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This contribution describes an evaluation method for phase resolved patterns of partial discharges over time. Therefore, their specific shape characterizes patterns in question. The method searches for these characteristics within PRPD patterns by comparing characterization and PRPD using 2-dimensional cross-correlation. Crosscorrelation represents a measure for the similarity between different PRPD patterns. A use case determines the usability of the method in practice. The result is the time dependent occurrence of specific patterns, respectively specific PD sources. Long-term monitoring data of an aged generator step-up transformer with several PD sources of varying activity is used as PD dataset. PDs are recorded by the use of the electro magnetic PD measurement method, also known as the UHF-method. [ABSTRACT FROM AUTHOR]

The accurate measurement and the investigation of electromagnetic transients are becoming more important, especially with the increasing integration of renewable energy sources into the power grid. These sources introduce new transient phenomena due to the extensive use of power electronics. To achieve this, the measurement devices must have a broadband response capable of measuring fast transients. This paper presents a capacitive electric field sensor-based measurement system to measure transient overvoltages in high-voltage substations. The concept and design of the measurement system are first presented. Then, the design and concept are validated using tests performed in a high-voltage laboratory. Afterwards, two different calibration techniques are discussed: the simplified method (SM) and the coupling capacitance compensation (CCC) method. Finally, three recorded transients are evaluated using the calibration methods. The investigation revealed that the SM tends to overestimate the maximum overvoltage, highlighting the CCC method as a more suitable approach for calibrating transient overvoltage measurements. This measurement system has been validated using various measurements and can be an efficient and flexible solution for the long-term monitoring of transient overvoltages in high-voltage substations.

The introduction of artificial intelligence (AI) to ultra-high-frequency (UHF) partial discharge (PD) monitoring systems in power transformers for the localization of PD sources can help create a robust and reliable system with high usability and precision. However, training the AI with experimental data or data from electromagnetic simulation is costly and time-consuming. Furthermore, electromagnetic simulations often calculate more data than needed, whereas, for localization, the signal time-of-flight information is the most important. A tailored pathfinding algorithm can bypass the time-consuming and computationally expensive process of simulating or collecting data from experiments and be used to create the necessary training data for an AI-based monitoring system of partial discharges in power transformers. In this contribution, Dijkstra's algorithm is used with additional line-of-sight propagation algorithms to determine the paths of the electromagnetic waves generated by PD sources in a three-dimensional (3D) computer-aided design (CAD) model of a 300 MVA power transformer. The time-of-flight information is compared with results from experiments and electromagnetic simulations, and it is found that the algorithm maintains accuracy similar to that of the electromagnetic simulation software, with some under/overestimations in specific scenarios, while being much faster at calculations.

Ultra-high frequency (UHF) partial discharge (PD) measurements in power transformers are becoming popular because of the advantages of the method. Therefore, it is necessary to improve the basic understanding of the propagation of signals inside the transformer tank and the factors that influence the sensitivity of the measurement. Since the winding represents a major obstacle to the propagation of the UHF signals, it is necessary to study the effect of winding design on signal propagation. Previous research activities have studied these effects using simplified models, and it is essential to consider the complexity of propagation in a complete transformer tank. Additionally, the quality of UHF PD measurements depends, to a large extent, on the sensitivity of the UHF sensors. In this contribution, a simulation model consisting of a simple, grounded enclosure with multiple winding designs is used to study the propagation characteristics of UHF signals when an artificial PD source is placed inside the winding. After analysis of the results, the winding designs are incorporated in an existing and validated simulation model of a 420 kV power transformer and analyzed to observe the influence in a more complex structure. Two commonly used sensor designs are also used in the simulation model to receive the signals. In all cases, the propagation and signal characteristics are analyzed and compared to determine the influence of the winding and sensor design on the UHF signals. It is found that the level of detail of winding design has a significant impact on the propagation characteristics. However, the attenuation characteristics of the UHF signals received by the two sensor designs are similar, with the electric field distribution around the sensor being the key difference.

Diagnoses of power transformers by partial discharge (PD) measurement are effective to prevent dielectric failures of the apparatus. Ultra-high frequency (UHF) method has recently received attention due to its various advantages, such as the robustness against external noise and the capability of PD localization. However, electromagnetic (EM) waves radiated from PD tend to suffer attenuation before arriving at UHF sensors, because active part of the transformer disturbs the EM wave propagation. In some cases, that results in poor detection sensitivity. To understand propagation and attenuation characteristics of EM waves and to evaluate the detection sensitivity quantitatively, a computational approach to simulate the EM wave propagation is important. Although many previous researches have dealt with EM wave simulation for transformers, validations of those simulations by comparing with the experimental ones have seldom been reported. In this paper, cumulative energies, signal amplitudes and propagation times of EM waves were measured using a 630 kVA transformer. EM wave propagation was computed using the time-domain finite integration technique and the results were compared with the experimentally obtained ones. These simulation results showed good agreement with the experimental ones. The results can serve as guidelines to improve the efficiency of UHF PD detection and offer the possibility to achieve optimal placement of UHF sensors in power transformers.