Determination of Transformers’ Insulating Paper State Based on Classification Techniques

Abstract

The continuity of transformer operation is very necessary for utilities to maintain a continuity of power flow in networks and achieve a desired revenue. Most failures in a transformer are due to the degradation of the insulating system, which consists of insulating oil and paper. The degree of polymerization (DP) is a key detector of insulating paper state. Most research in the literature has computed the DP as a function of furan compounds, especially 2-furfuraldehyde (2-FAL). In this research, a prediction model was constructed based on some of most periodical tests that were conducted on transformer insulating oil, which were used as predictors of the insulating paper state. The tests evaluated carbon monoxide (CO), carbon dioxide (CO2), breakdown voltage (VBD), interfacial tension (IF), acidity (ACY), moisture (M), oil color (OC), and 2-furfuraldehyde (2-FAL). The DP, which was used as the key indicator for the paper state, was categorized into five classes labeled 1, 2, 3, 4, and 5 to express the insulating paper normal aging rate, accelerating aging rate, excessive aging danger zone, high risk of failure, and the end of expected life, respectively. The classification techniques were applied to the collected data samples to construct a prediction model for the insulating paper state, and the results revealed that the fine tree was the best classifier of the data samples, with a 96.2% prediction accuracy.

Accurate Insulating Oil Breakdown Voltage Model Associated with Different Barrier Effects

“…The tstat represents the coefficient of t-test model. In Table 4, tstat can be assessed by the ratio of the mathematical model's coefficients to the SE at each variable coefficient α i , as in Equation (6).…”

“…The transformer's primary failure comes from the insulating system's deterioration, which consists of insulating oil and paper [1,2]. The transformer oil remains the most suitable liquid used in high-voltage apparatus as an insulating medium, but it still breaks under electrical and thermal stresses [3][4][5][6][7][8]. In the presence of a barrier in the insulating oil, the risk of the breakdown is reduced due to the stopping of the charge carriers by the barrier; then, these charge carriers accumulate on the barrier surface, constituting the barrier surface charge.…”

Evaluation of Selected Cellulose Macromolecular Properties after Its Chemical Treatment Using Size Exclusion Chromatography

“…Therefore, based on determination of MWD and DP, it is possible to accurately evaluate the degradation of cellulose and predict its physical and mechanical properties and ongoing chemical reactions. The result of cellulose degradation is an increased proportion of low molecular weight fractions and a decrease in average DP and polydispersity (PD) [ 18 , 19 , 20 , 21 ]. Moreover, DP, as well as crystallinity and crystallite size, have an influence on the thermal stability of cellulose [ 22 , 23 ].…”

Classification of Cellulosic Insulation State Based on Smart Life Prediction Approach (SLPA)

“…The concentration of these parameters, when attaining a prescribed limiting value, indicates that the CSKP insulation is considered to have failed. Since these by-products are directly associated with DP [10][11][12][13][14][15][16], a strong correlation can be established between diagnostic and destructive parameters. This helps to avoid the destructive procedure of CSKP health assessment.…”

“…The Return Voltage Measurement (RVM) and Voltage Response (VR) methods used for insulation diagnosis are some of the commonly used non-destructive testing methods [17,18]. In [11], Ghoneim stressed the role of furfurals along with other parameters in the classification of DP of the cellulose paper. Several classification techniques are applied to obtain a classification model to predict the state of insulation.…”