Search Results (21)

The integration of renewable energy sources (RESs) into power systems, particularly in microgrids, is becoming a prominent trend aimed at reducing dependence on traditional energy sources. Replacing conventional synchronous generators with grid-connected RESs through power electronic converters has significantly reduced the inertia of microgrids. This reduction negatively impacts the dynamics and operational performance of microgrids when confronted with uncertainties, posing challenges to frequency and voltage stability, especially in a standalone operating mode. To address this issue, this research proposes enhancing microgrid stability through frequency control based on virtual inertia (VI). Additionally, the Iterative Learning Control (ILC) method is employed, leveraging iterative learning strategies to improve the quality of output response control. Accordingly, the ILC-VI control method is introduced, integrating the iterative learning mechanism into the virtual inertia controller to simultaneously enhance the system’s inertia and damping coefficient, thereby improving frequency stability under varying operating conditions. The effectiveness of the ILC-VI method is evaluated in comparison with the conventional VI (C-VI) control method through simulations conducted on the MATLAB/Simulink platform. Simulation results demonstrate that the ILC-VI method significantly reduces the frequency nadir, the rate of change of frequency (RoCoF), and steady-state error across iterations, while also enhancing the system’s robustness against substantial variations from renewable energy sources. Furthermore, this study analyzes the effects of varying virtual inertia values, shedding light on their role in influencing response quality and convergence speed. This research underscores the potential of the ILC-VI control method in providing effective support for low-inertia microgrids. Full article

Based on the single-crank linkage mechanism and the double-pendulum rod mechanism, herein, a reciprocating swing single-blade cutting device is appropriately designed for the needs of GLVs’ planting and cutting operations. It can effectively solve the existing double-blade cutting device’s in-soil operation issue, where clods of soil and stones adhere to the upper and lower cutting blades, resulting in problems such as excessive wear and blade fracture. Using ADAMS, a virtual model of the cutting device is established, and a kinematic analysis of the cutting process is performed to accurately determine the cutting trajectory curve and the mathematical model of the cutting rate. The single-factor test and quadratic regression orthogonal combination test are designed to investigate the influence of the test factors, including crank length, crank rotation speed, and forward speed on the repeated-cutting rate and the miss-cutting rate. Comprehensively considering the stability and reliability of cutting, power consumption, device design, and processing difficulty, the optimal operating parameters of the cutting device are obtained as crank length 19 mm, crank rotation speed 650 r/min, and forward speed 0.5 km/h. On this basis, the fitted regression equations of the repeated-cutting rate and the miss-cutting rate are established, the miss-cutting rate and the repeated-cutting rate under the optimal parameters are 1.519% and 28.503%, and the corresponding errors with the simulation values are obtained as 11.36% and −0.45%, respectively, which verified the validity of the fitted regression equations. In the present investigation, the motion behavior of the single-blade cutting device is methodically examined for the first time, and the cutting motion rules of the cutter are illustrated. The research results aim to provide a fairly solid theoretical basis and practical reference for the optimization design of the in-soil cutting device of GLVs’ orderly harvester. Full article

Focused on the contradiction between the steady-state error of active power and the dynamic oscillation caused by the virtual damping characteristics of the virtual synchronous generator (VSG) under disturbances during grid-connected operation, this article proposes an adaptive virtual inertia regulation and compensation method (PFFCVSG_AJ) based on an active power differential feedforward compensation strategy (PFFCVSG). Firstly, this article presents the working and control principles of VSG, analyzing its control mechanisms through a small-signal model. Models for VSG’s active power, reactive power, and virtual impedance components are established, with particular focus on the impact of the damping coefficient on active power regulation. Based on the PFFCVSG, an adaptive virtual inertia adjustment method is introduced to resolve the inherent inertia deficiency in PFFCVSG control, the influence of the moment of inertia on PFFCVSG is theoretically analyzed, and a dynamic adjustment mechanism for moment of inertia is developed based on the rate of change in frequency (RoCoF). Finally, simulation validation using MATLAB/Simulink (MathWorks, R2022b, Natick, MA, USA) demonstrates that the proposed PFFCVSG_AJ strategy effectively eliminates active power steady-state deviation, suppresses active power dynamic oscillation, and mitigates the frequency overshoot issue prevalent in traditional PFFCVSG. Experimental verification is conducted via a TMS320F28378DPTPS-based control platform, confirming the algorithm’s effectiveness under sudden load variations, and that the power quality of the power grid is not affected under the premise of efficient grid connection. Full article

With the increasing popularity of low-cost, clean, and environmentally friendly new energy sources, the proportion of grid-connected new energy units has increased significantly. However, since these units are frequency decoupled from the grid through a power electronic interface, they are unable to provide inertia support during active power perturbations, which leads to a decrease in system inertia and reduced frequency stability. In this study, the urgent need to accurately assess inertia is addressed by developing an energy-function-based inertia identification technique that eliminates the effect of damping terms. By integrating vibration mechanics, the proposed method calculates the inertia value after a perturbation using port measurements (active power, voltage phase, and frequency). Simulation results of the Western System Coordinating Council (WSCC) 9-bus system show that the inertia estimation error of the method is less than 1%, which is superior to conventional methods such as rate-of-change-of-frequency (RoCoF) and least squares methods. Notably, the technique accurately evaluates the inertia of synchronous generators and doubly fed induction generators (DFIGs) under virtual inertia control, providing a robust inertia evaluation framework for low-inertia power systems with high renewable energy penetration. This research deepens the understanding of inertial dynamics and contributes to practical applications in grid stability analysis and control strategy optimalization. Full article

When wind generation systems operate under weak grid conditions, synchronization stability issues may arise, restricting the wind farms’ power transfer capacity. This paper aims to address these challenges on the grid side. Firstly, a clear exposition of the coupling mechanism between the grid-connected inverters (GCI) of wind generations and the weak grid is provided. Then, an equivalent parallel compensation method integrated into the PLL to enhance synchronization stability is proposed. The method changes the reference of the PLL and equivalently parallels the virtual resistance with the grid impedance, which alters the strength of the grid. It reshapes the inverter qq-axis impedance at the impedance level. And the proper design of the virtual resistance will enhance the system’s stability without compromising the dynamic performance of PLL. In addition, the proposed method is robust to the parameter changes of the grid-connected system and the grid impedance measurement error. Experimental results are presented to validate the effectiveness of the compensation method. Full article

The development of the automotive industry is associated with the rapid advancement of onboard systems. In addition, intensive development in the electronics and control systems industry has resulted in a change in the approach to the issue of assistance systems in vehicles. Classic hydraulic systems have been almost completely replaced by modern electric power steering (EPS) systems, especially in citizen vehicles. This paper focuses on fault detection algorithms for EPS, along with the available tools to aid development and verification. The article discusses in detail the current state of knowledge in this area. The principle of operation of the EPS system and the influence of the structure of the mechanical system on its operation, in particular the characteristics of the ground–tire contact, are presented. Various error identification methods are presented, including those based mainly on a combination of tests of real objects as well as those combined with modern hardware-in-the-loop (HIL) equipment and virtual vehicle environment software, enabling the development of new diagnostic methods, enhancing the security, reliability, and energy control in the vehicle. A review of the literature indicates that although many algorithms which enable fault detection at an early stage are described, their potential for use in a vehicle is highly limited. The reason lies in simplifications, including models and the operating EPS temperature range. The most frequently used simplification of the model is its linearization, which significantly reduces the calculation time; however, this significantly reduces the accuracy of the model, especially in cases with a large range of system operation. The need for methods to detect incipient faults is important for the safety and reliability of the entire car, not only during regular use but also especially during life-saving evasive maneuvers. Full article

Due to their efficient renewable energy consumption performance, AC/DC hybrid microgrids have become an important development form for future power grids. However, the fault response will be more complex due to the interconnected structure of AC/DC hybrid microgrids, which may have a serious influence on the safe operation of the system. Based on an AC/DC hybrid microgrid with an integrated bidirectional power converter, research on the interaction impact of faults was carried out with the purpose of enhancing the safe operation capability of the microgrid. The typical fault types of the DC sub-grid were selected to analyze the transient processes of fault circuits. Then, AC current expressions under the consideration of system interconnection structure were derived and, on this basis, we obtained the response results of non-fault subnets under the fault process, in order to reveal the mechanism of DC fault propagation. Subsequently, a current limitation control strategy based on virtual impedance control is proposed to address the rapid increase in the DC fault current. On the basis of constant DC voltage control in AC/DC hybrid microgrids, a virtual impedance control link was added. The proposed control strategy only needs to activate the control based on the change rate of the DC current, without additional fault detection systems. During normal operations, virtual impedance has a relatively small impact on the steady-state characteristics of the system. In the case of a fault, the virtual impedance resistance value is automatically adjusted to limit the change rate and amplitude of the fault current. Finally, a DC fault model of the AC/DC hybrid microgrid was built on the RTDS platform. The simulation and experimental results show that the control strategy proposed in this paper can reduce the instantaneous change rate of the fault state current from 19.1 kA/s to 2.73 kA/s, and the error between the calculated results of equivalent modeling and simulation results was within 5%. The obtained results verify the accuracy of the mathematical equivalent model and the effectiveness of the proposed current limitation control strategy. Full article

Keystroke authentication is a well-established biometric technique that has gained significant attention due to its non-intrusive and continuous characteristics. The method analyzes the unique typing patterns of individuals to verify their identity while interacting with the keyboard, both virtual and hardware. Current deep-learning approaches like TypeNet and TypeFormer focus on generating biometric signatures as embeddings for the entire typing sequence. The authentication process is defined using the Euclidean distances between the new typing embedding and the saved biometric signatures. This paper introduces a novel approach called DoubleStrokeNet for authenticating users through keystroke analysis using bigram embeddings. Unlike conventional methods, our model targets the temporal features of bigrams to generate user embeddings. This is achieved using a Transformer-based neural network that distinguishes between different bigrams. Furthermore, we employ self-supervised learning techniques to compute embeddings for both bigrams and users. By harnessing the power of the Transformer’s attention mechanism, the DoubleStrokeNet approach represents a significant departure from existing methods. It allows for a more precise and accurate assessment of user authenticity, specifically emphasizing the temporal characteristics and latent representations of bigrams in deriving user embeddings. Our experiments were conducted using the Aalto University keystrokes datasets, which include 136 million keystrokes from 168,000 subjects using physical keyboards and 63 million keystrokes acquired on mobile devices from 60,000 subjects. The DoubleStrokeNet outperforms the TypeNet-based authentication system using 10 enrollment typing sequences, achieving Equal Error Rate (EER) values of 0.75% and 2.35% for physical and touchscreen keyboards, respectively. Full article

Both 25-autoimmunity and(25(OH)D: calcifediol) and its active form, 1,25-dihydroxyvitamin D (1,25(OH)₂D: calcitriol), play critical roles in protecting humans from invasive pathogens, reducing risks of autoimmunity, and maintaining health. Conversely, low 25(OH)D status increases susceptibility to infections and developing autoimmunity. This systematic review examines vitamin D’s mechanisms and effects on enhancing innate and acquired immunity against microbes and preventing autoimmunity. The study evaluated the quality of evidence regarding biology, physiology, and aspects of human health on vitamin D related to infections and autoimmunity in peer-reviewed journal articles published in English. The search and analyses followed PRISMA guidelines. Data strongly suggested that maintaining serum 25(OH)D concentrations of more than 50 ng/mL is associated with significant risk reduction from viral and bacterial infections, sepsis, and autoimmunity. Most adequately powered, well-designed, randomized controlled trials with sufficient duration supported substantial benefits of vitamin D. Virtually all studies that failed to conclude benefits or were ambiguous had major study design errors. Treatment of vitamin D deficiency costs less than 0.01% of the cost of investigation of worsening comorbidities associated with hypovitaminosis D. Despite cost-benefits, the prevalence of vitamin D deficiency remains high worldwide. This was clear among those who died from COVID-19 in 2020/21—most had severe vitamin D deficiency. Yet, the lack of direction from health agencies and insurance companies on using vitamin D as an adjunct therapy is astonishing. Data confirmed that keeping an individual’s serum 25(OH)D concentrations above 50 ng/mL (125 nmol/L) (and above 40 ng/mL in the population) reduces risks from community outbreaks, sepsis, and autoimmune disorders. Maintaining such concentrations in 97.5% of people is achievable through daily safe sun exposure (except in countries far from the equator during winter) or taking between 5000 and 8000 IU vitamin D supplements daily (average dose, for non-obese adults, ~70 to 90 IU/kg body weight). Those with gastrointestinal malabsorption, obesity, or on medications that increase the catabolism of vitamin D and a few other specific disorders require much higher intake. This systematic review evaluates non-classical actions of vitamin D, with particular emphasis on infection and autoimmunity related to the immune system. Full article

The construction hoist drive system is a critical component of the construction hoist, and high speed and low vibration noise are essential development directions. In order to improve the NVH level of the construction hoist drive system, this paper carries out research and analysis of construction hoist drive system excitation, establishes the drive system rigid-flexible coupling dynamics model, and completes the establishment of the vibration and noise model of the drive system, simulation analysis, and optimization work. Ansys Motor CAD 2020 was used to establish the parametric model of the asynchronous motor and it was combined with the virtual work method to calculate Maxwell’s electromagnetic force to arrive at the radial electromagnetic force as the main cause of electromagnetic noise. For the mechanical excitation generated by the gearbox, the time-varying stiffness excitation, mesh shock excitation, and transmission error excitation are considered, and the transmission error of helical gears under different working conditions is calculated by combining it with Romax software 2020. The rigid-flexible coupling model of the construction hoist drive system is established. The load distribution analysis of the unit length of the tooth surface is completed for the first- and third-stage helical gears under different working conditions. The primary source of the drive system excitation is the tooth surface bias load. Based on the dynamic response analysis theory of the vibration superposition method, the maximum vibration speed of the drive system was analyzed by Romax. The maximum noise value of 78.8 dB was calculated from the acoustic power simulation of the drive system using Actran acoustic software 2022 in combination with acoustic theory, and the magnetic density amplitude of the stator teeth of the asynchronous motor was optimized based on the microscopic shaping design of the helical gear by Romax. The vibration and noise simulation of the optimized drive system shows that the vibration value is reduced to 0.75 mm/s, and the maximum noise is reduced to 70.2 dB, which is 10.9% lower than before the optimization. The overall NVH level has been improved. The optimization method to reduce the vibration noise of the drive system is explored, which can be used for vibration noise prediction and control during the development of the construction hoist drive system. Full article

Power systems with a high wind power share are characterized by low rotational inertia and weak frequency regulation, which can easily lead to frequency safety problems. Providing virtual inertia for large-scale wind turbines to participate in frequency regulation is a solution, but virtual inertia is related to wind power output prediction. Due to wind power prediction errors, the system inertia is reduced and there is even a risk of instability. In this regard, this article proposes a unit commitment model that takes into account the constraints of sharp changes in frequency caused by wind power prediction errors. First, the expressions of the equivalent inertia, adjustment coefficient, and other frequency influence parameters of the frequency aggregation model for a high proportion wind power system are derived, revealing the mechanism of the influence of wind power prediction power and synchronous machine start stop status on the frequency modulation characteristics of the system. Second, the time domain expression of the system frequency after the disturbance is calculated by the segment linearization method, and the linear expressions of “frequency drop speed and frequency nadir” constraints are derived to meet the demand of frequency regulation in each stage of the system. Finally, a two-stage robust optimization model based on a wind power fuzzy set is constructed by combining the effects of wind power errors on power fluctuation and frequency regulation capability. The proposed model is solved through affine decision rules to reduce its complexity. The simulation results show that the proposed model and method can effectively improve the frequency response characteristics and increase the operational reliability of high-share wind power systems. Full article

The proliferation of devices for the Internet of Things (IoT) and their implication in many activities of our lives have led to a considerable increase in concern about the security of these devices, posing a double challenge for designers and developers of products. On the one hand, the design of new security primitives, suitable for resource-limited devices, can facilitate the inclusion of mechanisms and protocols to ensure the integrity and privacy of the data exchanged over the Internet. On the other hand, the development of techniques and tools to evaluate the quality of the proposed solutions as a step prior to their deployment, as well as to monitor their behavior once in operation against possible changes in operating conditions arising naturally or as a consequence of a stress situation forced by an attacker. To address these challenges, this paper first describes the design of a security primitive that plays an important role as a component of a hardware-based root of trust, as it can act as a source of entropy for True Random Number Generation (TRNG) or as a Physical Unclonable Function (PUF) to facilitate the generation of identifiers linked to the device on which it is implemented. The work also illustrates different software components that allow carrying out a self-assessment strategy to characterize and validate the performance of this primitive in its dual functionality, as well as to monitor possible changes in security levels that may occur during operation as a result of device aging and variations in power supply or operating temperature. The designed PUF/TRNG is provided as a configurable IP module, which takes advantage of the internal architecture of the Xilinx Series-7 and Zynq-7000 programmable devices and incorporates an AXI4-based standard interface to facilitate its interaction with soft- and hard-core processing systems. Several test systems that contain different instances of the IP have been implemented and subjected to an exhaustive set of on-line tests to obtain the metrics that determine its quality in terms of uniqueness, reliability, and entropy characteristics. The results obtained prove that the proposed module is a suitable candidate for various security applications. As an example, an implementation that uses less than 5% of the resources of a low-cost programmable device is capable of obfuscating and recovering 512-bit cryptographic keys with virtually zero error rate. Full article

Ethylene-Vinyl Acetate (EVA) copolymer was synthesized from ethylene and vinyl acetate at high temperatures and ultra-high pressures. In this condition, any reactor disturbances, such as process or mechanical faults, may trigger the run-away decomposition reaction. This paper proposes a procedure for constructing a conditional health status prediction structure that uses a virtual health index (HI) to monitor the reactor bearing’s remaining useful life (RUL). The piecewise linear remaining useful life (PL-RUL) model was constructed by machine learning regression methods trained on the vibration and distributed control system (DCS) datasets. This process consists of using Welch’s power spectrum density transformation and machine learning regression methods to fit the PL-RUL model, following a health status construction process. In this research, we search for and determine the optimum value for the remaining useful life period (T_RUL), a key parameter for the PL-RUL model for the system, as 70 days. This paper uses four-fold cross-validation to evaluate seven different regression algorithms and concludes that the Extremely randomized trees (ERTs) is the best machine learning model for predicting PL-RUL, with an average relative absolute error (RAE) of 0.307 and a Linearity of 15.064. The Gini importance of the ensemble trees is used to identify the critical frequency bands and prepare them for additional dimensionality reduction. Compared to two frequency band selection techniques, the RAE and Linearity prediction results can be further improved to 0.22 and 8.38. Full article

To enhance the operation effect and working performance of our previously developed strip fertilization planter for broken straw back throwing and inter-row laying, and to improve the stability of straw crushing and consistency of straw mulching between rows (broken straw inter-row mulching), the key operation parameters of the planter were optimized in this study. On the basis of determining the transmission route and matching power consumption, the discrete element method was used to establish a mechanical model of straw particles using the EDEM software, which was then imported into the rigid–flexible coupled system of the ‘shredded straw-mechanism’. Quadratic regression orthogonal methods and rotation combination experiments were then designed to carry out a DEM virtual simulation and numerical simulation, and the optimal combination of operating parameters affecting planter working performance was obtained, which was also verified by field tests. The simulation test results showed that the smashing spindle speed (A) had the most significant influence on the coefficient of variation (Y₁) of straw crushing, followed by the planter working forward speed (C). The conveying impeller speed (B) had the most significant influence on the coefficient of variation (Y₂) of inter-row straw mulching, also followed by (C). The optimal combination of operating parameters after optimization were A = 2060.79 rpm, B = 206.25 rpm, and C = 0.95 m·s⁻¹, and the optimal working performance of the planter was obtained as Y₁ = 8.51% and Y₂ = 10.34%. The evaluation index results corresponding to the field test were Y₁ = 9.35% and Y₂ = 10.97%, which met the technical requirements of the relevant operation machinery; the relative errors of the simulation test results were 9.87% and 9.63%, respectively, indicating the effectiveness of the virtual numerical simulation and the rationality of the optimized operation parameters. Our results provide a technical reference for realizing high-quality and smooth no-tillage seeding operations. Full article

This article examines the mechanisms for cross-border interchange of the regulating reserves (RRs), i.e., the imbalance-netting process (INP) and the cross-border activation of the RRs (CBRR). Both mechanisms are an additional service of frequency restoration reserves in the power system and connect different control areas (CAs) via virtual tie-lines to release RRs and reduce balancing energy. The primary objective of the INP is to net the demand for RRs between the cooperating CAs with different signs of interchange power variation. In contrast, the primary objective of the CBRR is to activate the RRs in the cooperating CAs with matching signs of interchange power variation. In this way, the ancillary services market and the European balancing system should be improved. However, both the INP and CBRR include a frequency term and thus impact the frequency response of the cooperating CAs. Therefore, the impact of the simultaneous operation of the INP and CBRR on the load-frequency control (LFC) and performance is comprehensively evaluated with dynamic simulations of a three-CA testing system, which no previous studies investigated before. In addition, a function for correction power adjustment is proposed to prevent the undesirable simultaneous activation of the INP and CBRR. In this way, area control error (ACE) and scheduled control power are decreased since undesired correction is prevented. The dynamic simulations confirmed that the simultaneous operation of the INP and CBRR reduced the balancing energy and decreased the unintended exchange of energy. Consequently, the LFC and performance were improved in this way. However, the impact of the INP and CBRR on the frequency quality has no unambiguous conclusions. Full article