Energy Function Method Research Articles

Overvoltage ride through control strategy for improving voltage support capability of virtual synchronous generator

AbstractAs the application of renewable energy sources continues to increase, the virtual synchronous generator (VSG) has been proposed and received widespread attention. In China, new energy stations are typically situated at the transmission end of LCC‐HVDC lines. A failure in DC commutation can lead to overvoltage at the DC transmission end, thus posing a significant risk of disconnection from the grid due to the occurrence of overvoltage. Compared to when low‐voltage occur, it was discovered that, during overvoltage, VSGs face difficulties in rapidly attaining the preset power and transient instability. These issues can significantly impact the voltage support capability of the VSG. To address these concerns, an enhanced control strategy has been proposed. The control strategy sets reasonable power reference values, leveraging the advantage of fast voltage response in VSG by matching its voltage with virtual impedance. This ensures that the power rapidly reaches the designated reference value while reducing fluctuations in power angle. The transient power‐angle stability is validated using the energy function method. This approach enhances the reactive power absorbed by VSG, thereby mitigating transient overvoltage. Finally, simulation results from PSCAD/EMTDC validate the rationale and effectiveness of the control strategy.

Ship target detection in SAR images based on SimAM attention YOLOv8

AbstractDeep learning has been widely applied in ship detection in synthetic aperture radar (SAR) imagery due to their powerful feature representation capabilities. However, YOLOv8 models treat all regions of the image equally during convolutional feature processing, resulting in less‐than‐ideal outcomes. To address this limitation, this study proposes a simple, parameter‐free attention module (SimAM) attention‐based YOLOv8 algorithm for ship detection in SAR images. The proposed algorithm first passes through a backbone network, which incorporates SimAM attention modules. The SimAM attention mechanism successfully allocates the convolutional neural network's 3D weights effectively using an energy function method, without introducing additional parameters. This mechanism enables the network to automatically emphasize key features in the image, enhancing its ability to represent target areas and suppress background interference. Subsequently, deep features are upsampled and fused with relatively shallow features to extract features at three different scales and achieve target detection, ultimately outputting classification and positional information of the targets. The effectiveness of the model on the SAR‐ship‐dataset is experimentally validated achieving an mAP50 value of 97.72% and an mAP50‐95 value of 68.99%, confirming the superiority of the proposed model.

Linear and non-linear stability analysis of double-diffusive Hadley-Prats flow through horizontal porous layer with non-uniform thermal and solutal gradients

A scientific model is devised to understand the onset of double-diffusion Hadley-Prats flow through an infinite parallel permeable channel with non-uniform thermal, solutal gradients, and concentration based internal heat generation under the influence of convection conditions is considered. Darcy’s model is implemented in the context of a porous medium, which is characterized as isotropic and homogeneous. A linear and nonlinear stability analysis is conducted with the help of energy functional method and longitudinal roll perturbations are examined. The emerged dimensionless eigenvalue problem in the linear and nonlinear stability analysis is solved numerically by utilizing fourth order Runge-Kutta method (RK-4) method and shooting scheme. The critical values of wave and vertical thermal Rayleigh numbers are examined. A comprehensive analysis of solutions concerning the onset of convection mechanism is conducted. The produced results are discussed for the various values of emerged physical parameters. It is evident that, the presence of non-uniform thermal and solutal gradients and the internal heat generation mechanism causes the significant variations in the critical values of vertical thermal Rayleigh number in the channel regime.

Transient synchronization stability of photovoltaics integration by singular perturbation analysis

The integration of large-scale photovoltaics (PVs) into the power grid has significantly altered the transient synchronization dynamics of traditional power systems dominated by synchronous generators (SGs) and posed great challenges to modeling and analysis of PVs integration. In this paper, the transient synchronization stability of the PV-SG system is studied using the singular perturbation technique. Firstly, a nonlinear model of a PV-SG system is established to reveal the multiscale transient synchronization characteristics. Further, the full system is decomposed into a slow subsystem and a fast subsystem by the singular perturbation technique. The fast subsystem containing the dynamics of the DC voltage control, terminal voltage control, and phase-locked loop, and the slow subsystem containing the dynamics of rotor motion can perfectly reflect the dynamics of the full system within the electromagnetic and electromechanical timescales, respectively. The proposed model provides a clearer physical picture of dynamics in the PV-SG system within the electromagnetic and electromechanical timescales. Subsequently, the stability of the slow and fast subsystems is investigated using the energy function and eigenvalue analysis methods, respectively. Meanwhile, the impacts of various operating, control, and structural parameters on the transient synchronization stability are uncovered. Different from the most existing research endeavors on the wide simulations of the PVs integration, the impact of PVs on the synchronization dynamics of SGs without considering the dynamical characteristics of the PV system, and the transient synchronization stability analyses of the PLL-based voltage source converter systems, it is the key contribution to study the transient synchronization dynamical characteristics of the PV system and its interaction with the SG under different timescales. All these are helpful and easy to extend to more complicated PV-SG systems. Finally, the analysis results are validated by extensive simulations.

Finite Bending of Fiber-Reinforced Visco-Hyperelastic Material: Analytical Approach and FEM.

This paper presents a new anisotropic visco-hyperelastic constitutive model for finite bending of an incompressible rectangular elastomeric material. The proposed approach is based on the Mooney-Rivlin anisotropic strain energy function and non-linear visco-hyperelastic method. In this study, we aim to examine the mechanical response of a reinforced viscoelastic rectangular bar with a group of fibers under bending. Anisotropic materials are typically composed of one (or more) family of reinforcing fibers embedded within a soft matrix material. This operation may lead to an enhancement in the strength and stiffness of soft materials. In addition, a finite element simulation is carried out to validate the accuracy of the analytical solution. In this research, the well-known stress relaxation test, as well as the multi-step relaxation test, are examined both analytically and numerically. The results obtained from the analytical solution are found to be in good agreement with those from the finite element method. Therefore, it can be deduced that the proposed model is competent in describing the mechanical behavior of fiber-reinforced materials when subjected to finite bending deformations.

Component Mode Synthesis Based on the Energy Method for Frequency Domain Dynamic Response Analysis of Ballastless Track Structure

Used extensively in structural dynamics analysis, the energy method is advantageous for transforming boundary value problems of differential equations into variational extremum problems. Recent applications include analyzing the wave and vibration characteristics of track structures. However, traditional energy methods for dynamic modeling and analysis of ballastless track structures require obtaining the global stiffness matrix and mass matrix of the entire coupled system, which decreases computational efficiency. The EM-CMS algorithm for frequency domain dynamic response analysis of ballastless track structures has been proposed to address this issue. The core of EM-CMS is the development of model reduction strategies within the framework of the energy method to reduce matrix dimensions and thereby improve computational efficiency. Specifically, the steel spring floating slab track is the focus of this research. Utilizing the energy functional variational method, the modal properties of the rail and floating slab structures are obtained, and truncation is performed. A reduced-order model for the steel spring floating slab track is established by considering the boundary conditions between the rail-floating slab and the floating slab foundation (connected through fastener springs and steel springs, respectively, and considering the springs’ elastic potential energy). Comparatively, the computational efficiency of EM-CMS is approximately ten times greater than that of the energy method. The method’s accuracy is also carefully validated against finite element simulations.

A robust transient energy function‐based controller for enhancing transient stability of virtual power system

AbstractThis paper offers non‐linear control for enhancing the transient stability in power systems containing a photovoltaic (PV) and doubly fed induction generator (DFIG) by transient energy function (TEF) method and finite‐time observers. At first, the TEF method is utilized to enhance the transient stability in a power system containing a PV, DFIG, and synchronous generator (SG) by constructing a hybrid Lyapunov function. Then, the derivative terms in control are estimated with finite‐time observers. The main contribution of the research is the application of the TEF technique in the transient stability evaluation of a power system consisting of PV, SG, and DFIG. Another innovation of the research is the simultaneous control of DFIG and PV, whose uncertain parameters are estimated with the use of finite‐time observer. The proposed non‐linear control scheme is robust against changes in the configuration of the power system. In order to show the capability of this control scheme, time domain simulations are performed on the IEEE 9‐bus, and the NEW ENGLAND Standard 39‐Bus power system. Using the obtained result, some comparisons are made with the back‐stepping control scheme to clarify the superiority of the proposed method. The comparisons show that the proposed non‐linear control scheme can properly provide extra damping to reduce the first‐swing fluctuations in less time.

Region stability of switched two-dimensional linear dissipative Hamiltonian systems with multiple equilibria

This paper studies the issues of region stability of switched two-dimensional linear dissipative Hamiltonian systems. Such switched systems are composed of two stable subsystems with two different equilibrium points. Since the equilibrium points of two subsystems are different, and the state matrices of subsystems may not commute, it is difficult to address such switched systems. This paper considers the case that the switching path corresponding to the switched systems is a switching line passing through the equilibrium points of two different subsystems. A suitable region containing all the equilibrium points of subsystems is first determined. Based on the concept of region stability of switched systems with multiple equilibrium points, this paper proposes some sufficient conditions of region stability and asymptotically region stability for such kind of switched linear dissipative Hamiltonian systems via the maximum energy function method. The above main results obtained can be applied to some classes of electronic circuits, such as switching DC/DC converters and AC/DC converters. As an application and illustration, a switching DC circuit and two numerical examples are carried out to show the effectiveness of the region stability results obtained in this paper.

A New Medical Analytical Framework for Automated Detection of MRI Brain Tumor Using Evolutionary Quantum Inspired Level Set Technique.

Segmenting brain tumors in 3D magnetic resonance imaging (3D-MRI) accurately is critical for easing the diagnostic and treatment processes. In the field of energy functional theory-based methods for image segmentation and analysis, level set methods have emerged as a potent computational approach that has greatly aided in the advancement of the geometric active contour model. An important factor in reducing segmentation error and the number of required iterations when using the level set technique is the choice of the initial contour points, both of which are important when dealing with the wide range of sizes, shapes, and structures that brain tumors may take. To define the velocity function, conventional methods simply use the image gradient, edge strength, and region intensity. This article suggests a clustering method influenced by the Quantum Inspired Dragonfly Algorithm (QDA), a metaheuristic optimizer inspired by the swarming behaviors of dragonflies, to accurately extract initial contour points. The proposed model employs a quantum-inspired computing paradigm to stabilize the trade-off between exploitation and exploration, thereby compensating for any shortcomings of the conventional DA-based clustering method, such as slow convergence or falling into a local optimum. To begin, the quantum rotation gate concept can be used to relocate a colony of agents to a location where they can better achieve the optimum value. The main technique is then given a robust local search capacity by adopting a mutation procedure to enhance the swarm's mutation and realize its variety. After a preliminary phase in which the cranium is disembodied from the brain, tumor contours (edges) are determined with the help of QDA. An initial contour for the MRI series will be derived from these extracted edges. The final step is to use a level set segmentation technique to isolate the tumor area across all volume segments. When applied to 3D-MRI images from the BraTS' 2019 dataset, the proposed technique outperformed state-of-the-art approaches to brain tumor segmentation, as shown by the obtained results.

Reliability Analysis of Power System Considering Flexibility Resources

Flexible resources are a critical resource in ensuring the security and steady running of a large percentage of electricity systems that use new sources of energy. The power system’s flexible resources participate in power regulation, improving the power system capability to absorb new energy and also the electricity system’s reliability. This paper calculates the dependability index of electricity system using the basic calculation method of the equivalent energy function. By flexibly handling the new power generation curve’s adjustable capacity and flexible resources, new energy generation and flexible resources count toward equivalent energy calculation, and the dependability index of the electricity system is calculated. The efficacy of this approach is illustrated by an example.

Energy function‐guided histogram analysis for interrupted sampling repeater jamming suppression

AbstractInterrupted sampling repeater jamming (ISRJ) is a novel intra‐pulse coherent jamming based on digital radio frequency memory (DRFM). By repeatedly sampling and retransmitting the radar transmitting signal fragments, a series of false targets can be formed after pulse compression (PC), posing a severe threat to modern radar systems. Inspired by the energy function method and histogram analysis in image processing, an adaptive time‐frequency (TF) filtering method is proposed in this letter. The ISRJ‐contaminated regions can be accurately determined in the TF image after histogram analysis and subsequent energy accumulation. Guided by the energy function, the proposed method can automatically adjust the intensity threshold in TF image histogram analysis and therefore reveals better robustness compared with other competing methods. Simulations have verified the effectiveness and robustness of the proposed method against ISRJ under various circumstances.

Transient Stability of Low-Inertia Power Systems With Inverter-Based Generation

This study examines the transient stability of low-inertia power systems with inverter-based generation (IBG) and proposes a sufficient stability criterion. In low-inertia grids, transient interactions are induced between the electromagnetic dynamics of the IBG and the electromechanical dynamics of the synchronous generator (SG) under a fault. For this, a hybrid IBG-SG system is established and a delta-power-frequency model is developed. Based on this model, new mechanisms of transient instability different from those of conventional power systems from the energy perspective are discovered. First, two loss-of-synchronization (LOS) types are identified based on the relative power imbalance owing to the mismatch between the inertia of the IBG and SG under a fault. Second, the relative angle and frequency will jump at the moment of a fault, thus affecting the system energy. Third, the cosine damping coefficient induces a positive energy dissipation, thereby contributing to the system stability. A unified criterion for identifying the two LOS types is proposed using the energy function method. This criterion is proved to be a sufficient stability condition for addressing the effects of the jumps and cosine damping coefficient on the system stability. The new mechanisms and effectiveness of the criterion are verified based on simulation results.

Adaptive prescribed time control for quadrotor formation with stochastic links failure

AbstractThe formation control for multiple quadrotors subject to maintaining the formation configuration and collision avoidance in the situation of stochastic links failure is investigated in this paper. First, the distributed formation controller is designed, the position controller is developed to manage the desired formation of position, and the attitude controller is developed to control the translation and rotation movements of the quadrotor. Then, in order to avoid the collisions between multiple quadrotors and the obstacles, a potential energy function method is introduced into the quadrotor formation control combined with the nest adaptive control. Inspired by the design of event trigger controller, a communication compensation controller is designed to ensure the stability of quadrotor formation under the condition of random communication interruption and recovery. Moreover, a prescribed time function is designed, which means the convergence time of the formation system can be set in advance. The prescribed time stability of the formation control system is proved by Lyapunov theory. Finally, the simulation results verify the effectiveness and superiority of this method.

Decentralized Mutual Damping Control of Cascaded-Type VSGs for Power and Frequency Oscillation Suppression

This paper reveals the power and frequency oscillation mechanism of the islanded cascaded-type virtual synchronous generators (VSGs), and proposes a decentralized mutual damping suppression method. In the proposed scheme, the mutual damping term is constructed via the decentralized manner with transmission line current. It contributes to increasing damping and accelerating the frequency convergence of cascaded-type VSGs in the dynamic process. As a result, the power and frequency oscillations are restrained, and the system dynamic performance is improved. Further, the system stability based on the Lyapunov energy function method is proved. Finally, the effectiveness of the proposed decentralized mutual damping control is verified by simulations and experimental results.

Robust ΔSCF calculations with direct energy functional minimization methods and STEP for molecules and materials.

The direct energy functional minimization method using the orbital transformation (OT) scheme in the program package CP2K has been employed for Δ self-consistent field (ΔSCF) calculations. The OT method for non-uniform molecular orbitals occupations allows us to apply the ΔSCF method for various kinds of molecules and periodic systems. Vertical excitation energies of heteroaromatic molecules and condensed phase systems, such as solvated ethylene and solvated uracil obeying periodic boundary conditions, are reported using the ΔSCF method. In addition, a Re-phosphate molecule attached to the surface of anatase (TiO2) has been investigated. Additionally, we have implemented a recently proposed state-targeted energy projection ΔSCF algorithm [K. Carter-Fenk and J. M. Herbert, J. Chem. Theory Comput. 16(8), 5067-5082 (2020)] for diagonalization based SCF in CP2K. It is found that the OT scheme provides a smooth and robust SCF convergence for all investigated excitation energies and (non-)periodic systems.

Exponential Cluster Phase Synchronization Conditions for Second-Order Kuramoto Oscillators

This brief delivers cluster phase synchronization conditions for the second-order Kuramoto network under the effects of damping and inertia. These conditions are derived via an energy function method, which are related to the natural frequencies, damping and inertial constants of oscillators, and intra- and inter-cluster couplings among them. We show that each cluster can achieve exponential synchronization in the phase cohesive region when the inter-cluster coupling is sufficiently weak or strong. The effectiveness of presented conditions is validated on numerical examples.

Preparation and characterization of SiC-ZAC composite material for immobilizing the simulated radioactive graphite

For the safe treatment and disposal of radioactive graphite, SiC-ZAC (ZAC: ZnO-Al2O3-CaO glass-ceramic) composite materials were designed, in which ZAC is used as a sintering additive. The performance of ZAC was firstly studied by ASTM C1285 leaching test to obtain a formula composition with high chemical stability. Then, using the optimized formula of ZAC, the SiC-ZAC composites were prepared by vacuum calcination at 1350 °C–1410 °C for the immobilizing of simulated radioactive graphite, and the structure and compositions of SiC-ZAC composites were studied by XRD, SEM, EDS. The material Gibbs free energy function method was used to calculate the thermodynamics of SiC-ZAC composites to investigate the reaction ways among Si, C and ZAC. The results show the Z30 (30 wt% ZnO, 44.91 wt% Al2O3, 25.09 wt% CaO) glass-ceramic is the applicable formula composition due to its high chemical stability, in which the normalized elemental mass loss of Zn, Al, Ca are 10−6g/m2-10−5 g/m2, 10−1 g/m2, 10−1 g/m2 respectively. Calcined at 1350 °C for 2 h, the B-Z30(0)-1(70.05 wt% Si, 29.95 wt% C) sample can be obtained with the phase compositions of β-SiC, α-SiC and a small amount of residual graphite. Moreover, the formations of Ca2Al2SiO7 and CaAl4O7 crystalline phase had a negative effect on the immobilization of simulated radioactive graphite in SiC-ZAC composites.

Adaptive Iterative Learning Control for High-Speed Train: A Multi-Agent Approach

The precise tracking control of high-speed train is an essential prerequisite to ensure the safety and comfort of the train. In this paper, an adaptive iterative learning control (ILC) scheme for the velocity and displacement tracking of high-speed train is proposed to handle the unknown time-varying parameters and lumped uncertainties. The composite energy function (CEF) method is used to analyze the stability of closed-loop system. Since the train usually runs on the same railway periodically, such as the same tunnels, slopes, bridges, etc., ILC is an inherent method for designing the tracking controller that is able to improve the operation performance of train iteratively. To the best of our knowledge, it is the first time that the multi-agent framework and ILC methodology are considered simultaneously in a single train, which can better reveal the coupled characteristic of adjacent cars and impose the repetitive operation pattern of train. The results of numerical simulations show that the tracking performance of the train toward the reference trajectory is significantly improved along with the increase of the number of operations.

Energy Prediction Model of PSO-BP Neural Network Three-dimensional Clusters based on Atomic Coordinates

Energy prediction for different cluster structures is the basis for finding and predicting the global optimal structure of clusters. The current methods for predicting the energy of the ground state structures of different clusters include theoretical prediction methods and optimized simplified potential energy function methods. The accuracy of the theoretical prediction method is high, but its calculation amount is too large. Therefore, this paper proposes a PSO-BP neural network three-dimensional cluster energy prediction model based on atomic coordinates, and uses different types of Euclidean distances between atoms as input variables, and the energy of clusters with different structures as output variables. Select gold cluster Au20 and boron cluster B45-part of the sample data as the training set to build the model, and predict the rest of the samples, and finally get: the prediction accuracy of the PSO-BP neural network model is higher than that of the traditional BP neural network model. The cluster energy prediction model is feasible.

Asymptotic profile of a two-dimensional Chemotaxis–Navier–Stokes system with singular sensitivity and logistic source

This paper is concerned with a spatially two-dimensional version of a chemotaxis system with logistic cell proliferation and death, for a singular tactic response of standard logarithmic type, and with interaction with a surrounding incompressible fluid through transport and buoyancy. Systems of this form are of significant relevance to the understanding of chemotaxis-fluid interaction, but the rigorous knowledge of their qualitative properties is yet far from complete. In this direction, using the conditional energy functional method, the present work provides some interesting contributions by establishing results on global boundedness, and especially on large time stabilization toward homogeneous equilibria, under mild assumptions on the initial data and appropriate conditions on the strength of the damping death effects.