The oil‐pressboard insulation on the valve side of the converter transformer withstands pulsating square wave voltage. The voltage contains lots of DC components and high‐order harmonics, which is likely to cause insulation failures. The partial discharge and space charge experiments of oil‐impregnated pressboard under DC superimposed harmonic voltage are conducted to study the effects of harmonic frequency and DC components on the discharge and charge accumulation and to explore the correlation mechanism of charge dynamic behaviour and discharge. Firstly, it is found that high‐order harmonic voltage promotes the partial discharge generation, but DC component suppresses the discharge. Moreover, the charge inside the pressboard is mainly injected in the same polarity and accumulates over time. The space charge density near the electrode increases with the increase of harmonic frequency, and the large amount of charge injection leads to electric field distortion. Meanwhile, the electric field direction changes faster, and the frequent charge injection and extraction behaviours make the charge recombination intensify, which promotes the discharge. Through the above analysis, the influence law of harmonic voltage on the failure of oil‐pressboard insulation is obtained, providing a theoretical basis for the structural optimisation and condition assessment of the converter transformer insulation.

The ultra high voltage direct current (UHVDC) transmission system has advantages in delivering electrical energy over long distance at high capacity. UHVDC converter transformer is a key apparatus and its insulation state greatly affects the safe operation of the transmission system. Partial discharge (PD) characteristics of oil-pressboard insulation under combined AC-DC voltage are the foundation for analyzing the insulation state of UHVDC converter transformers. The defect pattern recognition based on PD characteristics is an important part of the state monitoring of converter transformers. In this paper, PD characteristics are investigated with the established experimental platform of three defect models (needle-plate, surface discharge and air gap) under 1:1 combined AC-DC voltage. The different PD behaviors of three defect models are discussed and explained through simulation of electric field strength distribution and discharge mechanism. For the recognition of defect types when multiple types of sources coexist, the Random Forests algorithm is used for recognition. In order to reduce the computational layer and the loss of information caused by the extraction of traditional features, the preprocessed single PD pulses and phase information are chosen to be the features for learning and test. Zero-padding method is discussed for normalizing the features. Based on the experimental data, Random Forests and Least Squares Support Vector Machine are compared in the performance of computing time, recognition accuracy and adaptability. It is proved that Random Forests is more suitable for big data analysis.

The converter transformer is subjected to AC/DC composite voltage during operation, and the sealed and time-varying internal state makes its electric field distribution and charge accumulation unable to be monitored in real-time experiments. In this paper, aiming at the influence of bubbles in the oil passage of the converter transformer on charge accumulation before discharge, a simulation model in a laminar flow environment is established, and four different calculation conditions are set to simulate the charge accumulation in 1 s. It is found that under laminar flow conditions, the trapped bubbles on the insulation paper wall play an obvious role in intensifying the charge accumulation in transformer oil, and the extreme range of charge density will increase by about 10⁴ times. Bubbles aggravate the electric field distortion, and the insulation strength of bubbles is lower, which becomes the weak link of insulation. In the laminar flow environment, the oil flow will take away part of the accumulated charge in the oil, but in the case of trapped bubbles, the charge accumulation in the insulating paper will increase from the order of 10⁻² to 10⁻¹. In the case of no bubbles, the transformer oil layer flow will increase the charge accumulation in the insulation paper by 4–5 orders of magnitude. Therefore, it can be seen that the flow of transformer oil will increase the deterioration level of insulation paper. And when the transformer oil is already in the laminar flow state, the influence of laminar flow velocity on charge accumulation is not obvious. The research results in this paper provide a time-varying simulation reference state for the charge accumulation problem that cannot be measured experimentally under normal charged operation conditions, and we obtain quantitative numerical results, which can provide a valuable reference for the study of transformer operation and insulation discharge characteristics.