Effectiveness Analysis and Temperature Effect Mechanism on Chemical and Electrical-Based Transformer Insulation Diagnostic Parameters Obtained from PDC Data

Abstract

Abstract:The dielectric monitoring/diagnostic tool, such as Polarization and Depolarization Current (PDC) measurement, is now being widely applied to obtain the status of deteriorated transformers around the world. Nowadays, several works have reported that the chemical and electrical-based transformer insulation diagnostic parameters (absorption ratio, polarization index, paper conductivity, oil conductivity, insulation resistance, etc.) can be easily calculated from the PDC data. It is a fact that before using these parameters to obtain the status of deteriorated transformers, the power engineers should prudently investigate the effectiveness of these parameters. However, there are few papers that investigate the important issue. In addition, the understanding of temperature effect mechanism on these parameters should also be prudently studied. In the present work, we firstly prepare several oil-impregnated pressboard specimens with various insulation statuses by using a sequence of thermal ageing and moisture absorption experiments launched in the laboratory, and then the PDC measurement is performed to obtain the chemical and electrical-based transformer insulation diagnostic parameters. Finally, we systematically interpret the effectiveness and temperature effect mechanism on these chemical and electrical-based transformer insulation diagnostic parameters.

Transformer Fault Diagnosis Technology Based on Maximally Collapsing Metric Learning and Parameter Optimization Kernel Extreme Learning Machine

“…However, the above computational technologies are often employed with a single characteristic gas or characteristic gas ratio as the input vectors of classifiers to achieve transformer fault diagnosis. These adopted a single gas or the content ratio cannot show the relationship between the transformer fault and gases completely, and the limitation may affect the accuracy of the diagnosis result [20,21]. Hence, a new DGA features combination is proposed, and maximally collapsing metric learning algorithm (MCML) is employed to determine the optimal DGA features combination.…”

Precise Measurements of the Temperature Influence on the Complex Permittivity of Power Transformers Moistened Paper-Oil Insulation

“…Considering the type of voltage used in measurements, the electrical methods used for transformer diagnostics can be divided into two groups. The group of DC methods includes Return Voltage Measurement (RVM) [22][23][24] and Polarization Depolarization Current (PDC) [25][26][27]. The Frequency Domain Spectroscopy (FDS) method [28][29][30] uses alternating voltage in the low and ultra-low frequency ranges.…”

Normalization for FDS of Transformer Insulation Considering the Synergistic Effect Generated by Temperature and Moisture

“…Reviewing the existing researches, the approaches for state evaluation and condition monitor of transformer cellulose insulation have been widely reported. The typical analysis method is constituted of direct measurement (including the degree of polymerization [7], tensile strength [8], and Karl Fischer titration [9]), dissolved chemical indicators in the oil (dissolved gas [10], acid, aldehyde [11], furfural [12]), electrical indicators (insulation resistance, absorption ratio [13]), the theory of chemical reaction kinetics (aging kinetics model [14]- [16]), and especially dielectric response technique (time-domain response [17][18] and frequency-domain spectroscopy, FDS [19]- [20]). Relying on the strong anti-interference and the rich insulation information, the FDS is thus of great interest to the scholars in lab or field conditions [4].…”