Sequence Components Research Articles

Power Quality Management Strategy for High-Speed Railway Traction Power Supply System Based on MMC-RPC

This paper adopts the Modular Multilevel Converter Type Railway Power Conditioner (MMC-RPC) equipment to effectively manage the power quality of the high-speed railway traction power supply system including the reactive power and negative sequence component. Firstly, the single-phase model of the MMC was established to deduce the working characteristics of the MMC-RPC and its compensation principle for the traction power supply system with the v/v wiring transformer. Secondly, the adaptive VSG control strategy was adopted for the inverter of the MMC-RPC to provide dynamic inertial and damping support for the traction power supply system based on the virtual synchronous generator (VSG) control. Compared with the traditional double closed-loop (DCL) and VSG controls, it has better anti-disturbance and dynamic performance. The root locus analysis of control parameters based on a small signal model shows that VSG control can provide more stability margin. Furthermore, Differential Flatness Control (DFC) was used in the inner-loop controller to ensure the stable control of the inverter and the stability was verified by the Lyapunov stability analysis. For the rectifier of the MMC-RPC, a hierarchical three-level control strategy with system-level control, cluster-group voltage control, and inter-cluster voltage control for keeping the voltage balance was adopted. Finally, simulation results on the Matlab/Simulink platform verified the effectiveness and stability of the joint control applied in the MMC-RPC.

A positive, negative and zero sequences electric power, to improve upon the standard IEEE 1459-2010

PurposesThe purpose of this paper is to identify on the instantaneous electrical power basis of a nonsinusoidal periodic current three-phase asymmetric system, active and reactive positive, negative and zero sequence powers, taking into account higher harmonics. The main power theories, including those embodied in the IEEE 1459 standard, do not allow to evaluate some of power components.Design/methodology/approachA well-known fact is that the three-phase AC system total power with the symmetry of currents and voltages is constant. It corresponds to the electrical energy transfer process in a DC system. In this case, the electrical energy transmission can be taken as high quality. It has been established that the components of active and reactive powers are because of the product of current and voltage of unidirectional sequences. The orthogonal components of the oscillating power are because of the product of the voltage and current components of different sequences, with the exception of the zero sequence.FindingsFor an unbalanced nonsinusoidal mode of a three-phase system, the components of instantaneous power were defined, corresponding to the active and reactive positive and negative and zero sequences powers with the selection of the fundamental and higher harmonics. The active and reactive powers of sequences were divided into two categories – consumed and generated.Originality/valueIt is proposed to use the ratio of “interfere” power RMS value to the total power RMS value to assess the instantaneous power distortion.

Improving Patient Comfort in MRI with Predictive Acoustic Noise Cancelling.

With sound pressure levels reaching up to 130 dB, acoustic noise in Magnetic Resonance Imaging (MRI) is one of the main sources of patient discomfort in otherwise one of the safest medical imaging modalities. In this work, a noise prediction-based approach, termed predictive noise cancelling (PNC), is applied, for the first time, to suppress noise in MRI. In PN C the noise from the scanner gradient coils is predicted based on linear time-invariant models, which relate the individual gradient coil (X, Y and Z) input to the acoustic noise output. A model setup was constructed of a custom speaker box and MRI -compatible microphone to demonstrate live noise reduction. Additional tuning steps, including output channel equalization and clock mismatch correction, were performed to maximize noise reduction. A calibration sequence was designed to determine the model and tuning parameters. Analysis of actual scanner noise shows an upper limit of 21 dB noise reduction with the proposed linear model. For the components of a clinical example sequence, the setup demonstrated in-bore live noise reduction of up to 10 dB (7.01 ± 0.31 dB, 6.42 ± 2.04 dB and 9.28 ± 0.26 dB for X, Y and Z gradient coils respectively) in the presence of system imperfections. Clinical relevance - The results indicate promising noise attenuation without the need to modify scanner hardware or compromises in acquisition speed or quality. This has potential to substantially and cost effectively improve patient comfort in clinical MRI.

Angular symmetrical components-based anti-islanding method for solar photovoltaic-integrated microgrid

ABSTRACT This article examines how an innovative Angular Symmetrical Components of Voltages be applied to islanding detection and voltage unbalance factor estimation at a photovoltaic inverter-based distribution unit. Positive and Negative Sequence Components are converted into a polar form such as Line Aggregate RMS (LARMS) Voltage and Tangent Angle of Unbalance (TAU) which are determined from two line voltage signals. Three voltage relays are replaced with a single relay which compares the LARMS voltage and TAU with threshold limits to identify the condition of balance. ASCOV relay does not generate the trip signal in a non-islanding situation such as linear load switching and nonlinear load switching. The Non-Detection Zone (NDZ) of this ASCOV relay is very low compared to other relays. The proposed anti-islanding method is tested in a SPV powered microgrid using MATLAB/SIMULINK and the performance was studied under islanding and non-islanding events. Consequently, the simulation outcome indicates that the proposed technique effectively identifies the islanding condition with less computation time as 1 s and the performance of the proposed relay is compared with existing relays. The voltage unbalance factor determined by the proposed method is very close to the actual value in all types of unbalance conditions.

AC Fault Ride-Through Strategy of a Transformerless Soft Normally Open Point

This paper focuses on the soft normally open point (SNOP) which has no transformers and connects to the 10 kV distribution network through the arc suppression coil grounding mode. A mathematical model containing positive-, negative-, and zero-sequence components under AC fault is established by the circuit analysis and the sequence component decomposition. Then the voltage fluctuation mechanism at the DC side and the non-fault AC side caused by the zero-sequence voltage on the fault side is analyzed under the case without transformers. Taking the single-phase grounding fault as an example, the fluctuation formula of the DC voltage and AC voltage is deduced in detail. Based on the theoretical analysis, the zero-sequence control strategy and the sub-module improvement strategy of the modular multilevel converter (MMC) are proposed. A back-to-back SNOP simulation model is established in PSCAD/EMTDC. The simulation results verify the accuracy of the theoretical analysis, as well as the validity of zero-sequence control and MMC topology improvement strategies.

BERT contextual embeddings for taxonomic classification of bacterial DNA sequences

Biological taxonomic classification is an important task needed for the identification and discovery of organisms, as well as the inference of their evolutionary relationships. The order and structure of biological sequence components has an essential and primary role in what the sequence’s identity and function is. In order to be able to efficiently differentiate between different bacterial categories, interactions and positions of the biological components in sequences must be known — which is an essential challenge in biological sequence classification. In this light, a considerable amount of recent research has been made to explore efficient representations of biological sequences such as spectral k-mer representation, one-hot encoding, Hilbert space curves and classical word embeddings such as Word2Vec. This paper identifies the taxonomic classification of bacterial 16S rRNA genes at five resolutions mapping hierarchical taxonomic ranks. A Bidirectional Encoder Representations from Transformers (BERT) model is pretrained using biological sequences, which to the best of our knowledge is the first time BERT has been trained with such sequences. A complete prediction model is then proposed – BioSeqBERT-CNN – that initially extracts contextual embeddings representations of DNA sequences using the pretrained BERT model. Extracted representations are further used for taxonomic classification through a Convolutional Neural Network (CNN). For boosting the deep learning classification performance, a data augmentation step is applied. Classification with the original dataset on the most fine-grained rank produced an accuracy of 93.5%, which surpasses that of recent works by 1.5–24.3%. Using data augmentation, an accuracy of 99.9% is achieved, which exceeds values of recent works by a minimum and maximum of 7.9% and 30.7%, respectively on the most fine-grained taxonomic rank. This exhibits promising performance promoting the study of using contextual embeddings to represent biological sequences, with Deep Learning networks.

The emergence and early development of socio-sexual behavior in beluga calves (Delphinapterus leucas)

While the ontogeny of beluga (Delphinapterus leucas) socio-sexual behavior has been documented in animals between 37- and 108-months-old, the first 36 months of life are yet to be examined. This study investigated how socio-sexual behaviors emerge over the first three years of life in a group of belugas in managed care. The emergence of socio-sexual behaviors was relatively consistent among immature animals. More complex behaviors, like s-posture presentations, developed in a piecemeal fashion (i.e., simple components of the behavior sequence emerged before complex components). The presence of an adult male significantly predicted if immature belugas would initiate and participate in socio-sexual behavior. However, partner preferences changed with age. In the first year of life, belugas engaged in sexual behavior with their mother most frequently but preferred to play with older males if given a choice. By the third year of life, belugas engaged in socio-sexual behavior most frequently with other immature animals. These findings enhance our understanding of how belugas develop sexually and socially and have implications for social housing practices of immature belugas.

Analysis of Simultaneous Broken and Fallen to Earth Conductor Fault Condition in Power Systems

In power systems, analysis of critical faults, mainly, different types of simultaneous faults on transmission lines, is a sensitive issue. To identify the accurate fault place during a simultaneous fault condition, all major algorithms fail to provide the desired results. In this paper, an analysis of simultaneous faults called broken and fallen to earth conductor fault conditions is carried out. With the help of an equivalent sequence components network, generalized impedance equations are derived to determine the accurate fault place on the transmission line during the simultaneous broken and fallen to earth conductor’s fault condition. For authentication of the derived method, simulation has been done using MATLAB tool with two different medium transmission lines. Simulation outputs manifest the accuracy of the proposed generalized impedance equations by showing 98% accuracy for identifying precise fault places. The derived fault analysis method uses the sequential network formation technique, which can be easily understood by researchers.

Improved GM (1,1) Model by Optimizing Initial Condition to Predict Satellite Clock Bias

The variation law of satellite clock bias (SCB) can be regarded as a grey system because the spaceborne atomic clock is very sensitive and vulnerable to many factors. GM (1,1) model is the core and foundation of the grey system, which has been highly valued and successfully applied in SCB prediction since its production. However, there are still some problems to be further studied such as the lack of stability of its prediction effect in practical application. In view of this, an improved GM (1,1) model by optimizing the initial condition has been proposed in this paper so as to increase the prediction performance. The new initial condition is obtained by the weighted combination of the latest and oldest components of the original clock bias sequence. And the weight values of these two components are acquired from a method of minimizing the sum of squares of fitting errors. We adopt GPS rapid precision SCB data provided by the International GNSS Service (IGS) for 15 mins, 30 mins, 1 h, 3 h, 6 h, 12 h, and 24 h prediction experiments. The results show that the improved GM (1,1) model is effective and feasible, and its prediction accuracy and stability are significantly better than those of the traditional GM (1,1) model, ARIMA model, and QP model, even for the SCB signal with obvious fluctuation.

Hybrid voltage and current control strategy for virtual synchronous generator under unbalanced voltage conditions

AbstractThe traditional VSG strategy does not consider the negative sequence component, which will lead to current imbalance and power oscillation under unbalanced voltage. Several improved control strategies of VSG are usable for operating under unbalanced voltage nowadays. These control strategies usually require a complex PLL (phase‐locked loop) to detect sequence components, and a current reference generator to convert voltage references to current references. This paper proposes an improved control strategy for VSG. The main contributions are in threefold: (1) A hybrid voltage and current control strategy by simultaneously controlling the positive sequence output voltage and negative sequence output current is proposed, which can achieve different operation demands under unbalanced voltage conditions without changing the original characteristics of VSG. (2) A positive and negative sequence decoupling method is designed to acquire the synchronization phase information directly from the positive sequence voltage control branch, thereby avoiding the use of complex PLL (phase locked loop). (3) A general formulation for the negative sequence current references is presented to control the power oscillations or the current balance flexibly. The correctness and effectiveness of the control strategy are verified by simulation and experimental results.

A One-Pot Photochemical Method for the Generation of Functionalized Aminocyclopentanes.

Detailed herein is the development of a photochemical intermolecular formal [3+2] cycloaddition between cyclopropylimines and substituted alkenes to generate aminocyclopentane derivatives. The Schiff base of the cyclopropylimine was designed to enable a masked N-centered radical approach in which the requisite open-shell character was achieved upon excitation with visible light. The cycloaddition products were directly converted to N-functionalized aminocyclopentanes via solvolysis and N-acylation. The photochemical component of this reaction sequence was demonstrated to operate in continuous flow.

Quasi Type-1 PLL With Tunable Phase Detector for Unbalanced and Distorted Three-Phase Grid

Out of various moving average filter (MAF)-based phase-locked-loop (PLL), quasi type-1 PLL (QT1-PLL) is widely adopted due to its fast dynamic performance, implementation simplicity, and harmonics rejection abilities. However, the performance of QT1-PLL deteriorates in the presence of an off-nominal frequency unbalanced grid voltage component. Moreover, the sensitivity towards the fundamental frequency negative sequence (FFNS) component is high. Hence, this paper proposes a novel enhanced QT1-PLL solution that is insensitive to unbalance in the grid voltage signal during off-nominal frequency conditions. The proposed adaptive phase detector makes it possible to estimate both the fundamental frequency positive sequence (FFPS) and FFNS components with a high degree of immunity against harmonics. Notably, the pre-loop separation of the FFPS and the FFNS components helps suppress the second harmonic oscillations for improving the parameter estimation accuracy. The loop-filter design of QT1-PLL remains unaffected and requires a proportional gain to estimate the fundamental phase and frequency information. To address the DC offset issue, a modified delayed signal cancellation method is also proposed, which can theoretically eliminate the DC offset for any arbitrary delay length. A small-signal model of the proposed PLL is developed for the sake of stability analysis. Comparative numerical simulation and experimental results are provided with various variants of QT1-PLLs to demonstrate the performance improvement achieved with the proposed technique.

A Hybrid Carrier-Based DPWM With Controllable NP Voltage for Three-Phase Vienna Rectifiers

In this article, a hybrid carrier-based discontinuous pulsewidth modulation (HCB-DPWM) scheme is proposed for Vienna-type rectifiers. By injecting modified zero sequence components (ZSCs), the proposed HCB-DPWM-I scheme solves the issue of alternating input current distortion under unbalanced neutral point (NP) voltage conditions. The proposed HCB-DPWM-II scheme can also active NP voltage balancing control in case of extreme imbalance NP voltages. The flexible transition between the HCB-DPWM-I and the HCB-DPWM-II is also analyzed. Finally, a 10-kW prototype was built to conduct experiments. Experimental results demonstrate that the HCB-DPWM-I can be preferred to run Vienna-type rectifiers without regulating the NP voltage, and the HCB-DPWM-II can balance the NP voltage under severe NP voltage imbalance conditions. Compared with existing DPWM schemes, both the current THD performance and efficiencies can be significantly improved by the proposed HCB-DPWM scheme, especially under unbalanced NP voltage conditions.

Research on Diagnosis and Prediction Method of Stator Interturn Short-Circuit Fault of Traction Motor

The traction motor (TM) is an essential part of the high-speed train, the health condition of which determines the quality and safety of the vehicle. Hence, this study proposed a novel approach to diagnosing and predicting the TM stator interturn short-circuit fault (SISCF). Based on the Park vector (PV) of the stator current, this method could overcome the interference of current sensor errors, null shift, and motor frequency fluctuations in the actual conditions. More specifically, Park’s transformation was used to obtain the PV of the stator current. Then, the PV was fitted to obtain the elliptical trajectory and its parameters from which the negative sequence component of the stator current could be calculated. Finally, the SISCF diagnosis and prediction method were realized by the magnitude and trend of the negative current as well as the inclination of the trajectory ellipse. Furthermore, the performance of the proposed method was validated by a simulation model and a series of experiments. The simulation results were consistent with the experimental results, supporting the validity and correctness of the method proposed in this study.

Luenberger Observer-Based Microgrid Control Strategy for Mixed Load Conditions

In this paper, a Luenberger observer-based microgrid control strategy is proposed to enhance the power quality of microgrids, when the grid loads are mixed and strongly non-linear. To improve performance under this condition, a Luenberger observer is designed for three phase power grids. On the basis of the observer, the components of different frequencies and sequences of voltages and currents are obtained accurately. The virtual impedance of different frequencies and sequences is designed, which makes the equivalent line impedance meet the power-sharing condition, reducing the fundamental negative sequence voltages and harmonic voltages. The active power droop equation, meanwhile, is proposed, where the bus voltage is modified. The value range of virtual impedance is discussed in the complex frequency domain. The proposed control strategy does not require any communication lines, so the hardware structure is simplified. The simulations and experiments are provided to verify the effectiveness of the proposed method.

An Analytical Zero Sequence Method to Locate Fault in Distribution Systems Rich in DG

Locating high impedance faults (HIF) in a distribution system increases the system’s reliability and improves the service’s quality for customers. However, this type of fault produces currents of low magnitude, making it difficult to locate using conventional techniques. Therefore, this paper proposes a method for the location of single-phase high impedance faults in distribution systems with photovoltaic cells in low voltage. The method is based on the use of the sequence component of the current circulating in the medium voltage feeders of the distribution system, which are obtained from synchronized phasorial meters positioned along the feeder. The method considers nonsymmetrical lines, unbalanced loads, capacitors banks, photovoltaic DGs, and load variation. The performance of the proposed method was evaluated and tested on several distribution systems using ATP or PSCAD® and the results show that the method can locate HIFs with high precision. Also, a comparison was made with recently published methods to show the efficiency of the proposed method.

Improved Sensorless Control Method and Asymmetric Phase Resistances Determination for Permanent Magnet Synchronous Machines

This article proposes an improved sensorless control method for permanent magnet synchronous machines under phase resistance asymmetry. The proposed method acquires positive sequence current and voltage signals by applying a sequence component extractor and a double synchronous reference frame current control strategy. These signals can, then, be applied to improve the extended electromotive force based sensorless observer to eliminate the undesired second-order fluctuation in position and speed estimation due to asymmetric phase resistances. In addition, the resistance deviations, which may be due to asymmetric resistances and temperature variation, could introduce dc offset error in rotor position estimation. Therefore, a model reference adaptive system based resistance estimation is employed to compensate for inaccuracy of resistances. Moreover, from the information contained in the negative sequence voltages, the specific values of all asymmetric phase resistances can be estimated as well. Experimental and simulation results are provided to validate the proposed method.

A Negative Sequence Current Phasor Compensation Technique for the Accurate Detection of Stator Shorted Turn Faults in Induction Motors

Stator faults are the most critical faults in induction motors as they develop quickly hence requiring fast online diagnostic methods. A number of online condition monitoring techniques are proposed in the literature to respond to such faults, including the signature analysis of the stator current, vibration monitoring, flux leakage monitoring, negative sequence components of voltage and current and sequence components monitoring based on the identification of asymmetrical behavior in a machine. Negative sequence components of voltage and current and sequence components monitoring are commonly considered for the identification of asymmetrical behavior of induction motors. Negative sequence current analysis is a sensitive technique for the detection of shorted turns as it directly measures the asymmetry produced by the fault. However, the technique is sensitive to other asymmetrical faults and disturbances, which can also produce negative sequence currents. These disturbances include sensor errors, inherent asymmetry and voltage unbalance. This paper provides a comprehensive investigation of the disturbances using a motor model along with experimental measurements under varying load conditions. Then, a new phasor compensation technique is explained to eliminate such disturbances effectively. This technique enables the accurate detection of even relatively small shorted turn faults, even at an early stage. The technique is tested experimentally, and a set of practical results are given to validate the methods developed.

A direct analytical predetermination of PMSG based WPS steady-state values under different operating conditions

This paper presents a direct analytical method to predetermine the steady-state values of a permanent magnet synchronous generator (PMSG) based wind power system (WPS) at each stage of power flow. A generalized structured is developed with two independent equivalent circuits, that is, PMSG and grid side. To effectively determine the converters performance numerals despite grid disturbances, steady-state model is structured with positive sequence components of grid voltage. The advantage of the proposed model is that the methods evade the requirements of d-q modeling and a dedicated controller to evaluate the system performance. Using the proposed steady-state model, the entire WPS components ratings is predicted evading time domain simulation with complicated controller design. Also, the simple controller design is proposed to aid in optimal power flow supplement with FRT requirements under all possible system operating conditions. Ultimately, validation of predetermined values with the simulated PSCAD/EMTDC response including the proposed controller is investigated.

Rotor Transverse Slots’ Influence on Negative Sequence Loss and Heat Distribution Prediction of Large Generators Based on Improved Radial Basis Function Process Neural Network

Owing to the advantages of scientific computation and the data feature support provided by artificial intelligence technology, the theoretical exploration and application research of new computing methods for large generators, one of the most expensive energy equipment in a power system, has become a research hotspot toward solving the bearing limit and operation capacity under abnormal working conditions. Because of many factors affecting the distribution of negative sequence loss and temperature rise that have an extremely complex nonlinear relationship, the traditional calculation and prediction methods of negative sequence conditions cannot suitably reflect the time accumulation effect. Therefore, a prediction method of rotor steady-state negative sequence heating based on radial basis function process neural network is proposed in this paper, and a negative sequence working condition prediction model is established. Accordingly, this study focuses on the study of the relationship among negative sequence heating characteristics, negative sequence component proportion, and transverse slot; additionally, their influence degree, variation relationship, and main principles are further explored that provide a theoretical basis for the design and operation of large generators. As observed from the test results, the steady-state negative sequence condition prediction method based on the improved genetic algorithm radial basis function process neural network features high accuracy; it is a feasible prediction method, specifically for negative sequence conditions of large generators.