Load Changes Research Articles

Nonlinear Characteristic Analysis of Gas-Interconnected Quasi-Zero Stiffness Pneumatic Suspension System: A Theoretical and Experimental Study

Because of significantly changed load and complex and variable driving road conditions of commercial vehicles, pneumatic suspension with lower natural frequencies is widely used in commercial vehicle suspension system. However, traditional pneumatic suspension system is hardly to respond the greatly changed load of commercial vehicles. To address this issue, a new Gas-Interconnected Quasi-Zero Stiffness Pneumatic Suspension (GIQZSPS) is presented in this paper to improve the vibration isolation performance of commercial vehicle suspension systems under frequent load changes. This new structure adds negative stiffness air chambers on traditional pneumatic suspension to reduce the natural frequency of the suspension. It can adapt to different loads and road conditions by adjusting the solenoid valves between the negative stiffness air chambers. Firstly, a nonlinear mechanical model including the dimensionless stiffness characteristic and interconnected pipeline model is derived for GIQZSPS system. By the nonlinear mechanical model of GIQZSPS system, the force transmissibility rate is chosen as the evaluation index to analyze characteristics. Furthermore, a testing bench simulating 1/4 GIQZSPS system is designed, and the testing analysis of the model validation and isolating performance is carried out. The results show that compared to traditional pneumatic suspension, the GIQZSPS designed in the article has a lower natural frequency. And the system can achieve better vibration isolation performance under different load states by switching the solenoid valves between air chambers.

Strain Measurement Technology and Precision Calibration Experiment Based on Flexible Sensing Fiber.

As the basic application of fiber optic sensing technology, strain measurement accuracy as a key index needs to be further calibrated and analyzed. In this paper, accuracy calibration experiments and the related analyses of two fiber-optic sensing technologies, the fiber-optic grating (FBG) and optical frequency domain reflectometry (OFDR), are carried out using a standard beam of equal strength and a mature resistive strain gauge (ESG). The fiber-optic single-point strain data for loading and unloading changes of the beams of equal strength show good continuity and linearity, with good cyclic stability, and the error in the strain test data is less than 2% after repeated loading. At the same time, using finite element theory to analyze the data and using the measured data error within 5%, a good strain test curve linearity is achieved and R2 is better than 0.998. After repeated loading and unloading tests, it is verified that the fiber grating and the distributed optical fiber in the strain test have good stability in repeatability accuracy. The calibration experiments and data analysis in this paper further illustrate the three sensing technologies in determining the strain test accuracy and the advantages and disadvantages of the indicators, and the development of the fiber optic sensing technology application provides basic technical support.

DRB1 locus alleles of HLA class II are associated with modulation of the immune response in different serological profiles of HIV-1/Epstein-Barr virus coinfection in the Brazilian Amazon region.

Epstein-Barr virus (EBV) infection involves distinct clinical and serological profiles. We evaluated the frequency of alleles of locus DRB1 of HLA class II in different serological profiles of EBV infection among HIV-1 infected patients. We recruited 19 patients with primary infection, 90 with serological transition and 467 with past infection by EBV, HIV-1 co-infection was 100% in primary infection and approximately 70% in other serological profiles. EBV viral load was quantified by real-time PCR, T lymphocyte quantification and cytokine level analysis were performed by flow cytometry, and HLA locus genotyping was performed by PCR-SSO. The DRB1*09 allele was associated with primary infection (p: 0.0477), and carriers of the allele showed changes in EBV viral load (p: 0.0485), CD8(+) T lymphocyte counts (p: 0.0206), double-positive T lymphocyte counts (p: 0.0093), IL-4 levels (p: 0.0464) and TNF levels (p: 0.0161). This allele was also frequent in HIV-coinfected individuals (p: 0.0023) and was related to the log10 HIV viral load (p: 0.0176) and CD8(+) T lymphocyte count (p: 0.0285). In primary infection, the log10 HIV viral load was high (p: 0.0060) and directly proportional to the EBV viral load (p: 0.0412). The DRB1*03 allele correlated with serological transition (p: 0.0477), EBV viral load (p: 0.0015), CD4(+) T lymphocyte count (p: 0.0112), CD8(+) T lymphocyte count (p: 0.0260), double-negative T lymphocyte count (p: 0.0540), IL-4 levels (p: 0.0478) and IL-6 levels (p: 0.0175). In the serological transition group, the log10 HIV viral load was high (p: 0.0060), but it was not associated with the EBV viral load (p: 0.1214). Past infection was related to the DRB1*16 allele (p: 0.0477), with carriers displaying IgG levels (p: 0.0020), CD4(+) T lymphocyte counts (p: 0.0116) and suggestive CD8(+) T count alterations (p: 0.0602). The DRB01*16 allele was also common in HIV-1 patients with past EBV infection (p: 0.0192); however, the allele was not associated with clinical markers of HIV-1 infection. Our results suggest that HLA class II alleles may be associated with the modulation of the serological profiles of the immune response to Epstein-Barr virus infection in patients coinfected with HIV-1.

Analyzing effective external interventions for optimizing energy hubs with electric and TS: A numerical study from a network topology perspective

Currently, there has been a notable surge in sabotage targeting critical infrastructures, particularly energy hub systems. External interventions on these infrastructures have significantly affected various loads, including electrical and thermal loads. Considering the significance of cybersecurity in energy hubs, there are high expectations for investigating the role of topology in their measures. The aim of this study is to investigate the impact of cyber sabotage on energy management within the demand sector, with a specific emphasis on the topology of an energy hub system. According to the structure of the desired energy hub that has been mathematically modeled, the CPLEX solver is used as a powerful optimization tool with the mixed integer linear programming (MILP) model, which serves as a framework for optimizing the operation cost of the energy hub. The findings reveal the occurrence of false data injection (FDI) into the real network loads. This inconsistency has led to disruption of energy management in the system. Utilizing considered scenarios, the first of them as the base scenario, representing the system under normal network conditions. The second scenario is modeled an attack vector aimed at the electric load, specifically utilizing FDI tactics with an understanding of the network topology. In the third scenario, attention turns to modeling a thermal load attack vector, utilizing FDI tactics with an understanding of its topology. In the final scenario, the emphasis is placed on designing an FDI-based attack vector that targets electric loads within the network, without prior knowledge of the energy hub's topology. Although in all scenarios where the attack is executed, the measuring devices during peak load indicate values lower than the actual ones, the intensity of the attack on the system is considerable in attacks conducted with knowledge of the energy hub topology. Taking into account the importance of the peak load intervals, the maximum changes in electric load during peak hours in the second scenario are compared to those in the first scenario, attributing them to interventions, representing approximately a 17.4 % difference. Similarly, assuming knowledge of the network topology during peak consumption, the impact of the attack on the thermal loads results in changes of 17.17 %. Additionally, in the fourth scenario compared to the first, the maximum changes in electric load during peak hours are approximately 2 %. In the meantime, the optimal cost has remained consistent across all scenarios, rendering the attacks undetectable to the operator and ultimately demonstrating the effectiveness of the proposed method.

Change Point Detection with Adaptive Measurement Schedules for Network Performance Verification

When verifying that a communications network fulfills its specified performance, it is critical to note sudden shifts in network behavior as quickly as possible. Change point detection methods can be useful in this endeavor, but classical methods rely on measuring with a fixed measurement period, which can often be suboptimal in terms of measurement costs. In this paper, we extend the existing framework of change point detection with a notion of physical time. Instead of merely deciding when to stop, agents must now also decide at which future time to take the next measurement. Agents must now minimize the necessary number of measurements pre- and post-change, while maintaining a trade-off between post-change delay and false alarm rate. We establish, through this framework, the suboptimality of typical periodic measurements and propose a simple alternative, called crisis mode agents. We show analytically that crisis mode agents significantly outperform periodic measurements schemes. We further verify this in numerical evaluation, both on an array of synthetic change point detection problems as well as on the problem of detecting traffic load changes in a 5G test bed through end-to-end RTT measurements.

Effect of Excitation Vibration at Different Frequencies on Pick Cutting

The pick vibration model was established and analyzed, and discussed the influence of vibration at different frequencies on the cutting load. Then a discrete element model of the interface coal seam is established in EDEM to analyze the change of cut load at different vibration frequencies. The conclusion shows that it is more suitable to apply high frequency vibration when the coal seam content is high, and it is more suitable to apply low frequency vibration when the rock layer content is more.

A multi-algorithm fusion model for predicting automotive fuel cell system demand power

The dynamic of a full-power fuel cell vehicle highly depends on the proton exchange membrane fuel cell power response. However, when frequent load changes in full-power fuel cell vehicle, proton exchange membrane fuel cell air shortage often occurs, leading to its poor power response. Predictive control of proton exchange membrane fuel cell is considered an effective solution, in which its demand power is a key input variable and must be predicted accurately. Proton exchange membrane fuel cell demand power has a strong nonlinear trend, which leads to large prediction errors. This paper proposes a hybrid prediction model that further extracts the data trendiness through the seasonal and trend decomposition using loess method and extracts the global features using the attention mechanism. The proposed prediction model is validated using real data under different driving conditions. Experimental results show that the proposed prediction model captures data characteristics and trendiness well and can better predict proton exchange membrane fuel cell demand power compared to other models. The proposed prediction model provides a prerequisite for improving the proton exchange membrane fuel cell power response and dynamics of full-power fuel cell vehicle.

Auxetic hybrid metamaterial with tunable elastic wave bandgap

Auxetic metamaterials have shown good stability and uniform deformation capabilities against influences (vibration, temperature change, load change), making them significant in maintaining and adjusting the bandgap of phonon crystals. The low-frequency and broadband are the important goals of phonon crystals. For most traditional re-entrant honeycomb structures (T-RHS), the bandgap range is narrow and tunability is poor. Here, an auxetic hybrid structure with tunable acoustic bandgap (AHS-T) consisting of periodic mass inclusions integrated with traditional re-entrant honeycomb and chiral hybrid is proposed. Aiming at investigating the tunability of the bandgap in the low-frequency range. Compared with T-RHS, the bandgap real-time adjustment and wider bandwidth of the AHS-T be realized during compression and tension. The numerical results show that the bandgap of the AHS-T can be flexibly tailored by reasonably adjusting the strain and geometrical configurations of AHS-T. The bandwidth of AHS-T can be increased to 87.1% when the bottom diameter Db and column height H of the scatterer are changed reasonably. Moreover, the deformation behavior of auxetic material has an auxiliary effect on expanding the bandwidth. Compared with the structure which is not subjected to load, the adjustable amplitude of the bandgap is 41%. The findings of this work provide a design idea for manipulating elastic waves in dynamic environment.

Strengthening of glass fiber sheets for multi-bolted pultruded GFRP connections: Effects of connection type and bolt-tightening force

This study investigated the effects of bolt-tightening forces on the connection strengths of non-strengthened and glass fiber sheet (GFS)-strengthened pultruded glass fiber reinforced polymer (PGFRP) connections through a series of experiments using double-lap and single-lap specimens. A total of 96 specimens (3 specimens for each parameter), half of which were non-strengthened, were tested under tensile loads and four bolt-tightening forces: 0, 5 N.m, 10 N.m, and 20 N.m. The (0°/90°)/chopped strand mat/(0°/90°) lamination was bonded to both PGFRP plates’ outside surfaces and improved the connection strengths. The results indicated that maximum failure loads increased with an increase in bolt-tightening forces. However, there were different trends in the maximum failure load changes, depending on the specimen type (non-strengthened or GFS-strengthened specimens; double-lap or single-lap specimens) and bolt-tightening forces. In addition, GFSs could effectively improve PGFRP’s connection strengths and ductility performances.

Investigation on dynamic mechanism of fault slip and casing deformation during multi-fracturing in shale gas wells

Fracturing horizontal well casing deformation has become very prominent, particularly in tectonic stress-concentrated shale gas fields, limiting the efficient development progress of shale gas. The main failure mode of casing shearing deformation had been attributed to fault slip caused by multi-fracturing. The current research did not provide a clear picture of the dynamic evolution relationship between hydraulic fracturing, fault slip, and casing deformation. In this paper, the dynamic model of fault slip induced by formation pressure change is established, incorporating the effects of stress drop, physical change of friction, and casing and cement-sheath resistance loads. The discontinuous displacement approach and explicit/implicit coupling iteration methods are used to reveal the relationships between the effective normal stress, shear stress, friction coefficient, and sliding velocity during the fault slip process. Furthermore, the microscopic process of casing deformation sheared by fault slip is investigated using static equilibrium theory, and a characterization method for determining the amount casing deformation caused by real-scale fault slip is proposed. The results show that three stages exist in the process of casing deformation sheared by fault slip, including trigger activation stage, accelerated slip stage, and deceleration slip stage. Fault slip is clearly influenced by fault strike. To reduce the amount of fault slip, the fault direction with the maximum in-situ stress should be avoided as much as possible. Serious casing deformation still occurs for large-scale activated faults even though the optimization measure of wellbore structure has been well taken. To fundamentally reduce the possibility of casing shear deformation, it is necessary to prevent fault slip through optimizing the design of hydraulic fracturing. This study lays the theoretical groundwork for the casing deformation control method in shale gas wells.

Analysis and Optimization of Operating Modes of Mini-CHP on Local Fuels in Conditions of Surplus Electric Power Capacities in the Unified Energy System of Belarus. Part 1

The paper presents the results of a study to determine the rational structure of mini-CHP (Cogeneration Heat and Power Plant) using local fuels types (LFT) for operation as part of the United Energy System (UES) of Belarus with a surplus of electricity generating capacity and dominance of imported types of energy resources (natural gas and nuclear fuel) in the fuel balance. When optimizing the operating modes of mini-CHPs using LFT and operating in parallel with the UES, which has a significant surplus of electricity generating capacity, it is necessary to separate options for existing stations and options for newly built ones. In the first case, due to the fact that the power of the equipment is known, it is advisable to consider two extreme options, i.e., the operation of the heating unit according to an electrical or thermal load schedule. In this case, in order to maintain the daily consumption traffic it is necessary to provide for the accumulation of thermal or electrical energy, respectively. In the case of new construction, the optimized parameter is the power of the generating equipment, so it is advisable to give preference to the option with the maximum number of hours of use of the rated power. In order to increase the economic attractiveness of mini-CHP, options for developing the structure of mini-CHP using LFT with the transition to multi-generation technologies and adaptation to the existing operating conditions of the UES of Belarus have been considered. The results of an analysis of commercially available technologies for storing excess electrical energy are presented in accordance with current and projected (until 2030) cost and operational indicators. For adapting mini-CHP to operate in the UES in conditions of a surplus of electrical power capacity, an electrical energy storage system using hydrogen as an intermediate energy carrier is of greatest interest. To utilize the excess electrical energy consumption from a mini-CHP with a heating ORC unit during the daily dips, a structural diagram configuration using an alkaline electrolysis module for hydrogen production is proposed. The efficiency of energy storage and use technology is considered depending on the specific energy intensity for various electrical energy storage technologies. The use of the two most energy-intensive energy storage technologies is proposed: accumulation based on electrochemical batte-ries and the “electricity-hydrogen” type. During the study, an analysis of the functioning of the ORC-installation Turboden 14 CHP ORC-installation operating as part of a mini-CHP using LFT was carried out. It was revealed that today the installation operates in a wide range of load changes (from 17 to 87 % of the rated electrical power), while the generation of electrical energy from thermal consumption varied in the range from 0.20 to 0.026 MW/MW. Due to the fact that the ORC installation under study is a component of the energy source with a high installed peak thermal power, in the current state there is no direct correlation between the outside air temperature and the generation power of the ORC installation. This circumstance indicates the need to continue the study of heat load trends to build functional models for short- and medium-term forecasting of heat load depending on the time of day and average hourly outside air temperature, which was implemented in the second part of the work.

A dSPACE-based implementation of ANFIS and predictive current control for a single phase boost power factor corrector

This paper presents an innovative control scheme designed to significantly enhance the power factor of AC/DC boost rectifiers by integrating an adaptive neuro-fuzzy inference system (ANFIS) with predictive current control. The innovative control strategy addresses key challenges in power quality and energy efficiency, demonstrating exceptional performance under diverse operating conditions. Through rigorous simulation, the proposed system achieves precise input current shaping, resulting in a remarkably low total harmonic distortion (THD) of 3.5%, which is well below the IEEE-519 standard threshold of 5%. Moreover, the power factor reaches an outstanding 0.990, indicating highly efficient energy utilization and near-unity power factor operation. To validate the theoretical findings, a 500 W laboratory prototype was implemented using the dSPACE ds1104 digital controller. Steady-state analysis reveals sinusoidal input currents with minimal THD and a power factor approaching unity, thereby enhancing grid stability and energy efficiency. Transient response tests further demonstrate the system’s robustness against load and voltage fluctuations, maintaining output voltage stability within an 18 V overshoot and a 20 V undershoot during load changes, and achieving rapid response times as low as 0.2 s. Comparative evaluations against conventional methods underscore the superiority of the proposed control strategy in terms of both performance and implementation simplicity. By harnessing the strengths of ANFIS-based voltage regulation and predictive current control, this scheme offers a robust solution to power quality issues in AC/DC boost rectifiers, promising substantial energy savings and improved grid stability. The results affirm the potential of the proposed system to set new benchmarks in power factor correction technology.

Novel feed additive delivers antimicrobial copper and influences fecal microbiota in pigs.

Dehydrated alginate beads formulated with copper were synthesized and tested as a feed additive to influence the microbiota in finishing pigs and potentially use them as a preharvest intervention to reduce fecal pathogen shedding. The efficacy of the copper beads was tested in vitro and in vivo. In vitro, Salmonella was significantly (P < 0.05) reduced when in contact with the copper beads solution for up to 6 h, with a 5.4 log CFU/mL reduction over the first hour. Chemical analysis of the soak solutions demonstrated the beads delivered their copper payload gradually over the same period the bactericidal effect was observed. For the in vivo experiments, pigs (n = 48) supplemented with the copper beads experienced significant shifts in their microbiota. Enterobacteriaceae (EB) increased by 1.07 log CFU/g (P < 0.05), while lactic acid bacteria (LAB) decreased by 1.22 log CFU/g (P < 0.05) during the treatment period. When beads were removed from the feed, EB and LAB concentrations returned to baseline, indicating copper beads led to measurable and significant changes in microbial loads. Fecal microbiome analysis conducted to explore additional changes by copper bead supplementation demonstrated that, at the phylum level, there was an increase in Firmicutes, Euryarchaeota, and Acidobacteriota, while at the genus level, an increase in Methanosphaera and Pseudomonas was observed. Measures of copper in swine feces showed values ~20 times higher in the treatment group than in the control group during the treatment period, suggesting that dehydrated alginate copper beads were effective in delivering antimicrobial copper to the animal hindgut.IMPORTANCECopper has long been known to have antimicrobial properties. However, when water-soluble salts are fed to livestock, the copper may rapidly dissolve in gastric contents and fail to reach the gut. Here, specially formulated copper beads are seamlessly incorporated into feed and allow copper to remain longer in the gastrointestinal tract of animals, reach deep into both the foregut and hindgut, and shift microbial populations. The technology delivers antimicrobial copper to the animal hindgut and potentially reduces pathogenic microorganisms before animal slaughter.

Spinal joint moment prediction following simulated breast surgery using a female whole-body musculoskeletal model

This study aimed to use a musculoskeletal model to predict changes in spinal moments following simulated breast surgery. A female full body musculoskeletal model with a fully articulated thoracolumbar spine and independent moveable breast segments was customised for this study. Key findings suggest that the simulated removal of breast tissue (750 g to 1501 g) can reduce the magnitude of lumbar spine extensor moments by >0.05 Nm/kg during walking and jogging. A customised female whole-body musculoskeletal model is capable of providing a first approximation of changes in spinal loading following simulated breast surgery.

Predicting hourly heating load in district heating system based on the hybrid Bi-directional long short-term memory and temporal convolutional network model

Accurate heating load prediction is essential to supply-demand collaboration in district heating systems and energy sustainability. With the development of the Internet of Things technology, massive monitoring data is collected that provides abundant data sources for the prediction models. However, the missing data from equipment anomalies, network transmissions and the complexity of heat load changing cause difficulty in realizing accurate heat load prediction. Therefore, the hybrid model based on bidirectional long short-term memory network and temporal convolutional network proposed in this paper to improve the accuracy of the heat load prediction from the aspects of reconstruction of missing values and extraction of complex features. The bidirectional long short-term memory algorithm imputes missing values based on bi-directional features of existing data and provides solid data foundation for subsequent training of predictive models. The temporal convolutional network achieves high-level feature extraction and parallel computation, which contributes to the effective modeling of complex changes in heat load and the realization of accurate heat load prediction. Comparative study was conducted with four heat exchange stations of actual environment to evaluate the performance of the prediction model. The results showed the mean absolute percentage error of the hybrid model decreased to 2.47% which is lower than the State-of-the-Art models, such as long short-term memory, temporal convolutional network, and support vector regression etc. The superior results further validated the feasibility of this hybrid model in heat load prediction.

The Effect of Antibacterial-Osteogenic Surface Modification on the Osseointegration of Titanium Implants: A Static and Dynamic Strategy.

Titanium (Ti) and its alloys are widely used biomaterials in bone repair. Although these biomaterials possess stable properties and good biocompatibility, the high elastic modulus and low surface activity of Ti implants have often been associated with infection, inflammation, and poor osteogenesis. Therefore, there is an urgent need to modify the surface of Ti implants, where changes in surface morphology or coatings loading can confer specific functions to help them adapt to the osseointegration formation phase and resist bacterial infection. This can further ensure a healthy microenvironment for bone regeneration as well as the promotion of immunomodulation, angiogenesis, and osteogenesis. Therefore, in this review, we evaluated various functional Ti implants after surface modification, both in terms of static modifications and dynamic response strategies, mainly focusing on the synergistic effects of antimicrobial activities and functionalized osteogenic. Finally, the current challenges and future perspectives are summarized to provide innovative and effective solutions for osseointegration and bone defect repair.

Impacts of dynamic stall on engineering model predictions of wind turbines loads under design load cases

The present work is aimed specifically at providing an order of estimate of the load changes due to the inclusion of unsteady aerodynamic effects. Two dynamic stall models are assessed: (1) the incompressible version of the Beddoes-Leishman model and (2) the newly developed IAG dynamic stall model. Two sets of attached flow constants are considered, based on the flat plate approximations according to Jones and the original constants adopted by the IAG model. On top of that, the influence of the impulsive contributions is also highlighted. This work is aimed at filling the gap of the state-of-the-art since at present there is no available study which compares the impacts of using the IAG model against the BL model in real design load case (DLC) scenarios required for wind turbine designs, considering it is very important to estimate loads changes depending on the engineering model being used. It will significantly influence the design of wind turbine structures, especially blades and the strength of the materials for the manufacturing process. Toward the end, providing a proper estimate into the load changes will greatly influence the cost required in blade design and manufacturing. The present study investigates the influence of dynamic stall modeling on the loads acting on wind turbines with various sizes, ranging from 2.5 MW to 8 MW of the rated power. In the studies, both onshore and offshore conditions are considered to obtain the full picture into the engineering modeling effects.

Novel control of PV-wind-battery powered standalone power supply system based LSTM based ANN

Integrated wind-photovoltaic (PV) based standalone electric power supply systems are widely used for various applications. A battery storage system is needed to provide continuous power supply to loads despite changes in loads, wind speed, and solar irradiance. Power quality is crucial in these hybrid systems, as the battery needs to charge from surplus power when generation exceeds the load and discharge to meet load demand. A bidirectional DC to DC converter is used to connect the battery to the network, and maximum power point tracking devices with proper algorithms are incorporated for optimal utilization of PV and wind turbines. Multiple PV systems and wind turbines are considered for proper power supply system ratings. Long short-term memory (LSTM) based artificial neural network (ANN) controllers are implemented for various control units in the hybrid standalone power system. The proposed control techniques improve power quality under various situations. Results are presented using MATLAB/Simulink to evaluate the performance of the proposed method.

Modeling and virtual simulation of the boost chopper by DCM using the optimal PIDF control

This work introduces an improved method for modeling and simulating the Boost Converter utilizing Duty Cycle Modulation (DCM) regulated by an optimum PIDF (Proportional-Integral-Derivative with Filter) regulator. We optimized the characteristic parameters of the PIDF regulator for a second-order system generated from its transfer function by using a mix of theoretical study and simulation using the Matlab/LQR tool. The conventional PID parameters in the time domain were converted into their corresponding LQR (Linear Quadratic Regulator) counterparts, allowing for the solution of the Riccati problem and the creation of an optimum state trajectory model. The results of analog virtual simulations done in a Multisim environment indicate that the system has improved dependability. It maintains a high level of accuracy in a stable condition, with no static error and a reaction time of 1.5 ms, without any overshooting. The effectiveness of the optimum PIDF control in regulating the DCM Boost Converter is highlighted by the system's strong ability to handle changes in load during transient states within a time frame of 300 ms. This study represents a substantial enhancement compared to conventional PID-based approaches, providing valuable knowledge about the possible uses in power electronics and control systems.

Analysis of power system frequency and active power based on wind-storage combined frequency modulation system

Abstract To solve the problem of frequency and active power regulation of power systems, this paper proposes a wind-storage combined frequency modulation strategy. The mathematical models of doubly-fed induction machines, pump turbines, and wind turbines are established. Based on wind power frequency modulation, the doubly-fed variable-speed pumped storage unit is added to establish a combined frequency modulation system, and a simulation model on Simulink to analyze the participation of different parts of the combined system in frequency modulation and the active power output of the unit when the load changes. The simulation results show that when the load increases or decreases, the addition of a doubly-fed variable speed pumped storage unit can effectively improve the frequency modulation performance of the system, reduce the fluctuation numbers and amplitude, and reduce the deviation after stabilization. By changing its active power output, a new balance of the system power can be reached, which is conducive to the secure and steady functioning of the power system.