Voltage Angle Research Articles

Fault in Converter Interfaced Micro Grid Using Detection and Identification of Hybrid Technique

ABSTRACTThis paper introduces a novel hybrid approach, termed ZOA‐SNN, for fault detection and identification in converter‐interfaced microgrids. By integrating the Zebra Optimization Algorithm (ZOA) with Spiking Neural Network (SNN) technology, the proposed method provides a comprehensive solution suitable for both grid‐connected and autonomous microgrid operation scenarios. The technique effectively isolates faults in the microgrid while maintaining operation continuity, particularly in islanded conditions. When operating in grid‐connected mode, distributed generators (DGs) provide electricity as needed. When the grid is not available, power sharing amongst DGs is controlled by voltage angle droop control. By isolating malfunctioning portions, the proposed protection system reduces load shedding, while DG control guarantees smooth islanding and resynchronization. Evaluation on the MATLAB platform demonstrates the superior performance of the proposed technique compared to existing algorithms such as Augmented Lagrangian Particle Swarm Optimization (ALPSO), Graph Convolutional Network (GCN), and Buffalo Optimization (BO). With an accuracy, recall, precision, and F1‐score reaching 98.5%, 99.2%, 99.1%, and 99.1%, respectively, the ZOA‐SNN approach excels in fault detection and classification. Additionally, it significantly reduces computation times for parameter calculation, enhancing efficiency in microgrid control systems. These results highlight the innovation and advantages of the ZOA‐SNN approach in enhancing the reliability and efficiency of fault detection systems in microgrid environments.

Characteristics of Merging Plasma Plumes for Materials Process Using Two Atmospheric Pressure Plasma Jets

Atmospheric pressure plasma jets (APPJs) have attracted significant attention due to their ability to generate plasma without vacuum systems, facilitating their use in small areas of plasma processing applications across various fields, including medicine, surface treatment, and agriculture. In this study, we investigate the interaction between two helium plasma jets, focusing on the effects of varying flow rate, voltage, and directional angle. By examining both in-phase and out-of-phase configurations, this research aims to elucidate the fundamental mechanisms of plasma plume merging, which has critical implications for optimizing plasma-based material processing systems. We demonstrate that while increasing voltage and flow rate for the in-phase condition leads to an extended plasma plume length, the plumes do not merge, maintaining a minimal gap. Conversely, plasma plume merging is observed for the out-of-phase condition, facilitated by forming a channel between the jets. This study further explores the impact of these merging phenomena on plasma chemistry through optical emission spectroscopy, revealing substantial differences in the emission intensities of OH, the second positive system of N2, and the first negative system of N2+. These findings offer valuable insights into controlling plasma jet interactions for enhanced efficiency in plasma-assisted processes, particularly where plume merging can be leveraged to improve the treatment area and intensity.

Online Monitoring System of Electromechanical Transient Simulation Data of Distribution Network Based on Edge Computing

The current distribution network is developing toward the direction of information and intelligent distribution Internet of Things (IoT). In order to explore the online monitoring system for transient electromechanical simulation of distribution networks, this paper is based on the equivalent model of generator sets. Firstly, it describes the relevant theoretical knowledge of edge computing, designs the distribution IoT based on edge computing, and briefly introduces its network architecture. Secondly, based on the discrete-time domain equivalent model of generators, the electromechanical transient simulation distribution network is constructed by introducing the machine network division of the power network. Finally, the Western System Coordinating Council (WSCC)-3 units and 9 nodes are taken as an example, and simulation experiments are conducted under two fault simulation conditions to verify the effectiveness of the simulation model. The results show that under the two fault simulation conditions, the results of equivalent model simulation of generator terminal voltage and relative power angle change are like those of the Power System Analysis Software Package (PSASP). The changing trend of the two is similar and stable. After the PSASP results are stabilized at a value, the simulation results fluctuate extremely up and down the value. For example, under fault condition 1, the changing trend of the relative power angle of the No. 2 generator is first fluctuating and then becomes stable. After violent fluctuation, the relative power angle tends to be stable from about 20s to -12.35°. The result of PSASP software is stable at -12.35°. The transient electromechanical simulation of the generator equivalent model can provide some ideas for the online monitoring system of the distribution network.

Deep neural network based distribution system state estimation using hyperparameter optimization

In the past decade, distribution system state estimation has become a crucial topic in power system research due to the increasing importance of distribution networks amidst the decline of centralized energy production. This paper addresses a gap in the literature regarding the application of modern hyperparameter optimization techniques in low-voltage distribution system state estimation using deep neural networks. In particular, it demonstrates the use of the Tree-structured Parzen Estimator algorithm, which is a Bayesian hyperparameter optimization method, for distribution system state estimation on real Hungarian low-voltage networks. The study uses data from four real-life low-voltage supply areas in Hungary, which were modeled to address the challenges in obtaining network information. Compared to traditional methods like the weighted least squares method, the Tree-structured Parzen Estimator algorithm significantly improves the accuracy of the voltage amplitude and angle estimations, reducing the relative error by 14–73%. Additionally, it is shown that TPE outperforms simpler methods like Random Search in hyperparameter optimization. The results also reveal connections between the distribution system size and optimal hyperparameters, such as batch size, learning rate, and hidden layer configuration. The proposed non-iterative algorithm, combined with the parallel computation capabilities of deep neural networks utilizing GPU, resulted in four orders of magnitude improvement in runtime. These advancements make the proposed approach a valuable tool for renewable energy integration planning and real-time monitoring, highlighting its potential for practical applications in the power industry.

Phase Dependence of Surface Charge Measurement on Epoxy Insulator in C4F7N/CO2 under AC Voltage.

The application of binary gas mixtures consisting of heptafluorobutyronitrile (C4F7N) and carbon dioxide (CO2) in AC GIS is currently attracting much attention. Therefore, the evaluation of the gas-solid interface charge distribution characteristics of epoxy resin is indispensable. Additionally, the phase-dependency of the charging behavior remains not fully understood. We simulated coaxial electrode structure in GIS and investigated the surface charge distribution on a down-scaled epoxy insulator. The influence of the truncated phase angle and duration of AC voltage on charge behavior were analyzed, and the charge transport mechanism under AC voltage was theoretically analyzed. The results showed that there was a noticeable negative charge speckle with the presence of the metal particle and the accumulated negative charge on the insulator surface far exceeded that of the positive charge. The maximum surface charge density and the amount of surface charge accumulated first increased and then decreased over time. It was found that the phase angle has a negligible influence on the surface charge distribution at the cut-off moment.

Detection and Discrimination of Interturn Fault and High-Resistance Connection Fault in PMSM Based on Deviation Angle of Zero Sequence Voltage

Detection and Discrimination of Interturn Fault and High-Resistance Connection Fault in PMSM Based on Deviation Angle of Zero Sequence Voltage

Deciphering the Radiation Dose Summary Page in Interventional Fluoroscopy.

Fluoroscopy is an advanced medical imaging modality that utilizes x-rays to acquire real-time images throughout a medical examination. It is commonly used in various procedures such as in interventional radiology, cardiac catheterization, and gastrointestinal and genitourinary studies. While fluoroscopy is a valuable diagnostic and therapeutic tool, it exposes patients and medical staff to ionizing radiation, which carries health risks. A radiation dose summary page is a report generated by the fluoroscope that displays important information about the procedure. It provides an overview of the radiation doses administered during a fluoroscopic procedure, as well as certain technical parameters used during the irradiation events. The contents of a radiation dose summary page may vary depending on the make and model of the fluoroscope but some common elements include the cumulative reference air kerma, which serves as a surrogate of radiation dose delivered to the patient, and the dose-area product, which takes account of the x-ray beam area and is a measure of the total amount of energy imparted on the patient. Other imaging acquisition parameters may be also included in the dose summary page, including tube voltage, tube current, pulse width, pulse rate, spectral filters, primary and secondary angles, and source-to-image distance. The radiation dose summary page for fluoroscopy is a useful tool for physicians, technologists, and medical physicists, allowing them to comprehend the technical details of a fluoroscopically guided procedure. ©RSNA, 2024.

Enhancing power system stability with adaptive under frequency load shedding using synchrophasor measurements and empirical mode decomposition

This paper introduces an adaptive under frequency load shedding (AUFLS) scheme based on synchrophasor measurements and Empirical Mode Decomposition (EMD) to enhance power system stability during significant disturbances. The traditional UFLS methods, which rely on fixed frequency thresholds, often lead to unnecessary disconnections and a lack of flexibility. The proposed AUFLS scheme dynamically adapts to the magnitude of disturbances, frequency response, and voltage stability index, resulting in a more efficient and responsive system. Various UFLS techniques are reviewed, highlighting the advantages of adaptive strategies. The novelty of this research lies in the innovative application of the EMD algorithm within the AUFLS framework. This method identifies the center of inertia (CoI) of the rate of change of frequency (RoCoF) from frequency signals and calculates the total active power imbalance due to disturbances. Furthermore, EMD is applied to the voltage angle at each bus to identify and form coherent bus groups. These coefficients are subsequently employed to allocate the required active power shedding within each group to maintain system stability. Voltage stability indices are calculated for each group, and load shedding is distributed among the buses based on normalized voltage stability indices, thereby enhancing the precision of load shedding decisions and the overall stability of the power system. Results demonstrate that the proposed scheme provides satisfactory frequency response while requiring less load shedding compared to traditional methods, making it effective for modern power systems with high penetration of renewable energy sources (RES). The performance of the proposed scheme is assessed using the IEEE 39-bus test system, demonstrating its effectiveness in improving system resilience to frequency disturbances. The research concludes that the AUFLS scheme offers a promising approach for enhancing the resilience of power systems to frequency disturbances.

PMUs data based detection of oscillatory events and identification of their associated variable: Estimation of information measures approach

Information theory can be a useful tool for quantifying the perturbations in the associated state variables at the time of disturbance occurrence. The study introduces a framework for the spectral decomposition of multivariate information measures to detect initiation of low frequency oscillations (LFOs), caused due to physical events in the power grid. A frequency-specific quantification of the information is shared between a target variable and two source variables from their time series data. Initially, the approach is applied on different synthetic test signals having different oscillatory frequency modes and decay time constant. Then, approach is extended on PMUs signals. The combination of cross-spectral and information-theoretic approaches is applied for the multi-variable analysis of PMUs signals from the same bus. The interdependence among the frequency, voltage angle and voltage magnitude, corresponding to specific oscillations, manifested due to cause-effect relationships obtained in terms of statistics is estimated. The dynamics in terms of unique (interaction), redundant and synergetic information is determined with the contribution from two of these three signals as source variables to target variable (frequency/voltage angle). This provides a direct coupling to identify driver-response relationships between source variables and target variable to indicate the onset of LFOs, following physical events in power network. The extension of approach among the variables from different buses aids to identify the responsible area of event occurrence.

Voltage Angle Control for a BLDC Motor and Controller Gain Design

Voltage Angle Control for a BLDC Motor and Controller Gain Design

Green energy solution for grid integrated solar PV system for water storage towers

In India, water storage towers are present almost everywhere, especially across small towns to rural areas. The storage tanks either utilize diesel powered or utility grid fed induction motor (IM) water pumps. The large spaces available with water storage towers can be utilized to plant solar PV panel for large storage towers water pumping operation, hence, making a switch from diesel or grid run storage towers to solar operated storage towers. This paper presents a robust control of grid integrated solar PV-based water pump system with efficient and smooth transition between standalone and grid interfaced modes. A smart DC link voltage control is presented for distributed generation system (DGS), which provides full control on DC link voltage for both modes of operation at all dynamic load conditions. An enhanced phase-locked loop (EPLL) control is utilized for grid source converter (GSC) in grid control operation, making it flexible to different grid scenarios and power quality. It works for harmonics suppression, load balancing and grid side converter control. An enhanced phase-locked loop (EPLL) is implemented for synchronization control algorithm, which provides an accurate estimation of voltage angle even during frequency ramps and exhibiting superior performance particularly in terms of robustness against DC offsets. The primary requirement for smooth operation of grid-tied solar PV system is effective power management between different sources. The issues of power management and power quality, are discussed in this work, and solutions are presented. The implemented control algorithms are tested successfully for dynamic solar insolation, varying load conditions, unbalance in load, sudden grid outage condition. The system appropriateness is validated by experimental results.

Seamless transfer of virtual synchronous generator using virtual synchronizing torque controller

AbstractInverter‐dependent renewable energy sources are being integrated into the grid, raising several stability‐related difficulties. This is because these renewable sources have less inertia than synchronous generators. Since the power grid's overall inertia has improved, the introduction of virtual synchronous generators (VSG) has gained much attention. A robust microgrid system requires an effortless transition from grid‐connected to autonomous mode. This can be easily achieved with the help of VSGs. The angle, frequency, and magnitude of the grid voltage needed for synchronization have traditionally been determined by phase‐locked‐loop (PLL). The virtual synchronizing torque and voltage‐based synchronization controller for simple switching between islanding and grid‐connected modes are presented in this study. The proposed method requires no additional controller to identify the unwanted islanding situations because the operating mode can be identified with the help of synchronizing torque. The proposed method does not need to shift to different control algorithms while changing between grid connection and stand‐alone modes. The effectiveness of the suggested controller is established by comparing the experimental prototype of the VSG incorporating the proposed controller to the existing synchronization methods.

An easy method for simultaneously enhancing power system voltage and angle stability using STATCOM

The global electricity demand is growing rapidly and is expected to double by 2050. This growth requires significantly expanding the current high-voltage transmission lines, which is a long-term and costly solution. As an alternative, utilities use advanced technologies like Flexible Alternating Current Transmission System (FACTS) devices as a temporary measure, postponing the expansion. However, it is necessary to locate these devices in the network properly to avoid negative outcomes. Traditional methods for FACTS placement focus on voltage profile improvement and power loss reduction, neglecting rotor angle stability. This can lead to oscillatory instability, especially in weak power grids. To address this issue, the paper proposes a simple approach to optimize the placement of shunt FACTS devices in power systems. The method improves both voltage and rotor angle stability without compromising power loss. The proposed approach considers rotor angle stability constraints, which is essential for system stability during transient events. The study was demonstrated on Nigeria’s 50-bus 330 kV power system, with results indicating a 31% improvement in angle stability with an enhanced voltage profile. The method is straightforward, non-iterative, and provides a cost-effective solution for FACTS device placement in power systems.

Combined ns pulsed-RF excitation and impedance matching considerations for the production of moderate E/n atmospheric pressure discharges for gas conversion

Sub-breakdown radiofrequency (RF) discharges enabled by a nanosecond (ns) pulse ignition source are studied at atmospheric pressure in a range of gas mixtures from completely inert (in Ar) to completely reactive (in CO2). An electrical characterisation of the continuous wave (CW) RF discharge (13.56 MHz) is performed to determine plasma impedance and plasma power dissipation. Two different measurement methods to electrically characterize the system are described and compared. One method uses in-situ measurements of discharge parameters (voltage, current and the phase angle), and the other method performs ex-situ measurements of the load circuit using a vector network analyser. It was found that RF plasma power deposition depended on the applied RF power as well as the gas mixture composition. Using the in-situ voltage, current and phase angle measurements, plasma power deposition was calculated to be as much as 85% and 76% of the applied RF power for the pure Ar and pure CO2 cases, respectively. A preliminary qualitative assessment of the plasma composition was performed by optical emission spectroscopy, and CO2 conversion by mass spectrometry. CO2 to CO conversions of 11.2% and 5.5% in a 20:80 (CO2:Ar) mixture and in 100% CO2, respectively, were observed. This study demonstrates a RF plasma source for gas conversion applications at atmospheric pressure in a completely reactive gas.

Grid synchronization method based on three novel types of third-order generalized integrators

Phase-locked loop (PLL) is widely used to estimate synchronous information such as amplitude and phase angle of grid voltage. It plays a crucial role in distributed renewable energy grid-connected power generation. However, the presence of grid harmonics and DC offset voltage (DCOV) can affect the accurate extraction of the fundamental voltage component, leading to phase-locked deviation. This paper introduces three novel or improved third-order generalized integrators (TOGI) with DCOV rejecting function to address this issue. A unified dual third-order generalized integrator (DTOGI) structure is designed based on the three TOGI structures. This DTOGI structure is further combined with a moving average filter (MAF) to propose three innovative three-phase PLLs. Unlike other PLL filtering methods that inadequately consider DCOV, the proposed PLL methods not only reject DCOV but also eliminate the fundamental voltage negative sequence component (FVNSC) and each order harmonic component. They demonstrate strong robustness and excellent filtering performance even under abnormal grid conditions. Among the three methods, the DII-TOGI based PLL exhibits superior dynamic performance compared to the other two methods, it can improve dynamic characteristics by about 10 % compared to the other two methods. The effectiveness of the proposed methods is verified through extensive Matlab/Simulink simulations and experiments.

Voltage and Reactive Power-Optimization Model for Active Distribution Networks Based on Second-Order Cone Algorithm

To address the challenges associated with wind power integration, this paper analyzes the impact of distributed renewable energy on the voltage of the distribution network. Taking into account the fast control of photovoltaic inverters and the unique characteristics of photovoltaic arrays, we establish an active distribution network voltage reactive power-optimization model for planning the active distribution network. The model involves solving the original non-convex and non-linear power-flow-optimization problem. By introducing the second-order cone relaxation algorithm, we transform the model into a second-order cone programming model, making it easier to solve and yielding good results. The optimized parameters are then applied to the IEEE 33-node distribution system, where the phase angle of the node voltage is adjusted to optimize the reactive power of the entire power system, thereby demonstrating the effectiveness of utilizing a second-order cone programming algorithm for reactive power optimization in a comprehensive manner. Subsequently, active distribution network power quality control is implemented, resulting in a reduction in network loss from 0.41 MW to 0.02 MW. This reduces power loss rates, increases utilization efficiency by approximately 94%, optimizes power quality management, and ensures that users receive high-quality electrical energy.

Optimal voltage angle for maximum torque per voltage control of induction machine in deep field‐weakening region

AbstractThis paper investigates the optimal stator voltage angle in a rotor flux‐oriented system of an induction machine drive, aiming to maximise machine torque while operating in a deep field weakening region. Here, torque maximisation leads to maximum torque per voltage control, as only voltage constraints are relevant in this region due to high back‐electromotive force. Previous studies have predominantly focused on field‐weakening operation and torque maximisation, assuming a constant synchronous speed. However, for a given rotor speed, the variation in the dq voltage components impacts the slip speed, thereby influencing the synchronous speed. Therefore, this paper proposes enhanced analytical expressions to address this limitation. It is shown that after a linearisation around a suitable operating point, a closed‐form algebraic equation for calculating the speed and parameter‐dependent optimal voltage angle for torque maximisation can be obtained. The theoretical analysis is supported by numerical and experimental results. The presented linearised expression is proven to be an effective tool for the analytical calculation of the optimal voltage angle, making it suitable for real‐time control applications. It is shown that the proposed approach achieves higher drive torque and efficiency than the conventional voltage component distribution.

Hardware-in-the-loop simulation test platform for UAV flight control system

The flight control system is the integrated command center and core component of the UAV system. Aiming at the problems of poor accuracy and low efficiency in the field measurement of flight control system parameters, combined with the configuration of the flight attitude sensor-vertical gyroscope, hardware-in-the-loop simulation technology, and integrated automatic test methods are adopted. The hardware-in-the-loop simulation test platform for the UAV flight control system composed of a low-cost, high-precision miniaturized UAV attitude calibration platform and a control piston deflection angle test device is designed. The main controller replaces the ground master control station of the UAV and directly sends remote control commands to the aircraft. By changing the attitude of the aircraft, and measuring the voltage of the control signal, the feedback signal, and the rudder angle, the comprehensive performance test of the parameters of the flight control system is realized. The performance test of the platform shows that the platform can meet the test requirements of angular position, system voltage, and control piston deflection angle.

Three-phase voltage sensitivity estimation and its application to topology identification in low-voltage distribution networks

This paper aims to estimate the three-phase voltage sensitivity matrix and the network topology of a low-voltage distribution network from smart meter data, which measures voltage magnitude, current magnitude, and power factor with a lead/lag indicator. The targeted networks are three-phase networks with single-phase loads. Understanding network sensitivity and topology is crucial for fault detection, unmetered load identification, and addressing Dynamic Operating Envelope problems. The problem is formulated as a constrained optimization problem to estimate both the three-phase voltage sensitivity and the low-voltage transformer voltage. The estimated voltage sensitivity is used to further identify the network topology, by implementing an enhanced Recursive-Grouping and Backtracking algorithm, as well as a candidate topology selection technique. The proposed method is tested on the 55-node European feeder and several synthetic networks. Compared to the state-of-the-art, the results show a four-fold improvement in the accuracy of voltage sensitivity estimation and substantially fewer mistakes in the topology estimates. The result underscores the efficacy of a three-phase network model and voltage angle approximation in enhancing estimation accuracy.

Investigation into the optoelectrowetting droplet transport mechanism.

To explore the optoelectronic wetting droplet transport mechanism, a transient numerical model of optoelectrowetting (OEW) under the coupling of flow and electric fields is established. The study investigates the impact of externally applied voltage, dielectric constant of the dielectric layer, and interfacial tension between the two phases on the dynamic behavior of droplets during transport. The proposed model employs an improved Young's equation to calculate the instantaneous voltage and contact angle of the droplet on the dielectric layer. Results indicate that, under the influence of OEW, significant variations in the interface contact angle of droplets occur in bright and dark regions, inducing droplet movement. Moreover, the dynamic behavior of droplet transport is closely associated with various parameters, including externally applied voltage, dielectric layer material, and interfacial tension between the two phases, all of which impact the contact angle and, consequently, the transport process. By summarizing the influence patterns of the three key parameters studied, the optimization of droplet transport performance is achieved. The study employs two-dimensional simulation models to emulate the droplet motion under the influence of the electric field, investigating the OEW droplet transport mechanism. The continuous movement of droplets involves three stages: initial wetting, continuous transport, and reaching a steady position. The findings contribute theoretical support for the efficient design of digital microfluidic devices for OEW droplet movement and the selection of key parameters for droplet manipulation.