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For the development of converter transformer applications, research on the discharge characteristics in transformer oil is required. This article presents an analysis of the streamer discharge characteristics caused by a needle-plate electrode in oil-pressboard insulation under ac voltage and discharge images on the time scale of microseconds. Based on the discharge image, a Gaussian filter, image segmentation of the Otsu algorithm, and Canny edge detection are used to detect the edge of the discharge image. By extracting the discharge profile image, the discharge characteristics are effectively identified. The size and quantity of particles in transformer oil during the discharge are analyzed. Research on the characteristics of streamer discharge propagation is not only helpful for understanding the process of discharge but also has important significance for converter transformer design from the perspective of inhibiting streamer discharge. [ABSTRACT FROM AUTHOR]

As an important piece of equipment of ultrahigh-voltage direct current, the valve side of a converter transformer contains a large dc component prone to partial discharge (PD) under the action of a slightly uneven electric field, which can be simulated using a wedge electrode. To study the PD characteristics of oil–paper insulation under a wedge-shaped electrode, a 2-D axisymmetric simulation model was established based on the bipolar-charge transport theory and the fluid dynamics drift-diffusion theory. The microscopic discharge images at nanosecond scale under different dc voltage polarities were calculated, and the change process of the space charge and electric field intensity distribution was obtained. The effects of the voltage amplitude, polarity, and dielectric constant on PD characteristics are discussed. The simulation results show that the discharge pattern and velocity exhibit a notable polarity effect. This polarity effect is related to the adsorption of the cellulose hydroxyl group to negative charge, which leads to the amplitude of the homopolar charge accumulated in negative polarity being greater than that accumulated in positive polarity under the same applied voltage intensity so that the homopolar charge has a greater barrier to the discharge. This type of adsorption is positively correlated with the difference of dielectric constant between the paperboard and insulating oil. The results of this study are of great theoretical significance for elucidating the dc discharge mechanism under wedge electrodes. [ABSTRACT FROM AUTHOR]

The converter transformer is the most important piece of equipment in ultrahigh voltage direct current (UHVDC) transmission systems. The rectifying valve side of the converter transformer is dealing with composite voltages, containing both ac and dc components. Therefore, the characteristics of the partial discharge (PD) in oil–paper insulation of such rectifying valves are different from those of rectifying valves subjected to pure ac or dc voltage. In this study, theories of hydrodynamic drift-diffusion and bipolar charge transfer were used to build the needle-plate electrode model with a paperboard depression, and experiments were used to verify the feasibility of the simulation method. The electric field and net charge distribution that can reflect the PD were analyzed. Besides, the effects of instantaneous voltage, the proportion of ac–dc components, and depression parameters on the development characteristics of PD were also discussed. Simulation results show that applied voltage, interface charge density, and model parameters can all affect the electric field strength, which in turn influences the development of PD in the depression. This research reveals the process and influencing factors of PD during the electrical aging process, which not only helps to optimize the oil–paper insulation at the rectifying valve side of the converter transformer but also provides a basis for further explaining the PD mechanism. [ABSTRACT FROM AUTHOR]

• The bipolar charge transport and hydrodynamic drift-diffusion models were used. • The PD waveforms under the assessed conditions were unimodal. • Pressboard surface charge can form a shield layer that hinders streamer evolution. • The streamers have voltage-dependent shapes. • The time relationships between PD pulse and streamer evolution were found. A better understanding of the complicated characteristics and interrelationships between the charge distributions and partial discharge (PD) pulse waveforms occurring in oil-pressboard insulation can be used to characterise the PD mechanism as a basis for the optimisation of the insulation structure to minimise PD activity. These characteristics were studied by using a non-inductive resistor to measure the PD pulse waveforms produced in oil-pressboard insulation by a needle-plate at positive DC voltage and through additional simulations based on bipolar charge transport and hydrodynamic drift-diffusion models. It was found that the PD pulse waveforms are unimodal, and with increased applied voltage, their rising and falling edges and equivalent times decrease, and their apparent charge amplitudes and equivalent frequencies increase. These parameters have a saturation state at high voltages (>45 kV) and the oil streamers have voltage-dependent shapes and evolution velocities (v s); the higher the voltages, the higher the values of v s , and the wider are the streamer bodies. Accumulated charge can form a shield layer that hinders streamer evolution. Analysis of the PD mechanism in terms of the relationships between charge distribution and PD pulse waveform reveal that the rising and falling edges of a PD pulse correspond to streamer propagation in the oil gap and charge accumulation at the pressboard surface (i.e., the charging process in the pressboard), respectively. The peak value of the PD pulse waveform is shown to be related to the conduction current in the coupling loop as reflected by the current density at the streamer head. [ABSTRACT FROM AUTHOR]

The DC voltage related partial discharge (PD) classification in solid dielectrics under a uniform electric field has been studied, but it is more complicated in liquid-solid composite insulation under a highly non-uniform electric field. Therefore, PD pulse waveforms and PD channel shapes in oil-pressboard insulation were investigated by simulating a needle-plate model with a positive DC voltage via pulse current method. The elements of PD can be classified in order of ionizing intensity strength as corona, tree-like PD, single-streamer PD, or multi-streamer PD according to the discharge channel shape. The corona pulses are sharply oscillating, whereas the other types of PD can generate unimodal pulses with no over-zero oscillation. A finite element analysis reveals the PD types are related to the charge quantity at the oil-pressboard interface, which influences the streamer evolution by distorting the space electric field. This study uncovers the physical process during PD in oil-pressboard insulation and provides basis for explaining the PD mechanism. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Converter transformers in HVDC system use oil-pressboard as the main insulation. The insulation structures of valve side need to withstand combined AC-DC voltage. Oil-pressboard insulation shows distinctive PD characteristics under combined AC-DC voltage which are the bases of insulation assessment and fault diagnosis. In this paper, PD characteristics are investigated with the established experimental platform of ballplate electrode under 1:1 combined AC-DC voltage. The behavior of experimental results is explained trough discharge mechanism. To reflect the characteristics of the whole PD development process without the influence of test conditions on PD magnitude, Φ-ΔT-N pattern is used to establish the 3D spectrum Hn (ΔT,Φ) based on time interval, phase and repetition rate of PD pulses. Barycenter C (xc, yc) is calculated as a comprehensive feature parameter. In order to exclude the effect of oscillation components on real-time assessment, variational mode decomposition (VMD) is used to extract the primary development trend of the feature parameter. The difference value R (X, Y) between the value of each point in the trend and the reference target decreases in the whole PD development process. And R can assess the PD development degree continuously based on the historical trend without the normalization problem of PD magnitude. [ABSTRACT FROM AUTHOR]

Partition and Recognition of the partial discharge (PD) development stages in oil-pressboard insulation under AC-DC combined voltage stress are the bases for analysis of the insulation faults in converter transformers. In this paper, behavior of different characteristic parameters of the PD activity recorded in the oil-pressboard insulation with needle-plate electrodes is investigated. Beside the known characteristic parameters like amplitude of apparent charge in pC, frequency of occurrence of PD pulse, PD pattern (PRPD-pattern), additional parameters were defined to describe the PD development processes under AC-DC combined voltage stress. Additional parameters are: pulse equivalent time, pulse equivalent frequency and equivalent time-frequency pattern (ETF-pattern). According to the time-variation trends of these characteristic parameters the PD development process can be divided into five stages: initial stage (IS), transition stage (TS), developing stage (DS), steady stage (SS), and pre-breakdown stage (PS). In these five stages the PRPD pattern and ETF pattern have different shapes and characteristics. For the analysis of PRPD pattern and ETF pattern the wavelet moment invariants are extracted. Based on these new features the PD development stages can be recognized using the least square support vector machine (LS-SVM) with the particle swarm optimization (PSO). The recognition rate is about 94%. Finally the possible physical effects of the identified PD development stages in the oil pressboards insulation under AC-DC combined voltage stress are also discussed in this paper. [ABSTRACT FROM PUBLISHER]

Detection and localization of partial discharge are very important in condition monitoring of power cables, so it is necessary to build an accurate recognizer to recognize the discharge types. In this paper, firstly, a power cable model based on FDTD simulation is built to get the typical discharge signals as training samples. Secondly, because the extraction of discharge signal features is crucial, fractal characteristics of the training samples are extracted and inputted into the recognizer. To make the results more accurate, multi-SVM recognizer made up of six Support Vector Machines (SVM) is proposed in this paper. The result of the multi-SVM recognizer is determined by the vote of the six SVM. Finally, the BP neural networks and ELM are compared with multi-SVM. The accuracy comparison shows that the multi-SVM recognizer has the best accuracy and stability, and it can recognize the discharge type efficiently. [ABSTRACT FROM AUTHOR]

Abstract Partial discharge (PD) of high voltage equipment detected by online monitoring is regarded as a key indicator of insulation status. Threshold estimation exerts an important influence on the denoising effects of PD signals after wavelet-based denoising. In order to improve the adaptive performance of wavelet-based denoising and reduce the distortion of denoised signal, an approach of hybrid particle swarm optimization (HPSO) adaptive wavelet threshold estimation (HPSOTE) is presented in this paper. To obtain the global optimum thresholds, a novel hybrid particle swarm optimization algorithm merging crossover mutation and chaos is proposed in HPSOTE which could solve the premature convergence problem of common threshold selection methods. Genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are adopted to compare the effects with HPSOTE. The denoising results of simulated and actual PD signals show that HPSOTE has a faster convergence rate and more effective global optimization ability than the others and significantly improves the credibility and calculation speed. It gives better mean square error (MSE) and amplitude error performance. This HPSOTE can remove the noise effectively and has comparatively high application value in PD online monitoring for smart grid based on big data. [ABSTRACT FROM AUTHOR]

• Non-uniform electric field simulated by a needle-plate model. • PD statistical feature, PD pattern and pulse under either AC or DC voltage studied. • Charge distribution simulated considering the effects of interface charge. • Explanation of underlying PD mechanisms through a PD circuit model. • Cause of PD polarity effect analyzed based on PD mechanisms. The polarity effect of the partial discharge (PD) in oil-pressboard (oil-PB) insulation under a highly non-uniform electric field is remarkable. For intensive analysis of the characteristics and mechanisms of this polarity effect, a non-uniform electric field was simulated by a needle-plate model with oil-PB composite insulation. The PD statistical features, PD pattern and PD pulse were studied via pulse current method, the charge distribution was simulated on the basis of hydrodynamic drift-diffusion model and bipolar charge transport model, and the cause of the polarity effect was analysed based on the PD mechanism which is quantificationally explained via a PD circuit model. It was found that the average apparent discharge amplitude and PD repetition rate of the neg-PD are higher; the average equivalent frequency and equivalent time of neg-PD are higher and lower respectively; the pos-PD pulse is unimodal and the neg-PD pulse is oscillating with some secondary discharges at AC voltage or a back discharge at DC voltage; and the neg-PD pulse has a narrower width owning to the fast rising edge and falling edge. The PD current pulse in the coupling loop is essentially caused by the charging process of the streamer-shorted defect. The cause of the polarity effect is that the positive streamer evolves slowly and can puncture the entire oil gap with an energy-concentrated channel, whereas the negative streamer with a diffused channel evolves faster but cannot puncture the entire oil gap. [ABSTRACT FROM AUTHOR]