Line Current Research Articles

OUT–OF–STEP protection in rotating generation networks for hydrogen fuel production. Modeling conditions to test its algorithms

The testing of relay protection devices is an extremely important task on which the stable and safe operation of the power systems depends. One of the most complex and responsible kinds of protection in networks with rotating generation, which includes hydrogen fuel generation, is protection against loss-of-synchronism. Integration of heterogeneous generating electrical devices based on renewable energy sources and based on a hydrogen fuel cell is associated with the need for reliable relay protection. It disconnects tie-lines between the systems in out-of-step conditions. And it is a challenging task to simulate input signals corresponding to the exact settings of the out-of-step protection to make sure it operates correctly. This is because one has to simulate exact parameters of impedance locus (its radius, coordinates of the center in the impedance plane, spin direction, speed, etc.) while available tools embedded in testing devices often don’t support such parameters directly. To deal with the problem, the authors present the approach to simulate instantaneous values of line currents and phase-to-ground voltages during the out-of-step operation. These electrical signals form the locus of the impedance vector with the desired parameters to test the operation of the out-of-step protection devices. The software based on the proposed algorithm also provides a graphical representation of the simulation results. All the proposed solutions proved to reduce the time required for commissioning of out-of-step protection and thereby increase tests quality and speed.

Effects of Injected Current Streams on MHD Equilibrium Reconstruction of Local Helicity Injection Plasmas in a Spherical Tokamak

Open field line currents are intrinsic to DC helicity injection plasma startup and pose a challenge for inferring the plasma equilibrium with standard reconstruction analysis. Local helicity injection (LHI) is a type of DC helicity injection which uses small, modular current sources to drive force-free current along helical field lines to produce tokamak plasmas. MHD modeling and magnetic measurements during LHI indicate the injected current streams remain coherent as helical structures on the outboard edge of a core toroidal plasma that is tokamak-like in a toroidally averaged sense. To extract core plasma equilibrium properties, external magnetic diagnostics corrected for contributions from the injected current streams are fitted by a standard Grad-Shafranov equilibrium code. An iterative approach for estimating and subtracting the stream contributions from the diagnostic signals is described and applied to a model equilibrium database to reduce systematic errors introduced by the streams. Convergence is usually attained with 2 to 4 iterations, with derived equilibrium parameters matching the prescribed axisymmetric core values to within estimated experimental uncertainties. Accurate recovery of core parameters occurs when the ratio of the net toroidal windup current from the streams to the core plasma current is less than 0.2, which is typically satisfied in most experiments.

Direct torque control of a dual star induction generator based on a modified space vector PWM under fault conditions

Recent studies have shown that electrical systems in wind power conversion are subject to a 67 % failure rate, and conventional three-phase generators are considered to be the most sensitive to these faults. Induction generator current harmonics are a major source of torque ripples causing acoustic noise and vibrations. These ripples can progressively increase under faulty operating conditions. In six-phase machines, there is appearance of high harmonic currents in the air gap as space harmonics. Power electronic converters are also subject to faults, the most common being Short-Circuit (SC) and Open-Circuit (OC) faults. SC faults cause large peaks in the line currents, which trigger the protection devices, resulting in a complete shutdown of the production system. OC faults, on the other hand, cause imbalances in the phases, but the system remains in operation.Direct Torque Control (DTC) based on Space Vector Modulation (SVM) at constant switching frequency is an effective solution to tackle induction generator current harmonics. This paper proposes a DTC combined with a Proportional Integral Fuzzy Logic Controller (PIFLC) optimized by Particle Swarm Optimization (PSO) in order to overcome the problems of torque ripples. Furthermore, using Vector Space Decomposition (VSD) and the Modified Space Vector Pulse Width Modulation (MSVPWM) strategy, a significant reduction of harmonics in the air-gap can be achieved.Simulations were carried out under MATLAB/Simulink, and the results obtained demonstrate the superiority of the proposed DTC-PIFLC-PSO controller in terms of robustness against wind speed variations and under faulty switch conditions in the power converter of the Dual Star Induction Generator (DSIG) generator. In addition, a comparative study with the classical PI controller is presented to show the effectiveness of the DTC-PIFLC-PSO controller against faults with a significant reduction in the Total Harmonic Distortion (THD) during both faulty and non-faulty conditions.

Analysis of Relay Coordination in Electrical Distribution Networks with Optimally Positioned Distributed Generation Units

As power demand increases and transmission and distribution capacity is limited, Distributed Generation (DG) units are gradually being incorporated into electrical power distribution networks. However, this integration may result in a significant impact on the coordination of protective relays, potentially generating issues such as blindness of protection and false tripping of overcurrent relays. To overcome these issues, an adaptive protection method is presented that adjusts relay sensitivity in response to changes in network design. The suggested technique dynamically modifies relay settings based on the line current, which fluctuates depending on the system design. Digital relays are needed for this method in order to save operational data in real time. Based on periodic observations, the Plug Multiplier Setting (PMS) and Time Multiplier Setting (TMS) parameters are optimized using a Fuzzy Inference System (FIS). Fuzzy rules are used by the adaptive algorithm for every relay. These rules are produced using the fuzzy editor using the inputs provided. An initial investigation was carried out to evaluate the effect of DG on the coordination of relay protection., as well as the optimal placement of DG to reduce losses and improve voltage profiles, using two base distribution networks. The algorithm was further tested on various configurations of IEEE distribution networks, and its effectiveness in achieving optimal relay coordination with adaptive settings was validated through the relay coordination module in ETAP.

A novel phaselet-based approach for fault detection and location in HVDC lines

Recently, the popularity of direct current (DC) transmission has surged due to a 30 % reduction in power electronics equipment costs over the last decade. High-Voltage Direct Current (HVDC) transmission lines experience fluctuations in both nominal and faulty states, posing challenges for fault location methods, particularly those based on traveling waves, resulting in imprecise outcomes with an average error margin of ±2 %. This paper investigates a novel fault detection and location approach utilizing wavelet and phaselet transforms. The proposed method focuses on traveling waves in HVDC transmission lines, where the phaselet transform effectively eliminates undesired fluctuations in line currents, improving fault detection accuracy by up to 15 %. By leveraging the traveling time in the faulty line, the exact fault location is calculated with an accuracy of 98.5 %, independent of transmission line parameters, making it applicable to any DC line. Additionally, the method's precision is minimally affected by fault resistance, with <0.5 % deviation even in nonlinear scenarios. Sensitivity analysis conducted on various parameters, including mother wavelet patterns, suggests the optimal solution for each fault type, enhancing detection speed by 20 %. The proposed method is validated using the Cigre HVDC benchmark, confirming its accuracy, speed, and robustness in fault detection and location in HVDC lines. The main contribution of this paper is an accurate, fast, and robust phaselet-based algorithm that reduces fault location errors to <1 % and is applicable to all types of bipolar and monopolar HVDC systems, delivering reliable results for both ground and line faults.

Fine inductive VAR control with high power quality using thyristor controlled reactors and discontinuous phase control switching in power systems

The thyristor-controlled reactors (TCR) are widely employed to regulate the power system voltage and improve stability. However, TCR injects higher-order harmonics in the line current. For instance, in conventional TCR configurations, the total harmonic distortion (THD) is 78.5% at 10% of the fundamental current, and even it is 10% at 80% of the fundamental current. A previously reported control approach uses two reactors with a half-wave control design, which was only effective for the upper half of the control range. This paper proposes four new circuit configurations for reactive power regulation using discontinuous phase control (DPC). The new reactor design is also proposed for high-density magnetic flux perform well with double windings and three-inductor setups under the proposed approach. The proposed configuration of a multistage reactor with varying magnitudes provides extremely low total harmonic distortion (THD) across a near-complete control range. Even, the proposed design has achieved virtually zero THD for the reactor current. For THD to be less than 10%, a specific reactor pair is switched such that the control is only in the top half of the control range. The following configuration is based on reactors with the same magnitude. Like integral cycle control, the on-off control is employed for coarse action, whereas phase control is applied for fine control. All the proposed configurations are practically realized, and the performance is experimentally verified satisfactorily.

Phase sequence selection method of double-circuit transmission lines on the same tower based on a comprehensive index

Abstract The non-transposition erection of transmission lines will lead to the imbalance of electrical parameters, which will affect the protection and automatic reclosing. The best phase sequence arrangement is determined by comprehensively considering the comprehensive indexes (current imbalance, secondary current, and recovery voltage) of double transmission un-transposed lines with shared towers. PSCAD/EMTDC electromagnetic transient simulation software is applied to build a typical 750kV transmission line model for simulation analysis, and the comprehensive indexes under different phase sequence arrangements are studied. The analysis reveals that the arrangement of phase sequence exerts a significant consequence of the comprehensive index. The findings indicate that the margin and different secondary current and recovery voltage indexes, double transmission un-transposed lines with shared towers can be erected in the same direction or in different phase sequences to reduce the current imbalance.

Novel glassbox based explainable boosting machine for fault detection in electrical power transmission system.

The reliable operation of electrical power transmission systems is crucial for ensuring consumer's stable and uninterrupted electricity supply. Faults in electrical power transmission systems can lead to significant disruptions, economic losses, and potential safety hazards. A protective approach is essential for transmission lines to guard against faults caused by natural disturbances, short circuits, and open circuit issues. This study employs an advanced artificial neural network methodology for fault detection and classification, specifically distinguishing between single-phase fault and fault between all three phases and three-phase symmetrical fault. For fault data creation and analysis, we utilized a collection of line currents and voltages for different fault conditions, modelled in the MATLAB environment. Different fault scenarios with varied parameters are simulated to assess the applied method's detection ability. We analyzed the signal data time series analysis based on phase line current and phase line voltage. We employed SMOTE-based data oversampling to balance the dataset. Subsequently, we developed four advanced machine-learning models and one deep-learning model using signal data from line currents and voltage faults. We have proposed an optimized novel glassbox Explainable Boosting (EB) approach for fault detection. The proposed EB method incorporates the strengths of boosting and interpretable tree models. Simulation results affirm the high-efficiency scores of 99% in detecting and categorizing faults on transmission lines compared to traditional fault detection state-of-the-art methods. We conducted hyperparameter optimization and k-fold validations to enhance fault detection performance and validate our approach. We evaluated the computational complexity of fault detection models and augmented it with eXplainable Artificial Intelligence (XAI) analysis to illuminate the decision-making process of the proposed model for fault detection. Our proposed research presents a scalable and adaptable method for advancing smart grid technology, paving the way for more secure and efficient electrical power transmission systems.

A Novel Shunt Zigzag Double-Tap Low-Harmonic Multi-Pulse Rectifier Based on a Three-Stage Power Electronic Phase-Shifting Transformer.

To solve the problem of the large size of traditional industrial frequency phase-shift transformers and the harmonic distortion of multi-pulse wave rectifier systems, this paper proposes a three-stage shunt zigzag power electronic phase-shift transformer based on a double-tap multi-pulse wave rectifier, which combines the power factor correction (PFC) converter with the voltage-type SPWM inverter circuit to form a power electronic converter to realize the frequency boost and power factor correction. Through AC-DC-AC conversion, the frequency of the three-phase AC input voltage is increased, the number of core and coil turns in the transformer is reduced to reduce the size of the phase-shifter transformer, a zigzag structure of the phase-shifter transformer is used to solve the unbalanced distribution of current between the diode bridges, and a passive harmonic suppression method on the DC side is used to generate a loop current by using a group of single-phase rectifier bridges to regulate the input line current of the phase-shifter transformer. The phase-shifted voltage is input into two three-phase diode rectifier bridges to rectify and supply power to the load. Simulation and semi-physical test results show that the proposed method reduces the total harmonic distortion (THD) value of the input current of the phase-shifted transformer to 7.17%, and the THD value of the grid-side input current is further reduced to 2.49%, which meets the harmonic standard and realizes the purpose of power factor correction as well as being more suitable for high-power applications.

Resilient bus-bar protection scheme for DC microgrids connected to AC electric grids

ABSTRACT In recent years, there has been a growing interest in incorporating microgrids into existing electrical power networks to reduce reliance on conventional grids. This is further due to the numerous benefits of microgrids, most notably the ability to operate in either autonomous or grid-connected mode, making microgrids a highly versatile structure to incorporate intermittent production and energy storage. However, despite the many benefits, it is difficult to present resilience protection for DC bus bar to ensure the efficient operation of a DC microgrid, as there is a non-zero crossing phenomenon of DC fault current, while zero crossing phenomenon of an AC fault. Additionally, the DC bus bar has both an AC side with rectified DC and a DC line current, creating protection concerns for microgrids. To address these issues, this article proposes a novel fast fault detection scheme for DC microgrids with multiple renewable energy sources, energy storage, and loads. The scheme incorporates current and voltage sensing through current and voltage transformers, along with advanced digital relays, to detect and isolate faults on the DC microgrid. By analyzing rectified AC and DC line data, the scheme employs a differential current-based protection strategy to safeguard the DC bus bar. Validated through comprehensive fault simulations in PSS/SINCAL, the method proves effective in maintaining DC bus voltage stability and enhancing microgrid flexibility.

Short-Circuit Fault Diagnosis on the Windings of Three-Phase Induction Motors through Phasor Analysis and Fuzzy Logic

An induction motor is an electric machine widely used in various industrial and commercial applications due to its efficiency and simple design. In this regard, a methodology based on the electric phasor analysis of line currents and the variations in the phase angles among these line currents is proposed. The values in degrees of the angles between every pair of line currents were introduced to a fuzzy logic algorithm based on the Mamdani model, developed using the Matlab toolbox for detection and isolation of the inter-turn short-circuit faults on the windings of an induction motor. To carry out the analysis, the induction motor was modified in its stator windings to artificially induce short-circuit faults of different magnitudes. The current signals are acquired in real time using a digital platform developed in the Delphi 7 high-level language communicating with a float point unit Digital Signal Processor (DSP) TMS320F28335 by Texas Instruments. The proposed method not only detects the short circuit faults but also isolates the faulty winding.

Wattmeter based on tunnel-effect magnetoresistance sensor.

This work shows how the tunnel-effect based magnetoresistance (TMR) technology can be used as a competitive sensing method in electrical current and power processors. The sensor is arranged in a Wheatstone bridge topology, and each magnetoresistance was composed of a series connection of 360 magnetic tunnel junction elements with the following structure (thickness in nm): 100 SiO2/5 Ta/15 Ru/5 Ta/15 Ru/5 Ta/5 Ru/20 IrMn/2 CoFe30/0.85 Ru/2.6 CoFe40B20/1.2 MgO/2 CoFe40B20/0.21 Ta/4 NiFe/0.20 Ru/6 IrMn/2 Ru/5 Ta/10 Ru. First, the electrical and thermal characteristics of the sensor were evaluated by analyzing its response to DC current sweeps at various temperatures, controlled using a climatic chamber. Nominal values of current sensitivity S (0.324 mV/A), bridge output offset voltage Vo,s,o (-37.1 mV), bridge input resistance Rinp,bridge (0.958 kΩ), and their thermal behavior were obtained (0.0036 mV/A°C, 0.079 mV/°C, and -0.31 Ω/°C). Second, an instrumentation system is introduced to characterize the sensor, measuring its sensitivity to AC line currents from the mains up to 10Arms. Finally, an electronic wattmeter was developed showing the relevant quantities of its design. The circuit is able to interface a TMR Wheatstone bridge to an analog processor. Power and current measurements were obtained from a 150Vrms AC mains 1.5 kW load with resistive and capacitive components, achieving less than 1% deviation over the expected values. The circuit shown can be used to interface these signals to more complex smart digital engines with active or reactive energy processing capabilities, while providing inherent high voltage isolation, thanks to its TMR measurement technology.

Electrophysiological Impact of SARS-CoV-2 Envelope Protein in U251 Human Glioblastoma Cells: Possible Implications in Gliomagenesis?

SARS-CoV-2 is the causative agent of the COVID-19 pandemic, the acute respiratory disease which, so far, has led to over 7 million deaths. There are several symptoms associated with SARS-CoV-2 infections which include neurological and psychiatric disorders, at least in the case of pre-Omicron variants. SARS-CoV-2 infection can also promote the onset of glioblastoma in patients without prior malignancies. In this study, we focused on the Envelope protein codified by the virus genome, which acts as viroporin and that is reported to be central for virus propagation. In particular, we characterized the electrophysiological profile of E-protein transfected U251 and HEK293 cells through the patch-clamp technique and FURA-2 measurements. Specifically, we observed an increase in the voltage-dependent (Kv) and calcium-dependent (KCa) potassium currents in HEK293 and U251 cell lines, respectively. Interestingly, in both cellular models, we observed a depolarization of the mitochondrial membrane potential in accordance with an alteration of U251 cell growth. We, therefore, investigated the transcriptional effect of E protein on the signaling pathways and found several gene alterations associated with apoptosis, cytokines and WNT pathways. The electrophysiological and transcriptional changes observed after E protein expression could explain the impact of SARS-CoV-2 infection on gliomagenesis.

A new least squares error based method for accurate phasor estimation of fault currents in series-compensated transmission lines

Phasor estimation of the fundamental component of the fault current is of great importance for the fault location unit in distance relays. In series-compensated transmission lines, the transient component of the fault current may appear in the complicated wave shape of an exponential-sinusoidal function. Thus, phasor estimation is a major challenge owing to the fact that more unknown parameters should be found, especially during off-nominal frequency conditions. Therefore, in this paper, a new method is put forward, on the strength of the least squares error (LSE), in order to accurately estimate the fundamental component phasor of the fault current in a series-compensated transmission line for off-nominal frequency conditions. The performance of the established method is also investigated through extensive simulation studies, taking care of different fundamental components, harmonic contents, and transient components. Moreover, the performance of the proposed method is evaluated for off-nominal frequencies. The results obtained in this study demonstrate that the mean absolute error of the estimated amplitude and phase for the fundamental component is less than 1% and 1°, respectively. Furthermore, the accuracy of the proposed method is not affected by the noise up to a signal-to-noise ratio of 30 dB. Thus, the established method is capable to effectively be employed for the phasor estimation in fault location applications.

Microgrid F36ault Detection Method Based on Lightweight Gradient Boosting Machine–Neural Network Combined Modeling

The intelligent architecture based on the microgrid (MG) system enhances distributed energy access through an effective line network. However, the increased paths between power sources and loads complicate the system’s topology. This complexity leads to multidirectional line currents, heightening the risk of current loops, imbalances, and potential short-circuit faults. To address these challenges, this study proposes a new approach to accurately locate and identify faults based on MG lines. Initially, characteristic indices such as fault voltage, voltage fundamentals at each MG measurement point, and extracted features like peak voltage values in specific frequency bands, phase-to-phase voltage differences, and the sixth harmonic components are utilized as model inputs. Subsequently, these features are classified using the Lightweight Gradient Boosting Machine (LightGBM), complemented by the bagging (Bootstrap Aggregating) ensemble learning algorithm to consolidate multiple strong LightGBM classifiers in parallel. The output classification results of the integrated model are then fed into a neural network (NN) for further training and learning for fault-type identification and localization. In addition, a Shapley value analysis is introduced to quantify the contribution of each feature and visualize the fault diagnosis decision-making process. A comparative analysis with existing methodologies demonstrates that the LightGBM-NN model not only improves fault detection accuracy but also exhibits greater resilience against noise interference. The introduction of the bagging method, by training multiple base models on the initial classification subset of LightGBM and aggregating their prediction results, can reduce the model variance and prevent overfitting, thus improving the stability and accuracy of fault detection in the combined model and making the interpretation of the Shapley value more stable and reliable. The introduction of the Shapley value analysis helps to quantify the contribution of each feature to improve the transparency and understanding of the combined model’s troubleshooting decision-making process, reduces the model’s subsequent collection of data from different line operations, further optimizes the collection of line feature samples, and ensures the model’s effectiveness and adaptability.

Performance Evaluation of the B4 Topology for Implementing Grid-Connected Inverters in Microgrids

The B4 topology is an interesting alternative to the conventional B6 inverter due to its reduced number of parts and lower cost. Although it has been widely used in the past, especially in low-power motor drive applications, its application as a grid-connected inverter is an open area of research. In this regard, this paper analyses the feasibility of the B4 inverter topology for grid-connected applications. A versatile 7 kW inverter prototype, which may be configured as B4 and B6, was built, allowing for a comprehensive evaluation of the performance of both topologies. Through an analytical study and experimental tests, the performance of the B4 and B6 topologies was comparatively evaluated in terms of efficiency, total harmonic distortion of line currents, current unbalance, cost, and mean time between failures. The study was carried out in the context of microgrid systems, highlighting their role in the integration of renewable energy and distributed generation.

Magnetic Design and Electromagnetic Field Simulation of Downhole Turbine Generator

With the increasing difficulty of oil and gas resources exploration and the increase of drilling operations in complex geological environments, the challenges faced by oil drilling operations are also increasing. With the continuous improvement of the intelligence of MWD/LWD drilling technology and downhole instruments, the demand for electric energy is also increasing. In order to ensure the normal operation of the equipment and the accurate acquisition of data, this paper designs a new type of external rotor downhole turbine generator, and designs the structure and parameters of the turbine generator. Finally, Ansoft Maxwell software is used to simulate and analyze the electromagnetic field of the generator. The results show that the induced electromotive force and load current waveform obtained by electromagnetic field simulation analysis have good sinusoidality. At the rated speed of 2500rpm, the effective value of the output line voltage of the turbine generator is about 49.1V, the effective value of the line current is about 10.99A, and the output power is about 841.17W, which meets the design requirements. The research has certain guiding significance for practical engineering.

Network Reconfiguration Framework for CO2 Emission Reduction and Line Loss Minimization in Distribution Networks Using Swarm Optimization Algorithms

This paper presents the development of a generic active distribution network (ADN) operation simulation framework that incorporates selected swarm optimization algorithms (SOAs) for the purpose of reducing CO2 emissions and line loss minimization through network reconfiguration (NR). The framework has been implemented in the ADN of Taipower. Network data, provided by the Distribution Mapping Management System and Distribution Dispatch Control Center (DDCC) of Taipower, were converted into an OpenDSS script to create ADN models. The SOA is integrated into the framework and utilized to determine the statuses of both four-way and two-way switches in the planning and operating stages, in accordance with the proposed multi-objective function and operational constraints. The weightings for these decisions can be customized by distribution operators to meet their specific requirements. In this paper, the weighting for line loss reduction is set to one for minimizing CO2 emissions. The numerical results demonstrate that the proposed ADN framework can recommend a feeder switching scheme to distribution operators, aiming to balance feeder loading and minimize the neutral line current. Finally, this approach leads to reduced line losses and minimizes CO2 emissions. In contrast to relying solely on historical operational experience, this generic ADN reconfiguration framework offers a systematic approach that can significantly contribute to reducing CO2 emissions and enhancing the operational efficiency of ADNs.

Harmonics Cancelation in 3-Phase 4-Wire System using Modified Reference Frame

In this paper, A modified synchronous reference frame (SRF) or (d-q theory) with Self-Tuning Filter (STF) for the three-phase four wires system is presented to control of 4-legs shunt active power filter (SAPF) under balanced supply voltages. The main goal of the paper is to apply this control method using unit vector generation with STF instead of PLL circuit. In utility power system, it has been observed that harmonics build a major role in reducing the power quality. These harmonics caused by nonlinear loads. Many consumers appliances demand quality of power continuously for their operation. The performance of the end user equipment is heavily dependent on the quality of power supplied to it. This power is affected by various external and internal factors. They are like voltage and frequency variations, faults, outages etc. The solution to overcome these problems is to filter out these harmonics. For this purpose, there are many filters' topologies and control methods are proposed and studied in the literature to eliminate harmonics currents. In our study, 4-legs shunt active power filter is proposed and controlled by d-q method with modified unit vector generation. The SAPF is proposed to solve problems of line harmonic currents and neutral line currents of three phase 4-wire power distribution system. The use of STF in the modified control method can optimize the performance of this topology regarding to classical one (high pass and low pass filters). The proposed control strategy is simulated in MATLAB Simulink and the results are presented.

Analytical modelling and implementation of a new four-switch hybrid power filter topology.

This paper presents a new three-phase four-switch shunt hybrid power filter with the new circuit topology aimed at compensating reactive power and higher harmonics of the load. A space-vector PWM scheme is adopted to reduce the switching state of power switches. In the proposed control scheme, proper voltage vectors are generated on the ac terminal for drawing nearly sinusoidal line currents with controllable power factor. An original closed-form solution of line currents, based on the mixed p-z approach is presented. The analytical procedure is verified by experimental results to confirm the effectiveness of the proposed control scheme