Study on Quantitative Correlations between the Ageing Condition of Transformer Cellulose Insulation and the Large Time Constant Obtained from the Extended Debye Model

Abstract

Polarization-depolarization current (PDC) measurements are now being used as a diagnosis tool to predict the ageing condition of transformer oil-paper insulation. Unfortunately, it is somewhat difficult to obtain the ageing condition of transformer cellulose insulation using the PDC technique due to the variation in transformer insulation geometry. In this literature, to quantify the ageing condition of transformer cellulose insulation using the PDC technique, we firstly designed a series of experiments under controlled laboratory conditions, and then obtained the branch parameters of an extended Debye model using the technique of curve fitting the PDC data. Finally, the ageing effect and water effect on the parameters of large time constant branches were systematically investigated. In the present paper, it is observed that there is a good exponential correlation between large time constants and degree of polymerization (DP). Therefore, the authors believe that the large time constants may be regard as a sensitive ageing indicator and the nice correlations might be utilized for the quantitative assessment of ageing condition in transformer cellulose insulation in the future due to the geometry independence of large time constants. In addition, it is found that the water in cellulose pressboards has a predominant effect on large time constants.

Dissolved Gas Analysis Principle-Based Intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey

“…Besides, in order to develop more accurate diagnostic tools based on DGA, a large number of information processing-based algorithms have been extensively investigated, e.g., Abu-Siada and Hmood [88] proposed a new fuzzy logic algorithm to identify the power transformer criticality based on the dissolved gas-in-oil analysis; Illias et al [89] developed a hybrid modified evolutionary particle swarm optimizer (PSO) time varying acceleration coefficient-ANN for power transformer fault diagnosis, which can obtain the highest accuracy than the previous methods; Pandya and Parekh [90] presented how interpretation of sweep frequency response analysis traces can be done for open circuit and short circuit winding faults on the power transformer. All of the above mentioned intelligent approaches have improved the conventional DGA-based transformer fault diagnosis methods, and directly or indirectly improved the accuracy of fault diagnosis for the oil-immersed power transformers [91,92]. In essence, the application of AI for transformer fault diagnosis is fundamentally still based on the analysis of the content of dissolved gas in transformer oil.…”

Hot Spot Temperature and Grey Target Theory-Based Dynamic Modelling for Reliability Assessment of Transformer Oil-Paper Insulation Systems: A Practical Case Study

“…Here, Tenbohlen et al [12] presented the status and current trends of different diagnostic techniques of power transformers, including the DGA, partial discharge (PD), International Electrotechnical Commission (IEC), ultra-high frequency (UHF), frequency response analysis (FRA), polarization and depolarization currents (PDC), and frequency domain spectroscopy (FDS). Among them, the PDC measurements, as a diagnosis tool, is difficult to be employed to obtain the ageing condition of transformer cellulose insulation due to the variation in transformer insulation geometry [13].…”

“…Besides, the model is built with a structure of the base model plus the dynamic correction model, such that the introduction of dynamic correction makes the entire reliability evaluation model can be adjusted according to operation state of the evaluation object, thus the credibility is higher. Moreover, the model built in this paper selects the DGA data as a source of information for dynamic correction instead of the characteristic parameters reflecting the reliability of transformer oil-paper insulation, such as DP [13] and VFF. This is because the operations of the power transformer, e.g., oil filtering and maintenance, have a great impact on furfural's concentration.…”

Adaptive Virtual Impedance Droop Control Based on Consensus Control of Reactive Current

“…Apart from ensuring the quality of power output, the inverter control system should be able to coordinate the operation of multiple distributed generators (DGs) and distribute power to loads according to the capacity of each power source [4]. Research on energy management, reliability of component, coordination, and optimization of renewable energy in hybrid microgrids has been conducted [5][6][7][8][9]. The droop control system, based on the droop characteristic of synchronous generators, offers the benefits of sparse communication and 'plug and play'.…”