicting the frequency-domain spectroscopy curves is first reported based on a small number of samples, which could be utilized to obtain the feature parameters database to develop GA-SVM. Then, the moisture diagnosis in the lab and field conditions is presented to verify its feasibility and accuracy. The novelty of this article is in an exploration of the reported model as an intelligent based moisture diagnosis tool for power transformers. [ABSTRACT FROM AUTHOR]

The dielectric modulus Μ∗(ω) is used for studying the frequency domain response and activation energy (E a) of transformer immersed cellulose insulation. Existing literatures show that the temperature is a crucial factor affecting the Μ∗(ω) and aging rate of transformer oil-paper insulation, while the E a can be regarded as an indicator to reflect the average aging rate of the transformer immersed cellulose insulation. Therefore, the discussion of the temperature-dependence on both Μ∗(ω) and E a is of great significance. This paper attempts to report an approach for understanding the temperature impact on both Μ∗(ω) and E a. The obtained knowledge can be used to establish two available models for temperature correction on Μ∗(ω) and activation energy prediction of transform immersed cellulose insulation, respectively. These findings are expected to promote the reliability of the condition prediction result of transformer immersed cellulose insulation by using Μ∗(ω) and E a technique. [ABSTRACT FROM AUTHOR]

Over the past few years, frequency domain spectroscopy (FDS) has been widely utilized to assess transformer insulation. Many investigations have revealed that the FDS measurement has been observed to be dependent on service conditions (aging, moisture, geometry, and temperature). During the onsite FDS measurement, the inner insulation temperature of the de-energized transformer gradually decreases, which affects the FDS results due to moisture migration from oil to the cellulose insulation. This process gives rise to misinterpreting of the condition of the transformer insulation. Presently, the master curve technique reported by several researchers is utilized for temperature correction in FDS measurements. In fact, various researchers have obtained different master curves, so making a universal approach to temperature correction has become an important topic. In the present investigations, a series of experiments was performed on oil-impregnated pressboard insulation under laboratory conditions which was followed by FDS measurements at lower than operating temperature and a universal master curve for temperature correction was studied. Activation energies from oil-impregnated pressboard tests support the effectiveness of the proposed universal approach for temperature correction. [ABSTRACT FROM AUTHOR]

The service life of a transformer is determined by the condition of its oil?paper insulation. A modified Cole?Cole model was introduced to describe the frequency domain spectroscopy (FDS) curves based on the classic Debye relaxation model and thereby accurately determined the ageing state of the insulation of a power transformer using FDS. Oil?paper insulation samples with different ageing states are prepared under laboratory conditions, and a characteristic parameter is extracted to quantify their ageing states after a detailed investigation of the frequency domain dielectric properties of the samples. Results reveal that the modified Cole?Cole model, including the ? relaxation components, dc and hopping conductivity components, can be employed to effectively model the frequency dielectric characteristics of oil?paper insulation. Furthermore, the extracted characteristic parameter from this model, ??, can be utilized in the quantitative evaluation of the ageing states of transformer insulation. A case example is discussed to demonstrate the applicability of the proposed technique in the condition assessment of field power transformers. [ABSTRACT FROM AUTHOR]