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The swivel clevis (SC) is a vulnerable part of the Overhead Catenary System (OCS). Regular inspection using computer vision technology is an effective way to detect SC defects and improve the OCS operation safety. However, achieving full automation of SC defects detection is still a difficult task due to defective sample scarcity and data distribution shift. To overcome these problems, this paper proposes a novel defects detection method that combines an adaptive SC segmentation network (Adaptive SSN) and local operators. During the inspection process, an unreliability index defined by the model uncertainty and prior knowledge is used to monitor the reliability of the Adaptive SSN. When data distribution shift causes the Adaptive SSN to be unreliable, human annotator will be asked to update the training set and retrain the Adaptive SSN to adapt to the new data distribution. Then the geometric features obtained from segmentation masks and the local features extracted by local operators are used to detect the SC defects. Effectiveness of the proposed method is demonstrated by the experimental results on the data from several high-speed railway lines.

Metal oxide varistors (MOVs) are usually applied to clamp the voltage across a dc circuit breaker (DCCB) after fault current elimination. This letter focuses on the transient process of a DCCB turn- off and has three contributions. First, it reveals that snubber circuit inductance, the internal and external stray inductances of an MOV could cause a significant overvoltage across a DCCB, which exceeds 47.5% of its nominal clamping voltage. The overvoltage mechanism is clearly analyzed based on the working principle of a DCCB, providing theoretical equations to estimate the overvoltage magnitude. Second, a nonlinear model of an MOV is proposed to simplify the calculation and provide an accurate estimation result. Third, a new arrangement of series submodules with discrete MOVs is proposed to suppress the overvoltage. A hybrid 500 kV/25 kA DCCB prototype with series insulated gate bipolar transistors (IGBTs) is implemented to validate the proposed analysis. The series-IGBT rating voltage is 1440 kV, and the MOV with a nominal clamping voltage of 800 kV is used to protect IGBTs. However, a 25 kA turn- off experiment clearly shows that the overvoltage increased to 1203 kV by an external stray inductance of 39.5 μ H and d i /d t of 1480 A/ μ s. The relative error between measurements and simulations is within 3%. Besides, simulations on the new arrangement show the overvoltage is decreased by 23.4% than before.

As a key component of the high-speed railway catenary, the insulator plays an important role in supporting the catenary and maintaining the insulation between the catenary and earth. Regular inspection using computer vision technology is an effective way to detect insulator defects and improve the catenary operation safety. However, achieving full automation of insulator defects detection is still a difficult task due to the defective sample scarcity and subtle defect features. To overcome the problem, this article proposes defect detection GANs (DefGANs) that consist of a denoising autoencoder, a discriminator, and a classifier to detect defects, which can generate defective samples from pitted latent representations, thereby improving the reliability of defect detection classifier. The proposed DefGAN can pit the latent representations of normal samples to generate defective samples. Our proposal mainly consists of two stages. In the first stage, we use cascaded deep segmentation networks (CDSNets) to extract the insulator from the catenary images. Then, the insulator area is sampled into small patches. In the second stage, the patches are fed into the proposed DefGAN to detect defects. Moreover, the defect score is determined by the anomaly probability of the classifier and reconstruction error of the denoising autoencoder. The effectiveness of our work is measured across the catenary data sets.

Extraction of the current commutation loop (CCL) inductance is necessary for the overvoltage analysis of power devices. In general, each transient process of a converter corresponds to a specific CCL. However, there is no such single CCL in the full-bridge module in hybrid dc circuit breakers during the turn- off transient. First, this article proposes a coupled inductance model of full-bridge modules. The model has less number of inductance compared to the traditional partial inductance model. Second, this article proposes the extraction method of inductances that can be easily obtained by both simulation and measurement. Moreover, the measured overvoltage waveforms of insulated gate bipolar translators (IGBTs) in the full-bridge module agree with the simulation results. Third, we propose an equivalent circuit of the series full-bridge modules in a 500 kV hybrid circuit breaker based on the proposed coupled inductance model. The mutual inductances among different modules are considered due to the compact structure of the series modules. The measured results show that the overvoltage of the IGBT in the series module could be well-predicted by the proposed equivalent circuit.

Load redistribution (LR) attacks represent a major cyber threat to the power grid that can result in branch overloads and even cascading failures in the transmission network by injecting false data to load bus power injection and line power flow measurements. While the mechanism and defense strategies have been well studied for single-occurrence (i.e., discrete) LR attacks, this paper focuses on a yet unexplored category of LR attacks, namely, the continuous LR (CLR) attack, which continuously injects time-varying false data to one or more bus and branch measurements within the system for a certain period of time. To cope with the potentially ever-changing targeted branches (i.e., the branches under attack) and system vulnerability features caused by CLR attacks, this paper takes a different route from the traditional LR defense and mitigation approaches. We propose a novel correlation chain model to capture the vulnerability correlations among branches under the CLR attack. Then, a dynamic sequential-mining algorithm (DSMA) with top-k structure is proposed based on the specific nature of the CLR attack, to mine the historical SCADA measurement database, extract vulnerable branch sequences, and identify the most suitable branches to defend preventively. Simulation studies are conducted on IEEE RTS-96 system to evaluate the effectiveness of the proposed approach in terms of increasing attack costs for the attackers and reducing the potential impacts of CLR attacks.

This paper aims to identify the vulnerability of electrical cyber-physical systems (CPSs) through fault propagation under cyber attacks. First, we propose a fault propagation model mainly considering the impact of interruptions on some nodes of the cyber network on the electrical physical systems. Secondly, two graphs, i.e. propagation graph and attack graph are proposed to reveal the physical fault propagation mechanisms and analyze the attack intensity of combinations of different communication nodes, respectively. Thirdly, a set of traditional vulnerable indices based on the propagation and attack graphs are employed to identify both the critical physical branches and communication nodes in the CPS. Finally, comparative analyses with and without considering the CPS on both IEEE 118- and 300- bus systems show that the fault propagation among are more sophisticated and the wrong decisions that the control center makes causes the higher vulnerability of the electrical network due to the interruption of the transmission information in the cyber system under cyber attacks.

The contact wire support (CWS) is an important catenary component that maintains the contact wire height and stagger. The direct impact of the pantographs makes the CWS a vulnerable part of the catenary. Recently, automatic catenary inspection using computer vision and pattern recognition has been introduced to improve railway operation safety. However, the automated detection of CWS defects remains to be further studied. This paper proposes a novel CWS defect detection system that consists of three stages. First, the Faster R-CNN network is adopted to localize the key catenary components, and the image areas that contain CWS components are obtained. Then, the CWS components are segmented using a Bayesian fully convolutional catenary components segmentation network (CCSN) that fuses different level features of the backbone network. The CCSN is not only able to perform accurate CWS components segmentation, but also capable of evaluating the model uncertainty by Monte Carlo dropout. Finally, the defect status is determined using the proposed criteria, which are defined according to the geometries of the components. Experiments on the Hefei-Fuzhou high-speed railway line indicate that this approach can be applied to the CWS defect detection.

The current interruption test based on an LC resonance circuit for hybrid DC circuit breakers (HVDC CBs) is widely employed to characterize the current interruption capability of CBs. In order to ensure a high-fidelity replica of the fault current in a high voltage application, this paper firstly proposes an equivalent model of the test circuit, where not only parasitic resistances but also the threshold voltages and on-state resistances of various semiconductor devices are considered. Moreover, the analytical formula of the test current is derived by including the working principle of the HVDC CB. Secondly, the parameter extraction method, which combines finite element analysis and measurements by impedance analyzer, is given in this paper. The extracted result implies that, in current interruption transient, equivalent resistances of the 500 kV CB is as large as 535 mΩ, having a significant influence on current waveforms. Thirdly, the 34 kV/25 kA current interruption test for the 500 kV CB is conducted. The measured results are proved to be consistent with the analytical results obtained from the proposed model, and the relative error is less than 2%.

In the Urban Energy Internet (UEI), any partial and weak faults may be transmitted to other subsystems through cyber and energy spaces, which may increase the risk of system catastrophe, ranging from small scale to large scale, from single system to multi-system, and from minor accidents to system crashed. Therefore, the analysis of the catastrophe in UEI is urgently needed. In this paper, a research framework of UEI catastrophe analysis and its dynamic early warning mechanism are constructed, based on the integration of human, cyber and energy in UEI, which aims at quantifying the potential catastrophic risks of the human-cyber-energy coupling system. First, the interaction mechanism among human, cyber and energy are analyzed. Secondly, the hybrid model of UEI calculation of probabilistic energy flow based on the dynamic probability method is developed. Furthermore, based on the analysis of catastrophe propagation and evolution mechanism of the human-cyber-energy space, the catastrophe analysis method for coupling system is analyzed, and indicators and assessment methods for characterizing the local and overall disaster-resistant status of UEI. On this foundation, the dynamic early warning mechanism of catastrophe based on artificial immune system is constructed. Finally, the comprehensive simulation architecture of catastrophe analysis and early warning mechanism for UEI are developed to verify the validity of the theoretical methods. The expected achievements of this framework proposed in this paper can provide theoretical support for the planning and operation of UEI.

Periodic switching processes of transistors may cause high-level electromagnetic interference (EMI), which will conduct along magnetic components in the system and threaten electromagnetically sensitive facilities. In order to evaluate impacts of magnetic components on propagation of the EMI, it is necessary to investigate capacitive effects on the whole component, i.e., the global capacitive effects. In this case, detailed partial capacitance (PC) networks based on turn-to-turn and turn-to-ground capacitances may be impractical due to their size and the resultant computational burden. A terminal capacitance (TC) method characterized by explicit physical mechanism and high computation efficiency is proposed to analyze global capacitive effects of magnetic components. By defining coefficient matrix accounting for potential distribution of each winding, PCs corresponding to turns are decoupled to TCs corresponding to external terminals, and quantificational links between TCs and PCs are established with rigorous equations. Furthermore, TCs are directly deduced based on energy computation without having to compute PCs beforehand, making the TC method convenient and efficient. An air-core inductor and a two-winding transformer are used to verify the proposed TC method, and a smoothing reactor employed in the practical UHVdc engineering is used as an application of the method.

As the key equipment of ultra-high-voltage direct-current (UHVDC) transmission systems, the converter valve would bear different forms of overvoltage. Consequently, a wideband model for the $\pm $ 1100 kV UHVDC converter valve is essential for the converter system to make overvoltage analysis, insulation design, and electromagnetic disturbance prediction. This paper proposed a wideband modeling method for the $\pm $ 1100 kV converter valve. First, the physics-based wideband model for the key component in the converter valve module is built, of which the parameters could be obtained through genetic algorithm. Second, the parasitic capacitances are obtained through a simplified boundary-element method according to the given structure of the $\pm $ 1100 kV converter valve. By combining wideband models for key components in the converter valve module and the parasitic capacitances of the valve tower, the integrated wideband model for the converter valve could be obtained. The systematic modelling method proposed in this paper could also be of reference value to the modelling of other large-scale complex high-voltage power-electronic equipment. Finally, the experiments for converter valve module and converter tower are carried out, and the corresponding results justified the effectiveness and correctness of the proposed wideband model for the converter valve tower.

Parasitic capacitances of the high-frequency (HF) transformer used in dc–dc converter impact harmonic analysis of the transformer and interactions with the converter. Resonant frequencies of open- and short-circuit impedances characteristics (ICs) have been widely used to extract parasitic capacitances of HF transformers, but it was reported that some resonant frequencies were unobtainable as they were too high where the ICs fluctuated heavily, and parasitic capacitances remained unevaluated. In this paper, resonance features of ICs and voltage transfer characteristics (TCs) are investigated, and a new frequency of voltage TC is used for extracting parasitic capacitances. By analyzing inner links of known impedance resonant frequencies, why and which resonant frequencies are likely to be unobtainable is revealed. Furthermore, a new frequency corresponding to zero of TC, accounting for parallel resonance between leakage inductance and mutual capacitance of the two windings, is used to extract parasitic capacitances. With this new frequency mutual capacitance of the windings is evaluated, and missing equation due to unobtainable impedance resonant frequency is added. Besides, merits and limitations of extracting parasitic capacitances based on ICs and TCs are analyzed. These techniques are verified with several HF transformer prototypes in the laboratory.

The dc-dc modular multilevel converter (dc-dc MMC) with a medium-frequency ac-link transformer is a promising candidate for the modern electric ship medium voltage dc power system to provide galvanic isolation, flexible voltage regulation, and fault ride through ability. However, the steady states and dynamics of such an isolated dc-dc MMC are rather complicated because it contains many state variables. Moreover, the on-ship requirements further complicate the system design. This paper thus proposes the modeling and control of such a dc-dc MMC. Based on the fact that such a dc-dc MMC is controlled by the phase-shifted operation, the fundamental period averaging (FPA) method is applied to obtain the steady-state and small-signal models, and based on the on-ship requirements, the modulation index control as well as the simple but efficient competitive dual closed loops (a voltage loop for normal condition and a current loop for overload condition) are designed. It is proved that the FPA method can preserve the necessary model information about the dc-dc MMC, and the proposed controllers can be well designed based on the steady-state and small-signal FPA models by compromising the on-ship requirements. The analysis and design results are verified by the simulations and experiments.

We, the Editor and Publisher of the Journal of Receptors and Signal Transduction, have retracted the following article: Ultrasound microbubble-mediated miR-150-5p inhibits gastric cancer cell growth by targeting the expression of NR2F2; Wei Wei, Xiaoguang Wei, Minyu ZhangCheng Peng; https://doi/10.1080/10799893.2021.1884260Since publication, concerns have been raised about the integrity of the following figures in the article. 2(A) miR-NC and 2(D) miR-NC-MBs;2(A) Control and 5(C) NR2F2-MBs + miR-NC-MBsWhen approached for an explanation, the authors were unable to provide original data in a suitable format that would confirm the authenticity of the data. The authors have been notified of the retraction but have not responded.We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions.The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as 'Retracted'.

The high-power high-voltage high-frequency transformer (H3T) is a key equipment to develop the isolated high-power dc–dc converter. In this paper, a wideband mechanism model is proposed to analyze the external behaviors of the H3T. This model is characterized by elaborate considerations on magnetic and capacitive effects of the H3T, including electrostatic couplings between windings, magnetic core, and the enclosure, with parameters which have explicit physical meanings. In terms of large number of turns and racetrack windings of the H3T, a finite-element method based on weighted algorithm is used to extract model inductance and capacitance parameters. To verify the proposed model and corresponding parameter extraction method, impedance characteristics of an H3T prototype under open circuit, short circuit, and load conditions are measured and simulated over a wide frequency band. The results show that the proposed model is valid up to 300 kHz. Besides, when one or two windings of the H3T are grounded, the proposed model may be reduced to traditional six or three capacitance models due to changes of winding-to-ground capacitances, which may account for shift of resonant frequencies. The proposed model and corresponding analyses are helpful to electromagnetic design and external behavior investigations of the H3T.

DC–DC modular multilevel converter (DC–DC MMC) with the medium-frequency or high-frequency interlinked transformer is an attractive candidate for high-voltage-direct-current system and DC grid. This study proposes the phase-shifted modulation for DC–DC MMC, aiming to reduce the switching losses, minimise the computational burdens and obtain the satisfactory performance. According to the features of DC–DC MMC, the least but necessary control parameters are extracted, and their control cycles are also properly designed to adapt to the digital implementation. Then, the modulation algorithm is designed and the parameter mapping is realised by the simplest algorithm. Finally, the voltage fluctuations of the submodules (SMs) under such a modulation are predicted off-line, and the adapted sort-and-selection strategy is designed for voltage balance of the SMs. With the proposed modulation, the switching frequencies of all SMs are strictly equivalent to the fundamental frequency; the sampling, parameter mapping and sort-and-selection frequencies are also the fundamental frequency. These features alleviate not only the switching loss in the power stage, but also the computational burden in the modulation and control systems. The analysis and design of the proposed modulation will be given in this study, and verified by the experiments.

This paper focuses on power system fault diagnosis based on Weighted Corrective Fuzzy Reasoning Spiking Neural P Systems with real numbers (rWCFRSNPSs) to propose a graphic fault diagnosis method, called FDWCFRSNPS. In the FD-WCFRSNPS, an rWCFRSNPS is proposed to model the logical relationships between faults and potential warning messages triggered by the corresponding protective devices. In addition, a matrixbased reasoning algorithm for the rWCFRSNPS is devised to reason about the fault alarm messages using parallel representations. Besides, a layered modeling method based on rWCFRSNPSs is developed to adapt to topological changes in power systems and a Temporal Order Information Processing Method based on Cause– Effect Networks is designed to correct fault alarm messages before the fault reasoning. Finally, in a case study considering a local subsystem of a 220kV power system, the diagnosis results of five test cases prove that the proposed FD-WCFRSNPS is viable and effective. Ministerio de Economía, Industria y Competitividad TIN2017-89842-P (MABICAP)

With the capacity of new energy resources such as wind power and photovoltaic in Zhangbei region increasing rapidly, the reliable transmission and consumption capabilities of large-scale and high-proportion new energy resources are urgently improved. Considering the advantages of the VSC-HVDC transmission technology, Zhangbei project is designed as symmetrical bipolar system which adopts half-bridge modular multi-level converter (MMC) topology and overhead lines for power transmission. In this paper, a system scheme is presented, and some results are provided. Meanwhile, a novel modular cascaded hybrid DC breaker concept is proposed, and 500kV VSC valve and DC breaker prototype are developed to meet the requirement of the Zhangbei four-terminal dc grid.

A power component detection (PCD) method and an improved current order limiter control (improved COL) are proposed to mitigate the commutation failure in a line-commutated converter-based high-voltage direct current (LCC-HVDC). Integrating the instantaneous voltage and instantaneous current characteristics under single-phase and three-phase-to-ground faults, a fault detection method based on the power component is proposed, and the corresponding setting principle is presented. Then, an improved dc current order limiter is introduced. To evaluate the effectiveness of the proposed methods, a dual-infeed HVDC system is developed in PSCAD/EMTDC, and the presented methods are also implemented. The transient performances of dual-infeed HVDC, under single-phase and three-phase-to-ground faults at the inverter ac busbar of one LCC-HVDC link, are investigated. Simulation results show that the PCD method, with the voltage and current components as an additional judgment criterion, is more sensitive to detect the single-phase and three phase faults, and even more reliable than the detect method taking only voltage or current components for faults recognition. It can also be concluded that the improved COL that is integrated with the advancing firing angle control has the ability to make the LCC-HVDC less susceptible to commutation failure. Finally, the improvement of commutation process by improved COL is further demonstrated.

As the key devices of an HVDC transmission system, converter valves should bear different forms of overvoltage. Additionally, the wideband frequency electromagnetic noises caused by the switching of thyristor may impact the normal operation of the communication and control systems in an HVDC converter substation. Consequently, it is of great significance to build the model that is suitable for wide frequency range for the key components of converter valve system. Based on the elementary wideband model, the integrated wideband model is proposed and the estimation method for corresponding parameters is also addressed for different kinds of components in this paper. The theoretical analysis and simulation results show that the integrated wideband model has high accuracy and simplicity; it also can provide the results with rigorous passivity and specific physical meaning. As for the application, the proposed method is used to model the key components of an HVDC converter valve and proved to be correct and effective.

Energy Internet (EI) is an inevitable development trend of energy systems under the background of technology development, environmental pressure and energy transition. Multi-energy flow coupling is one of the key characteristics of the EI, which enhances the interoperability of different types of energy flows while consequently increases the probability of cascading failures. Therefore it is of great significance to study the multi-energy flow fault diagnosis of the EI to ensure its safe and stable operation as well as the continuous energy supply. This paper introduces the concept of multi-energy flow cascading fault of the EI for the first time. The energy internet framework for multi-energy flow cascading fault diagnosis is firstly proposed, and then characteristics of various energy networks in the EI are analyzed from the perspective of fault diagnosis. Finally, future research prospects are discussed. National Natural Science Foundation of China 61703345 National Natural Science Foundation of China 61472328 National Natural Science Foundation of China 51607146

Containing false data injection attacks (FDIAs) plays a crucial role in securing the reliable operations of power systems. This paper first proposed a stealthiness corruption-oriented method to defend against such attacks. By checking the consistency between the real-time running states obtained from power system state estimation and the most likely running states derived from historical running state database, the operator would be able to corrupt the stealthiness of FDIAs and then modify the estimation results accurately. Simulation results conducted on the IEEE-14 bus test system demonstrate the feasibility of the proposed method, and analysis based on bus power flow imbalance index verifies the effectiveness and accuracy of this stealthiness corruption-oriented method in containing FDIAs.

This paper presents an approach for classifying different types of faults occurring in power transmission lines by integrating Fuzzy Reasoning Spiking Neural P Systems (FRSNPS) with wavelet transform and singular value decomposition. This is the first attempt to extend the application of FRSNPS from fault section identification to fault classification. The effectiveness of the introduced method is verified by various cases of fault types in power transmission lines.

Recently, dc-dc modular multilevel converter (MMC) with medium or high frequency transformer has attracted more and more attentions for its many advantages such as flexible dc power flow control, good voltage matching and inherent dc current limitation. So far, the arm-voltage of dc-dc MMC has been modulated in many forms such as sinusoidal, trapezoid or even rectangular to gain different benefits. However, the power-flow and capacitor-voltage fluctuation analysis only considering the dc and fundamental component for all kinds of modulations, leads to the deviation between analysis and practice. To bridge this gap, this paper proposes a general Fourier-Series-Expansion-based analysis approach for dc-dc MMC. Such a general approach suits for any modulations, and the power-flow, arm current and dc-capacitor voltage fluctuation in the Sub-modules (SMs) under different modulations can be calculated with accepted tolerance. The concept, analysis and example comparison are given in this paper, and the theoretical analysis are verified by both the simulation and experimental results.

A DC/DC Modular-Multilevel Converter (MMC) is proposed in this paper, in which two modular multilevel converters are linked by a LCL tank. With the proposed converter, the high power medium frequency transformer can be eliminated to simplify the structure, quasi zero-current-switching operation of both MMCs can be achieved to alleviate the switching loss, the voltage stress of internal LCL tank can be controlled and the destructive voltage derivation applying on LCL tank can be avoided. The operations, modulations and parameter design are given in this paper. A simulation model in Matlab/Simulink and a low power prototype are built to validate the proposed topology.

With the development of Chinese economy, the electric power has to be transmitted over long distance and in large scale. UHVDC provides a suitable solution to send power from large scale hydro and thermal power base to remote load centers. It improves distribution of resources, relieves environmental impact and costs less land resource, bringing significant economic and social benefits. As the key equipment in UHVDC project, converter valve plays an essential role in converting electricity from AC to DC and vice versa. CEPRI has developed its own UHVDC converter valve (typed A5000) with independent intellectual property rights and has completed the construction of related type tests capability. This paper describes in detail the testing capability of CEPRI, the R&D of A5000 valve and its type test results. A5000 valve will be used in the Jinping-Sunan ±800kV UHVDC transmission project which has highest transfer capacity up to 7600MW.

Analysis and simulation on voltage distribution of HVDC thyristor valves under a variety of voltage stress are performed respectively. The summarized influencing factors on voltage distribution indicate that they are different with frequency. Due to the importance and difficulty in approaching even distribution in high frequency, the voltage distribution with different module structure and different power circuit parameters is also investigated in detail. Equivalent circuits are built and circuit analysis method is applied on the basis of “field-circuit coupled method”. It shows that module structure such as framework and module size, module array etc. influence both stray capacitances and equivalent circuit topology, consequently the voltage distribution performance. Besides some power circuit parameters also take great effect. All these key factors are listed and their influences on transient voltage distribution are generally discussed

Digital right management can be used on digital copyright protection, access to control, trust management and other areas. Right expression language is an important component of DRM system. The purpose of this paper is to research the application of REL in education.It gives the introduction of development of right expression language firstly, and describes in detail the development process of MPEG-21 REL used in popular,and discusses the frame structure of MPEG-21 REL.According to the special needs of learning object, this paper introduces MPEG-21 REL connecting with the concrete application scenarios in education, summarizes the advantages and disadvantages of MPEG-21 REL and analyzes what MPEG-21 REL needs to improve in future.Lastly, the conclusion is made and the develop trend of REL is forecasted.

Digital right management can be used on digital copyright protection, access to control, trust management and other areas. Right expression language is an important component of DRM system. The purpose of this paper is to research the application of ODRL. It gives the introduction of development of right expression language firstly, and describes in detail the development process of ODRL used in popular, and discusses the frame structure of ODRL. This paper summarizes what ODRL need to improve in future and introduce it connecting with the concrete application scenarios. Lastly, the conclusion is made and the develop trend of REL is forecasted.