Time-varying Load Research Articles

Intelligent Caching for Vehicular Dew Computing in Poor Network Connectivity Environments

In vehicular networks, some edge servers may not function properly due to the time-varying load condition and the uneven computing resource distribution, resulting in a low quality of caching services. To overcome this challenge, we develop a Vehicular dew computing (VDC) architecture for the first time by combining dew computing with vehicular networks, which can achieve wireless communication between vehicles in a resource-constrained environment. Consequently, it is crucial to develop an adaptive caching scheme that empowers vehicles to form efficient cooperation in VDC. In this paper, we propose an intelligent caching scheme based on VDC architecture, which includes two parts. First, to meet the dynamic nature of VDC, a spatiotemporal vehicle clustering algorithm is proposed to establish adaptive cooperation to assist content caching for vehicles. Second, the multi-armed bandit algorithm is employed to select suitable content for caching in vehicles based on real-time file popularity, and a model is established to dynamically update each vehicle’s request preferences. Extensive experiments are conducted to demonstrate that the proposed scheme has excellent performance in terms of cluster head stability and cache hit rate.

Application of Fractional Order PI/PID Voltage Controllers for Three-Phase Voltage Source Inverter with Dynamic Load

Purpose: With the depletion of fossil fuels, the landscape of electrical energy generation has witnessed a transformative shift towards alternative sources such as fuel cells and photovoltaic (PV) systems that produce direct current (DC) electricity. In the realm of distributed power generation, three-phase voltage source inverters (VSIs) are extensively utilized for converting energy from DC sources to alternating current (AC) for the grid or loads. The pivotal objective of this study is to investigate and compare the performance of fractional-order Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) control structures against their integer-order counterparts in the voltage control loop of a VSI connected to a dynamic load system.
 Materials and Methods: The research employs frequency response analysis to design and implement both fractional-order PI/PID and integer-order PI/PID control structures for the voltage control loop. The simulation of the controlled system is conducted using MATLAB/Simulink, considering two distinct test scenarios – unstable and stable dynamic load conditions. The primary focus is on analyzing the inverter output voltage in the d-q axis under these scenarios.
 Findings: The analysis of the simulation results reveals noteworthy distinctions between the fractional-order and integer-order PI/PID controllers in the context of controlling the inverter system with dynamic loads. These findings shed light on the advantages of employing fractional order controllers, particularly in dynamic load scenarios, showcasing superior performance in comparison to their integer-order counterparts.
 Implications to Theory, Practice and Policy: The study's outcomes hold significant implications for the theory and practice of voltage control in distributed power generation systems. The superiority of fractional-order PI controllers underscores their potential for enhancing power quality, especially in systems with unstable and time-varying dynamic loads. These insights can inform the development of more effective control strategies for voltage source inverters, influencing both theoretical frameworks and practical applications. Policymakers may consider these findings when formulating regulations and incentives to promote the adoption of advanced control strategies in the evolving landscape of electrical energy generation.

Fluid-solid coupling numerical simulation of the effects of different doses of verapamil on cancellous bone in type 2 diabetic rats

BackgroundThe purpose of this study was to investigate the effects of four different doses of verapamil on the mechanical behaviors of solid and the characteristics of fluid flow in cancellous bone of distal femur of type 2 diabetes rats under dynamic external load.MethodsBased on the micro-CT images, the finite element models of cancellous bones and fluids at distal femurs of rats in control group, diabetes group, treatment groups VER 4, VER 12, VER 24, and VER 48 (verapamil doses of 4, 12, 24, and 48 mg/kg/day, respectively) were constructed. A sinusoidal time-varying displacement load with an amplitude of 0.8 μm and a period of 1s was applied to the upper surface of the solid region. Then, fluid-solid coupling numerical simulation method was used to analyze the magnitudes and distributions of von Mises stress, flow velocity, and fluid shear stress of cancellous bone models in each group.ResultsThe results for mean values of von Mises stress, flow velocity and FSS (t = 0.25s) were as follows: their values in control group were lower than those in diabetes group; the three parameters varied with the dose of verapamil; in the four treatment groups, the values of VER 48 group were the lowest, they were the closest to control group, and they were smaller than diabetes group. Among the four treatment groups, VER 48 group had the highest proportion of the nodes with FSS = 1-3 Pa on the surface of cancellous bone, and more areas in VER 48 group were subjected to fluid shear stress of 1-3 Pa for more than half of the time.ConclusionIt could be seen that among the four treatment groups, osteoblasts on the cancellous bone surface in the highest dose group (VER 48 group) were more easily activated by mechanical loading, and the treatment effect was the best. This study might help in understanding the mechanism of verapamil’s effect on the bone of type 2 diabetes mellitus, and provide theoretical guidance for the selection of verapamil dose in the clinical treatment of type 2 diabetes mellitus.

Dynamics analysis of helical gear considering de-meshing and reverse impact with EHL lubrication condition.

The purpose of this paper was to study the evolution and dynamic characteristics of the helical gear system co-existence response considering the occurrence of de-meshing and reverse impact under lubrication conditions. The double-three tooth alternate meshing model of a helical gear was established, and the time-varying geometric parameters, motion parameters, and load distribution of positive meshing and reverse impact were analyzed, respectively. The variation of oil film parameters and the coupling between oil film stiffness and meshing stiffness of a gear system were studied according to the equivalent lubrication model of a helical gear. Considering the phenomenon that the meshing state changed from positive meshing to de-meshing and reverse impact, the dynamics model was established. The global bifurcation diagram, the attraction domain, the phase portrait, and the Poincaré section were used to analyze the evolution of a coexistence response and dynamic characteristics with helical gear system parameters.

Fault diagnosis of rotating machinery using novel self-attention mechanism TCN with soft thresholding method

Rotating machinery (e.g. rolling bearings and gearboxes) is usually operated in high-risk and vulnerable environments such as time-varying loads and poor lubrication. Timely assessment of the operational status of rotating machinery is crucial to prevent damage caused by potential failure and shutdown, which significantly enhances the reliability of mechanical systems, prolongs the service life of critical components in rotating machinery, and minimizes unnecessary maintenance costs. In this regard, in this paper, a novel approach named self-attention mechanism combining time convolutional network with soft thresholding algorithm (SAM-TCN-ST) is proposed for fault intelligent recognition of rotating machinery. Specifically, the vibration signals are transformed into time-frequency graphs with distinct features utilizing the continuous wavelet transform, and then the proposed SAM-TCN-ST algorithm is employed for capturing essential data characteristics and classification performance. Eventually, datasets from rolling bearings and gearboxes are used to verify the accuracy and effectiveness of the proposed method compared with state-of-the-art benchmark networks such as pure TCN, convolutional neural networks and long short-term memory models. Experimental results demonstrate that the recognition accuracy rate of the proposed SAM-TCN-ST is higher than that obtained from the benchmark methods. This research presents an intelligent and viable solution for achieving real-time monitoring of the status and detecting faults in rotating machinery, thereby expectedly enhancing the reliability of mechanical systems. Consequently, the proposed SAM-TCN-ST algorithm holds significant potential for applications in prognostic and health management practices related to rotating machinery.

Machine learning-based optimal distributed generation and electric vehicle load management

The load profile of radial distribution networks (RDNs) is significantly impacted when plug-in electric vehicles (PEVs) are connected to them in large numbers. The disturbances in the load profile may lead to increased power losses in distribution lines and deterioration of the network voltage profile. The provision of distributed generation at strategic locations in the distribution network can help to compensate for the impact on the electrical network due to PEV loads. This paper proposes the use of machine learning (ML)-based models for determining the optimal location of distributed generators (DGs) in an RDN. The proposed method considered time-varying load in addition to PEV load. The suggested method determines optimal placement of DGs based on the power loss reduction index and voltage deviation index reduction index. Four distinct types of ML models were used in the proposed approach using synthesised data on the Institute of Electrical and Electronics Engineers' 33-bus RDN. The performance of the ML models was evaluated with respect to mean squared error and mean absolute percentage error and, for the ML models considered, the random forest ML model gave the best performance.

Vibration stability and bifurcation analysis of spur gear systems based on time-varying backlash and random load

Gear backlash and random load affect the stability of gear transmission, which are the main factors causing meshing impact. This study presents the establishment of a six-degree-of-freedom model for the spur gear system, employing the lumped parameter theory and D'Alembert's principle. The model comprehensively incorporates the effects of time-varying meshing stiffness (TVMS), static transmission error (STE), time-varying gear backlash, and random load. The system's equations of motion are solved using the fourth-order Runge-Kutta method. Subsequently, the dynamic response of the constant backlash constant load model is compared with that of the time-varying backlash constant load model and the constant backlash random load model. This research quantitatively dissects the impact of the nonlinear characteristics of backlash and load on the dynamic response of the gear system. This analysis is conducted utilizing a variety of methods, including bifurcation diagrams, Floquet characteristic multipliers, Lyapunov exponents, phase diagrams, and Poincaré sections. The study demonstrates that fluctuations in backlash and load during meshing compromise the stability of the periodic solution, thereby escalating the complexity of predicting system motion. Moreover, observations include the jump phenomena, quasi-periodic and periodic motions, and the trajectory of the system transitioning into a chaotic state via bifurcation. This investigation serves as a valuable reference for future explorations into spur gear systems.

Integration of a proton exchange membrane fuel cell system for voltage and frequency stabilization in a micro hydro system

This work discusses the frequency and voltage stabilization in a stand-alone self-excited induction generator system (SEIGs) using a fuel cell (FC)-based generation unit. The proposed SEIG acts as the power generator in a microhydro system. Variations in load create fluctuations in voltage and frequency, which have to be stabilized. In this work, authors have proposed integrating a FC-based generation unit with the existing SEIGs to improve its voltage and frequency profiles. For this work, a proton exchange membrane fuel cell (PEMFC) has been considered. Modeling of a 36 kW PEMFC is taken for the proposed work, which has to be integrated with the 22 kW self-excited induction generator. The design of the system and converter parameters have also been included in the work. Authors have proposed an orthogonal current component-based controlstructure that provides independent control of active and reactive power in the system. Considering the FC system working conditions, this article aims to assure optimum power transfer capability between the self-excited induction generator, fuel cell system, and the time-varying loads. The system is exposed to time-varying RL loads dynamic load switching, and the performance is evaluated in real-time. OP 4510 real-time simulator verifies the proposed system's dynamic model created using Matlab/Simulink.

A Simulation Study of an Electro-Hydraulic Load-Sensitive Variable Pressure Margin Diverter Synchronous Drive System with Time-Varying Load Resistance

This study aims to address the problem of poor synchronous accuracy when facing a time-varying load in conventional load-sensitive synchronous drive systems. The new electro-hydraulic load-sensitive (EHLS) diverter synchronous drive system was proposed by combining the diverter valve and the EHLS synchronous drive system. The variable pressure margin compensation control was proposed to further improve the system’s synchronous control performance. Based on the system control strategy and component mathematical model, the simulation models of the EHLS, EHLS synchronous, and EHLS diverter synchronous drive systems were established using AMESim, respectively, and the synchronous control performance of the systems was obtained. The simulation results show that the EHLS drive system realized the primary functions of the load-sensitive system and could realize the variable load-sensitive pressure margin control. The EHLS synchronous drive system had poor synchronous control accuracy, but variable pressure compensation valve pressure margin control could be realized. The EHLS diverter synchronous drive system effectively improved the system’s synchronous control performance and diverter synchronous accuracy by variable pressure margin compensation control. The diverter system diverter error was reduced by 40.8%, and the diverter system after the compensation diverter error was reduced by 52.6% when the multi-way valves were fully opening. The system provides the solution for high-performance hydraulic synchronous drives under severe operating conditions.

Modified state space method for bending creep and recovery behaviors of viscoelastic orthotropic laminated plate

A modified state space method (SSM) is proposed first to solve the analytical solution of viscoelastic orthotropic laminated (VOL) plate under time-varying load. This modification extends the applicability of traditional SSM from elastic materials to viscoelastic materials by resolving a limitation of the traditional SSM, where computing the exponential function of the state space matrix is infeasible. In the analytical model, the long-term stresses and displacements are established based on the orthotropic elasticity theory combined with the Boltzmann superposition. The convolution within the governing equation is resolved through Laplace transform. By using the proposed modified SSM, the general solution for each viscoelastic lamina is derived out, by separating the complex variable of Laplace transform out from the state space matrix. The analytical solution is ultimately derived using series expansion, transfer matrix method and inverse Laplace transform. The proposed model can provide long-term creep stress distribution in the VOL plate by creep deflection data from experiment. The comparison with existing results indicates the proposed solution exhibits greater accuracy than simplified solutions and higher efficiency compared to the finite element method. At last, the bending creep and recovery behaviors of the VOL plate are investigated in detail.

Nonreciprocal propagation of bending waves in spatiotemporally modulated prestressed beam

Breaking time or/and spatial symmetry can lead to unprecedent mechanical responses of a structure, the design of which is usually very intricate. This paper proposes a simple design of a beam structure with spatiotemporal modulation. In fact, a time-varying axial load applied to the ends of an elastic beam will induce space-time dependent axial force propagating in the form of longitudinal wave in the beam, which can modulate spatiotemporally the propagation of transverse bending waves. The governing equation is derived, of which the Floquet solution leads to a quadratic eigenvalue problem that can be solved for the frequency as a function of the wavenumber. Theoretical results show the existence of asymmetric wavenumber bandgaps and the unique dispersion diagram which is not periodic with respect to time or space. The breaking of temporal symmetry enables nonreciprocal propagation of transverse bending waves, which is confirmed by the finite element simulations. This modulation method offers promise for applications in the fields of elastic wave filter, frequency converter and magnitude amplifier.

ASMC and ARSMC cascaded controller design for QUAVs with time-varying load and unknown disturbances

ASMC and ARSMC cascaded controller design for QUAVs with time-varying load and unknown disturbances

Optimal Design of Volt/VAR Control Rules for Inverter-Interfaced Distributed Energy Resources

The IEEE 1547 Standard for the interconnection of distributed energy resources (DERs) to distribution grids provisions that smart inverters could be implementing Volt/VAR control rules among other options. Such rules enable DERs to respond autonomously in response to time-varying grid loading conditions. The rules comprise affine droop control augmented with a deadband and saturation regions. Nonetheless, selecting the shape of these rules is not an obvious task, and the default options may not be optimal or dynamically stable. To this end, this work develops a novel methodology for customizing Volt/VAR rules on a per-bus basis for a single-phase feeder. The rules are adjusted by the utility every few hours depending on anticipated demand and solar scenarios. Using a projected gradient descent-based algorithm, rules are designed to improve the feeder’s voltage profile, comply with IEEE 1547 constraints, and guarantee stability of the underlying nonlinear grid dynamics. The stability region is inner approximated by a polytope and the rules are judiciously parameterized so their feasible set is convex. Numerical tests using real-world data on the IEEE 141-bus feeder corroborate the scalability of the methodology and explore the trade-offs of Volt/VAR control with alternatives.

A novel energy management method for multiple residential energy systems with energy exchange

Energy saving and emission reduction are the worldwide outstanding problems in the development of economy and society, which lead to wide attention of residential energy management. This paper presents a novel energy management method for multiple residential energy systems with energy exchange based on action-dependent heuristic dynamic programming (ADHDP). The major contributions are displayed as follows: (1) a novel energy management model is established for multiple residential energy systems with real-time electricity price and time-varying residential loads; (2) a novel ADHDP based energy management method is presented to obtain the energy scheduling scheme of multiple residential energy systems; (3) the continuous control action of the overall system is transformed into discrete control space which avoids training the action network. First, the structure and system models of multiple residential energy systems are introduced, and the energy management problem is formulated. Then, a brief introduction of ADHDP method is provided. Based on this, an energy management method is presented and an effective discretization method of control action is developed for solving the presented energy management problem with less computational burden. Simulation results show that the presented method can reduce the energy cost effectively. Finally, the comparison results verify the superiorities over the traditional energy management methods.

OPTIMAL COORDINATED VOLTAGE CONTROL OF ELECTRICAL DISTRIBUTION NETWORKS IN THE PRESENCE OF DISTRIBUTED RENEWABLE ENERGY SOURCES

Recently, distributed generation (DG), as clean and renewable energy, has increased due to the global warming problems and depletion of fossil sources. Several DGs are installed near the end-user, with the feature that this will decrease power losses. However, without optimal control, many problems, such as voltage instability and power losses, may affect the performance and the good operation of the power system. This paper proposes an optimal coordinated voltage control (OCVC) method for the distribution networks with distributed generation sources. The method is based on a genetic algorithm (GA) approach in multi-core simulation with an open-source OpenDSS to obtain the optimal setting of voltage control devices adjusted remotely. This method takes into account time-varying load and generation based on day-ahead scheduling. To validate the performances of the proposed technique, simulations are performed in a distribution network test with DG integration.

Multiple control strategies for smart photovoltaic inverter under network voltage fluctuations and islanded operation

This article proposes a central control system that communicates with both grid-tied and off-grid control systems to offer various control strategies for operating a smart photovoltaic (PV) inverter. The target is to connect two sets of PV panels and one set of battery storage unit to either a 440 V/60 Hz utility grid or to feed local loads at 380 V/50 Hz using a smart inverter. When the smart PV inverter is connected to the grid, on the one hand, it injects fixed and programmed active power into the grid under all operating conditions, both normal and critical conditions, and on the other hand, by reciprocal exchanging reactive power with the grid, it addresses balanced and unbalanced fluctuations of the grid voltage. Also, when the smart PV inverter is disconnected from the grid, it can operate as an islanded mode to feed time-varying three-phase loads. Nonlinear simulations of the time domain in MATLAB-Simulink software show that the set of control strategies offered for the smart PV inverter not only by controlling the active power leads to the sale of electricity to the grid, but also by controlling the reactive power problems on the grid side such as voltage drop as a result of single-line-to-ground (SLG) or line-to-line-to-ground (2LG) faults, balanced grid voltage fluctuations such as voltage sag-swell and unbalanced voltage conditions will be resolved. Also, variable three-phase loads are fed well in off-grid mode.

Time-varying traffic load model of expressway based on long-term monitored data from multiple regions — A case in central and eastern China

Traffic load is one of the main loads borne by highway transportation infrastructure, which seriously impacts the safe operation of the bridge and road. Due to the change in the external environment and government policy, the traffic load has obvious time-varying characteristics, which is the key to establishing the real traffic load model. The two main time-varying factors of traffic load are the growth of traffic volume and the evolution of vehicle weight. In the long-term research work, there is a lack of research based on continuous monitoring data for the above two factors. Therefore, this paper carries out a study on the time-varying traffic load model of expressways based on long-term monitored data from multiple regions. Firstly, the data sources of monitored 18 expressways in central and eastern China are introduced. Secondly, the Logistic model is selected as the basic model to study the growth laws of expressways from different provinces; meanwhile, the evolution of vehicle weight distribution is also analyzed and a simplified model is established accordingly. Finally, a case study of a newly opened eight-lane expressway is operated to characterize the influence of time-varying vehicles. The results show that the traffic volume and vehicle weight distribution change significantly with the increase of service time. The Logistic model and liner model are appropriate to characterize the evolution model of the traffic volume and vehicle weight distribution separately. The time-varying characteristics of traffic load have a significant impact on the standard fatigue traffic load model and the cumulative equivalent axle loads. The research results could provide a reference for the establishment of time-varying traffic load standard models for highways and the revision of related standards. At the same time, it could provide technical support for the full life-cycle investigation and design of the road and bridge infrastructure.

Essential characteristics of rigid concrete airport pavements under cyclic traffic loading revealed from a thermodynamic perspective

The increasing global air traffic has placed higher demands on airport pavement design. However, the behavior of rigid concrete airport pavement (RCAP) under traffic loading is very complex, and the existing reliability theory and empirical concrete pavement analysis methods cannot detect the precise RCAP failure point. Based on this background, this paper attempts to study the failure of RCAP under traffic loading from a thermodynamic perspective. It selects the Federal Aviation Administration (FAA) test in Construction Cycle 8 (CC8) phase 3 as the research material. We apply the structural stressing state theory to equate the RCAP under traffic loading to a thermodynamic system with a phase transition, i.e., we model the whole process strain data as state variables. Then, analogous to the renormalization group method of Wilson's phase transition theory to reveal the critical point of the system, this study establishes matrixes (Modes) and Hamiltonians (Characteristic parameters) that can characterize the RCAP full-process stressing state evolution under traffic loading by accumulating the difference of state variables. We attempted to verify the effectiveness of this method under such complex working conditions, which can also be applied to many other high-speed time-variant loading conditions. By applying the clustering analysis criterion, we can reveal the phase transition points of the RCAP: elastoplastic branch (EPB), failure starting (FS), and progressive failure (PF) points, respectively. Taking the NW group as an example, the variances of EPB, FS, and PF points revealed by the mode and characteristic parameter curves conducted by the two homogeneous measured point selections, respectively, are 7.7,6.4, and 6.4, which are of exceptionally high stability. We also used thermodynamic modeling to reveal the phase transition points of the remaining three RCAPs and compared the effect of different joints on the phase transition points. Finally, this study also explores the feasibility of EPB-based concrete airport pavement design.

Study on the vibration characteristics of deep groove ball bearings under time-varying loads

A general methodology for dynamic modeling and analysis of deep groove ball bearing used in the crank-slider mechanism of punching machine is presented in this paper. The time-varying loads applied at the inner ring of this bearing can be obtained by analyzing the planar multibody systems. The bearing joint has been modeled by introducing a nonlinear constraint force system, which takes into account the contact stiffness interaction between the rolling elements and the raceways. The four-degree-of-freedom dynamic equations for the inner and outer rings of the bearings is established by Newton's second law. By numerical calculation, the variations of the load, trajectory, FFT frequency domain response, and x direction phase trajectory and Poincare of the inner ring, and the contact force on each ball element are discussed. The results indicate that the present methodology can not only be used to analyze the overall dynamic behavior of crank-slider mechanism and the deep groove ball bearing used in punching machine, but also to obtain the dynamic loads of the inner ring and ball in bearing. Therefore, the dynamic loads on ball elements can provide a basis for the strength checking, fatigue life calculation and wear analysis of the deep groove ball bearing.

Model-free frequency regulation in islanded microgrids: An event-triggered adaptive dynamic programming approach

This paper is concerned with frequency regulation in islanded microgrids via an event-triggered adaptive dynamic programming method. Comparatively to the existing works, we relax the typical limitations on the system, namely, exactly known models, constant load impedances, and single operation mode. The adopted frequency regulation scheme can reach frequency synchronization within the acceptable bounds in the presence of the model uncertainties, operation mode switching, and time-varying loads with no need for any prior information on the system parameters. By employing an event-triggered scheme, the secondary controller is updated only at the aperiodic triggering instants which contributes to less transmission cost. Besides, the use of measurements can help the adaptive weights to be adjusted online in the approximation process, which allows the proposed controller to adapt to the disturbances in real time. Finally, tests including the islanding process and load variation are performed in MATLAB/SimPowerSystem to show the effectiveness of the proposed method.