High voltage direct current (HVDC) systems are now well integrated into AC systems in many jurisdictions. The integration of renewable energy sources (RESs) is a major focus and the role of HVDC systems is expanding. However, the protection of HVDC systems against DC faults is a challenging issue that can have negative impacts on the reliable and safe operation of power systems. Practical solutions to protect HVDC grids against DC faults without a widespread power outage include: 1) using DC circuit breakers (CBs) to isolate the faulty DC-link, 2) using a proper converter topology to interrupt the DC fault current, and/or 3) using high-power DC transformers and DC hubs at strategic points within DC grids. The application of HVDC CBs is identified as the best approach that satisfies both DC grids and connected AC grids' requirements. This article reports a comprehensive review of HVDC CBs technologies, including recent significant attempts in the development of modern HVDC CBs. The functional analysis of each technology is presented. Additionally, different technologies based on information obtained from literature are compared. Finally, recommendations for the improvement of CBs are presented.

High voltage circuit breakers (HVCBs) play a critical role on providing the desired reliability, and resiliency in power systems. In order to extend their lifetime and predict the failures, various maintenance policies could be applied on these critical components. Amongst these strategies, condition-based maintenance (CBM) provides a satisfactory agreement with future smart environment. This paper aims to provide an insight into the relevant developments in this subject and to explore the viable visions compatible with future research stream. Accordingly, three directions, i.e. diagnostic signals, intelligent modelling and using monitoring data in asset management have been addressed in this paper. It presents challenges dealing with real-time assessment of the diagnostic signals relating to measurements, and analyses. Subsequently, the issues associated with using artificial intelligent (AI) and Machine learning for providing intelligent algorithms have been discussed. Finally, the connection between the monitoring data and the asset management approach is investigated. The latter is looking for the subjects including remaining lifetime estimation, prioritization, and health index definitions. This paper has attempted to make a bridge from past to future research trends in the failure diagnosis of HVCBs.

To avoid failures in circuit breakers (CBs) and to extend the lifetime of these critical components, condition-based-maintenance has been increasingly requested by utilities to enable them to efficiently manage their assets. The origin of the most failures in CBs is the operating mechanism. Travel curve (TC) could effectively reveal the condition of the operating mechanism. However, the measurement of a TC profile is not simple in all CBs. This paper presents the impacts of common failure modes of CBs on TC profiles, and proposes a new model-aided approach to simulate the behavior of the operating mechanism with coupling the model-based and rule-based approaches. The simulation results along with experiments conducted on 72.5 kV SF6 CBs are organized into a fuzzy-probabilistic approach through maximum likelihood and interacting multiple models (IMM) to precisely predict the condition of CB and to detect intelligently the cause of the failure.The CB condition has been categorized into three modes based on its operating speed: normal, faulty-1 and faulty-2. The mode variations of the CB have been estimated via IMM in each operation. The proposed approach in prediction of the failures and cause(s) prior to their occurrence has been verified against experime

In this paper, an effort has been made to evaluate the online condition of arc contacts as a vital component of interruption chamber in high voltage puffer type SF6 circuit breakers. The relationship between eroded mass caused by short-circuit current interruption and different thermal stress indices such as transferred electrical charge, current squared, and arc energy is investigated, by performing many experiments with different current amplitudes and arcing times. It is demonstrated that none of the known indices can solely determine mass erosion caused by the current interruption. Therefore, the equations including two of defined parameters are proposed to evaluate mass erosion. The method using arc energy and transferred electrical charge owns the highest accuracy in evaluating mass loss. However, considering the complexity of arc voltage measurements, a second method using current and arcing time can be also utilized. In addition, the development of erosion during the lifetime of arc contacts is studied. It is shown that arc roots tend to form on new uneroded areas of the contacts during current interruption, resulting in different erosion rates between the first few and subsequent interruptions due to change of morphology of the contacts after the first few switching operations.

The objective of this article is to characterize partial discharge (PD) inception voltages and patterns at sinusoidal and square voltages in insulating ceramic substrates with generic manufacturing defects. PD tests were conducted on active metal brazed (AMB) aluminum nitride (AlN) substrates either with cavities in the polymer coating or sharp protrusions of the metal brazing. The substrates were tested in silicone liquid instead of silicone gel. Light sensitive imaging was used to localize the PD sites on the surface. PDs at square voltage with rise time of $1.6 ~\mu \text{s}$ were measured with a high-frequency current transformer and a photomultiplier. In both substrate types, the peak–peak value of the PD inception voltage (PDIV) was higher at sinusoidal voltage compared to peak-peak value of the square wave. This difference was more pronounced in uncoated substrates, where discharges incepted at sharp edges surrounded by silicone liquid. For both types of defects, comparable PDIVs were measured at bipolar and unipolar square waves. Results for unipolar pulses are discussed considering the role of charge memory effect.

Low-temperature plasma ion mobility spectrometry (LTP-IMS) is the method to identify some materials by measuring concentration of gas phase ions. IMS used in a wide range of laboratory-based biomedical research studies. A nanosecond pulse generator is necessary for LTP-IMS apparatus to enable direct analysis of various chemical compounds without having to evaporate the analyte or seek a solvent or any reagent. In this paper, a dual Marx pulsed generator for LTP-IMS Ionization power supply is proposed based on a new combination of some solid-state switches including insulated gate bipolar transistor (IGBT) and avalanche bipolar junction transistors (BJTs). The compact dual Marx generator is composed of a series of avalanche BJTs and an IGBT as the trigger switch, where its rise time is reduced from 100 to 5 ns by using an avalanche BJT in its command circuit. In this way, a controllable high-voltage pulse generator has designed, built, and tested. The proposed circuit can be used to generate the repetitive high-voltage pulses necessary for low temperature ionization in advanced IMS apparatus. The output voltage has an amplitude of up to 6 kV with pulse widths in the range of 40-1000 ns and pulse repetition rates up to 2 kHz, having rise time and fall time less than 10 ns independent of the load specifications.