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Compared with a single chemical indicator, the use of multivariate chemical indicators in aging status assessment of transformer cellulose paper insulation can improve the reliability of the evaluation. In this study, a non-destructive method based on multivariate chemical indicators was proposed to evaluate the remaining life of cellulosic paper insulation. The selected chemical indicators closely related to the aging of the insulating paper were analyzed. Additionally, by applying the subjective and objective weighting method, the evaluation information of each indicator was fully extracted to obtain reasonable comprehensive evaluation weights. Besides, the comprehensive evaluation index of multivariate chemical indicators was obtained by using the technique for order preference by similarity to ideal solution method, which is consistent with the deterioration law of paper insulation. Then, the correlation lifespan model between the comprehensive evaluation index of multivariate chemical indicators and the degree of polymerization of insulating paper under different aging stages was established. The effectiveness of the proposed model was verified by experiments. This promising model can increase the accuracy of the condition assessment for the transformer cellulosic paper insulation.

Methanol in oil was used to indirectly evaluate the aging status of cellulosic paper insulation for oil-immersed transformers. However, the distribution of methanol in oil is affected by many factors, not only related to the oil–paper adsorption equilibrium, but also may be affected by the vapor–liquid phase transition. In this study, the adsorption experiments of mineral oil and standard cellulosic Kraft paper for methanol were designed to explore the adsorption equilibrium process at different oil–paper mass ratios under room temperature. The vapor–liquid equilibrium experiments of methanol between oil and gas were carried out to explore the effects of temperature and phase volume ratios. It turned out that: firstly, compared with mineral oil, the Kraft paper has a stronger adsorption capacity for methanol, which makes most of methanol adsorbed in paper when equilibrium at room temperature. Secondly, the increase of oil–paper mass ratios reduces the adsorption of Kraft paper for methanol and makes the equilibrium time longer. Particularly, at a higher oil–paper mass ratio, due to the less paper mass, methanol would “reverse diffusion” from paper to oil standard solution in the early stage of equilibrium. Finally, the presence of methanol in gas phase cannot be ignored. The increase of temperature makes more liquid methanol in oil transferred to the gas phase by the phase transition process, while increasing the oil–gas phase volume ratios in constant volume system can inhibit this process.

Methanol in oil can be used to evaluate the aging status of oil-paper insulation system of power transformers. Many scholars have shown that the production of methanol in oil is closely related to the degradation of paper. However, the methanol distributed in oil is affected by the oil-paper adsorption equilibrium. In this paper, the equilibrium distribution of methanol between oil and paper at different temperatures were investigated. The equilibrium experiments were conducted by soaking methanol-oil standard solution with ordinary Kraft paper at 20°C, 45°C and 60°C respectively. The results showed that temperature obviously affects the adsorption capacity of oil and paper for methanol: with the increase of temperature, the equilibrium time of methanol between oil and paper is accelerated. Within a certain temperature range, the adsorption capacity of paper for methanol will decrease with the increase of temperature. However, when the temperature was near the boiling point of methanol, the content of methanol in oil declined, which might be related to the existence of gaseous methanol at high temperature. At this time, the equilibrium distribution model of methanol changed from the two-phase model of oil-paper system to the three-phase model of oil-paper-gas system.

The method using ethanol to evaluate the cellulose insulation aging condition of oil-immersed transformers has been proposed. At present, the dominating method for detecting ethanol in insulating oil is to use headspace&ndash, gas-chromatography&ndash, mass-spectrometry (HS-GC-MS). However, the problem of quantitative inaccuracy will be sometimes encountered in the actual detection process due to improper instrument parameter setting and improper manual operation. In this study, as an aging marker, ethanol in transformer insulating oil was separated by using VF-624 ms capillary column. The effects of gas-chromatography&ndash, mass-spectrometry (GC-MS) optimization conditions, headspace equilibrium temperature, headspace equilibrium time and standard solution preparation method on the determination of ethanol content in oil were discussed, and optimized measures were proposed. The experimental results showed that the measurement can be more accurate under the headspace temperature of 80 &deg, C and the headspace time of 40 min, and relative standard deviation percentage (RSD%) could reach to 4.62% under this condition. It was also pointed out that, for the preparation of standard solution, the method which controlled the sampling volume of anhydrous ethanol by microliter syringe could make the peak area of ethanol chromatogram have a better linear relationship with the standard curve. Under the similar linear range, the goodness of fitting curve without diluting process could be as high as 0.9993, while the method of preparing the stock solution and diluting stepwise to obtain the fitting curve only had a goodness of 0.9910. The method was validated by standard addition recovery test, and the recovery values obtained were between 90.3% and 95.8%. The optimized method is of great significance for the measurement of ethanol dissolved in insulating oil.

The present “condition-based maintenance decision making” of power transformers will cause large financial losses to electric enterprises, because of not having taken reliability and economy into consideration. To solve this problem, a maintenance decision-making model with the consideration of reliability and economy was established to choose the best maintenance strategy for oil-filled transformers. With the corrected parameters of operating environment and maintenance records, a condition assessment model including DGA test, oil test, and the electrical test was proposed to decide the comprehensive health index of transformers. After establishing the relationship between the fault rate and the comprehensive health index, a reliability evaluation model was formed, which can simulate the impact of different maintenance types. Taking the reliability and economy operation of transformers into consideration, a particle swarm optimization method was developed to solve the optimization model and select the best maintenance strategy according to the current condition of transformers. Two cases were studied and the results demonstrate that the proposed model offers an improved maintenance strategy.