Stability Of System Research Articles

The potential role of airborne and floating wind in the North Sea region

Abstract Novel wind technologies, in particular airborne wind energy (AWE) and floating offshore wind turbines, have the potential to unlock untapped wind resources and contribute to power system stability in unique ways. So far, the techno-economic potential of both technologies has only been investigated at a small scale, whereas the most significant benefits will likely play out on a system scale. Given the urgency of the energy transition, the possible contribution of these novel technologies should be addressed. Therefore, we investigate the main system-level trade-offs in integrating AWE systems and floating wind turbines into a highly renewable future energy system. To do so, we develop a modelling workflow that integrates wind resource assessment and future cost and performance estimations into a large-scale energy system model, which finds cost-optimal system designs that are operationally feasible with hourly temporal resolution across ten countries in the North Sea region. Acknowledging the uncertainty on AWE systems’ future costs and performance and floating wind turbines, we examine a broad range of cost and technology development scenarios and identify which insights are consistent across different possible futures. We find that onshore AWE outperforms conventional onshore wind regarding system-wide benefits due to higher wind resource availability and distinctive hourly generation profiles, which are sometimes complementary to conventional onshore turbines. The achievable power density per ground surface area is the main limiting factor in large-scale onshore AWE deployment. Offshore AWE, in contrast, provides system benefits similar to those of offshore wind alternatives. Therefore, deployment is primarily driven by cost competitiveness. Floating wind turbines achieve higher performance than conventional wind turbines, so they can cost more and remain competitive. AWE, in particular, might be able to play a significant role in a climate-neutral European energy supply and thus warrants further study.

Simulation study of the electrothermal field in a chloride electrolysis cell with 16 electrode pairs

AbstractThe spatial distribution of the electrothermal field within molten salt electrolytic cells significantly influences the efficiency of the electrolysis process, the quality of the end products, and the overall stability of the system. Enhancing the design of chloride electrolysis cells can lead to marked improvements in both process efficiency and system stability, thereby yielding increased economic benefits. This study introduces a design for a chloride electrolysis cell and examines the thermal budget under elevated electrical current intensities across 16 electrode pairs. It further analyzes the degree to which various parameters affect thermal equilibrium. The findings indicate that the electrolytic cell maintains a small thermal budget discrepancy at a current intensity of 124 kA and is less than 5%, with substantial heat dissipation observed at the surface of the top area of anode exposure and considerable energy consumption at both the anode and the electrolyte. Dimensionless treatment of the different parameterized simulation results has been conducted to develop a nondimensional equation, describing the thermal equilibrium conditions within the electrolytic cell. This foundational work paves the way for further investigations into the interactions between the electrothermal field and other physical fields, as well as for the optimization of the electrolytic cell's geometry and design.

The Impact of Hybrid Power Generations on a Power System's Voltage Stability

The Impact of Hybrid Power Generations on a Power System's Voltage Stability

Particle Swarm Optimization (PSO) And Evolutionary Programming (EP) Technique for Optimal Placement and Sizing DG for Minimizing Loss in IEEE-30 Bus System

In recent years, most growing nations worldwide have experienced an unavoidably rising demand for electricity, which may result in a dropping of the voltage profile and a reduction in system stability, both of which have the potential to overload the power generation system significantly. One of the ways to reduce loss system network in this study is by distributed generation (DG) allocation, which the DG optimal location and sizing are the two most significant considerations for integration of DG. Improper placement and DG sizing in the power system not only result in increased total power losses but also affect the electrical system’s capability to be function properly. This paper provides a comparative analysis of two meta- heuristic optimization techniques, that is, Particle Swarm Optimization (PSO) and Evolutionary Programming (EP), to examine the optimal placement and sizing of distributed-generation (DG) for photovoltaic systems with the aim of minimizing the losses in interconnected distributed generation, IEEE-30 bus system. The objective function of this study is minimization the power loss with considered some constraints which are voltage limits and DG sizing limits are being covers in this study. The optimization issue has been solved by working with MATLAB/m-files software. The outcomes derived from the simulation results in this study demonstrated that PSO performance of two units of DG is better compared to EP algorithm. The voltage profile was improved drastically, and the power loss was reduced as lowest as 17.4486MW in the first case, 17.4368MW in the second case, and 17.4179MW in the third case.

Enhanced Whale Optimization Algorithm for Fuzzy Proportional–Integral–Derivative Control Optimization in Unmanned Aerial Vehicles

The traditional PID controller in quadrotor UAVs has poor performance, a large overshoot, and a long adjustment time, which limit its stability and accuracy in practical applications. In order to solve this problem, an improved whale optimization fuzzy PID control strategy based on CRICLE chaos map initialization is proposed, and a detailed simulation analysis was carried out using MATLAB software (MATLAB R2022B). Firstly, to more realistically reflect quadrotor UAVs’ flight behavior, a dynamic simulation model was established, and the dynamics and kinematic characteristics of the aircraft were considered. Then, CRICLE chaotic mapping initialization was introduced to improve the global search ability of the whale optimization algorithm and to effectively initialize the parameters of the fuzzy PID controller. This improved initialization method helped to speed up the convergence process and improve the stability of the control system. In the simulation experiments, we compared the performance indicators of the improved CRICLE chaotic mapping initialization whale optimization fuzzy PID controller to the traditional PID and fuzzy PID controllers, including overshoot, adjustment time, etc. The results show that the proposed control strategy has better performance than the traditional PID and fuzzy PID controllers, significantly reduces overshoot, and achieves a significant improvement in adjustment time. Therefore, the improved CRICLE chaotic mapping initialization whale optimization fuzzy PID control strategy proposed in this study provides an effective solution for improving the performance of the quadrotor control system and has practical application potential.

Research on Optimization of Intelligent Driving Vehicle Path Tracking Control Strategy Based on Backpropagation Neural Network

To enhance path tracking precision in intelligent vehicles, this study proposes a lateral–longitudinal control strategy optimized with a Backpropagation (BP) neural network. The strategy employs the BP neural network to dynamically adjust prediction and control time-domain parameters within an established Model Predictive Control (MPC) framework, effectively computing real-time front-wheel steering angles for lateral control. Simultaneously, it integrates an incremental Proportional–Integral–Derivative (PID) approach with a meticulously designed acceleration–deceleration strategy for accurate and stable longitudinal speed tracking. The strategy’s efficiency and superior performance are validated through a comprehensive CarSim(2020)/Simulink(2020b) simulation, demonstrating that the proposed controller adeptly modulates control parameters to adapt to various road adhesion coefficients and vehicle speeds. This adaptability significantly improves tracking and driving dynamics, thereby enhancing accuracy, safety, stability, and real-time responsiveness in the intelligent vehicle tracking control system.

Combined Control Strategy of Wind Storage Based on Power Electronic Transformer

Because of the inherent randomness and instability of the wind power generation system, the energy storage device and power electronic transformer are introduced into the wind power generation system to restrain the fluctuation of DC bus voltage and power junction, and improve the stability of the wind power generation system. This paper first introduces the basic characteristics of wind turbines and the basic idea of maximum wind energy capture and puts forward the control strategy of wind turbine side converter and grid side converter. Then the topological structure, mathematical model, and working principle of the power electronic transformer are described, and the control strategy of the power electronic transformer is proposed. Finally, the power electronic transformer is applied to the grid-connected wind storage system, and the grid-connected wind storage system model is built in MATLAB/Simulink platform, and the grid-connected control strategy under wind power fluctuation is simulated and verified. The simulation results show that the topology structure of the grid-connected wind storage system and the effectiveness of the grid-connected control strategy are proposed.

Analysis of friction-induced vibration and wear characteristics during high-speed train friction braking process

This study explored the evolution of friction-induced vibration (FIV) and wear in high-speed train friction braking through experiments, theoretical analysis, and numerical simulation. Experimental tests revealed that vibration behavior transitions from high-frequency modes at high speeds to low-frequency stick-slip at lower speeds. Theoretical analysis indicated that brake disc speed, coefficient of friction (COF), and contact stiffness affect system stability. Specifically, the system experiences high-frequency vibrations at high speeds due to mode coupling, and the friction block surface primarily undergoes abrasive wear mechanisms. At lower speeds, the system demonstrates low-frequency stick-slip vibrations induced by the combined effects of mode coupling and negative friction velocity slope (NFVS) characteristics, and the friction block surface mainly experiences adhesive wear mechanisms.

Disturbance rejection design for Gaussian process-based model predictive control using extended state observer

Gaussian process (GP) regression has gained significant popularity in machine learning because it has the intrinsic capability to capture uncertainty in function prediction and requires a limited number of hyperparameters to be optimized. In this study, a Gaussian process model predictive control (GPMPC) algorithm is proposed to model the unknown dynamics of the process using Gaussian process regression. The GPMPC incorporates the expected variance of the GP model to account for the model's uncertainty and to achieve prudent control. Meanwhile, the extended state observer (ESO) is introduced for the GPMPC, which can estimate the unmodeled dynamics and unknown disturbance. With the designed feedforward gain, the proposed extended state observer-based GPMPC (GPMPC-ESO) method can achieve offset-free performance. Theoretical analysis is conducted to evaluate the stability and disturbance rejection performance of the control system. Finally, the algorithms are validated by simulation in continuous stirred tank reactor (CSTR) process control.

Effect of Na+ migration and the component proximity on direct conversion of aromatics into aromatics over Fe-based zeolite bifunctional catalysts

Direct conversion of syngas into aromatics (STA) via Fischer-Tropsch (F-T) synthesis, using Fe-based zeolite bifunctional catalysts, has recently become a topic of great interest. The catalytic performance of the Fe-based zeolite bifunctional catalyst is influenced by the component proximity in the STA reaction, in addition to their physicochemical properties. However, the mechanism by which the component proximity affects the STA performance is still unclear. Herein, we investigate the effect of Na+ migration and the component proximity on the F-T reactivity, the aromatic distribution, and catalyst stability in a Fe-based ZSM-5 catalyst system. The correlation between the proximity of two components, the migration of alkali-metal promoters, the evolution of the Fe-based active phase, and the coke on the zeolite is analyzed using XRD, XPS, FT-IR, TG, Mössbauer spectroscopy techniques. The findings indicate that when the components are closer to each other, it encourages the formation of iron carbides and inhibits the coke deposition on the zeolite. However, the migration of alkali metals and the acidic environment of zeolite can decrease the catalyst’s stability and F-T reactivity. Moreover, by improving the hydrophobic nature of the zeolite, we can prevent the transfer of alkali-metal promoters from the Fe-based component to zeolite. This enhances the stability of Fe-based ZSM-5 catalysts in the STA reaction, suggesting a new approach to improve their STA performance.

Trajectory Tracking Control of Mobile Manipulator Based on Improved Sliding Mode Control Algorithm

Research on trajectory tracking control for climbing welding robots holds significant importance in the field of automated welding. However, existing trajectory tracking methods suffer from issues such as jitter and slow speed. In this paper, an improved sliding mode control strategy is proposed based on the self-designed wall-climbing welding mobile manipulator. Firstly, a new adaptive sliding mode control strategy is proposed for the mobile platform based on the kinematic model. By introducing a new approach law, the controller is designed when the distance between the center of mass is unknown. Secondly, regarding the manipulator, we analyze simplified dynamic equations, extract uncertain components, and utilize a CNN for compensation. This compensation strategy is integrated into the sliding mode control law, achieving precise control over the manipulator and effectively resolving issues like slow tracking speeds, large errors, and chattering. The stability of the robot control system is proved by the Lyapunov function. Through simulation analysis and experimental validation, the proposed control method is confirmed to be feasible and superior.

Photovoltaic power prediction system based on multi-stage data processing strategy and improved optimizer

Building a reliable forecasting system can quantify future fluctuations in short-term photovoltaic output power, which is essential for optimizing grid configuration and reducing operating costs. However, most of the existing studies only use denoising technology to preprocess data, which results in the elimination of some key information. And the traditional optimizer cannot meet the parameter optimization requirements of the prediction system because of its limited search capacity and search space. Based on the above problems, a combined system based on multi-stage data processing strategy and improved optimizer is proposed, which solves the tradeoff problem between prediction accuracy and stability. Firstly, the multi-stage processing strategy effectively improves the signal-to-noise ratio and preserves more implicit information. Then, the optimal sub-model determination strategy extends the structural framework of model selection and improves the flexibility of the prediction system. Finally, three improved strategies are introduced to improve the optimization ability and convergence speed of the optimizer, which magnifies the advantages of the prediction system. An empirical study using Safi-Morocco data shows that the symmetric mean absolute percentage errors of three photovoltaic modules are 4.777%, 4.755% and 6.033%, respectively, which implies that the system can not only achieve accurate prediction of photovoltaic output power, but also help to balance supply and demand and improve the overall sustainability and stability of the grid-connected power system.

Correction Control Model of L-Index Based on VSC-OPF and BLS Method

With the advancement of artificial intelligence (AI) technology, the real-time measurement and control technology of power systems has also progressed. This paper proposes a correction control model for L-indexes based on voltage stability constrained optimal power flow (VSC-OPF) and a broad learning system (BLS) (BLS-VSC-OPF). This model aims to quickly assess the system’s voltage stability and accurately correct the operation mode when the voltage stability indexes are out of the security range. Firstly, the BLS is used to predict the L-index and to analyze the voltage stability of the power system. Secondly, the approximate first-order sensitivity of the L-index is calculated by the combination of the BLS and the perturbation method. This method solves the problem of the complex sensitivity derivation process in the modeling process of the VSC-OPF model. Meanwhile, when the L-index exceeds the threshold, the BLS and VSC-OPF models are combined to correct this operation mode. The feasibility of the proposed method is verified by the simulation of IEEE-30, IEEE-118, and 1047 bus systems. Finally, the BLS-VSC-OPF model is compared with the linear programming correction model based on BLS (BLS-LPC). The results show that the BLS-VSC-OPF model provides a better correction and control performance.

USV Trajectory Tracking Control Based on Receding Horizon Reinforcement Learning.

We present a novel approach for achieving high-precision trajectory tracking control in an unmanned surface vehicle (USV) through utilization of receding horizon reinforcement learning (RHRL). The control architecture for the USV involves a composite of feedforward and feedback components. The feedforward control component is derived directly from the curvature of the reference path and the dynamic model. Feedback control is acquired through application of the RHRL algorithm, effectively addressing the problem of achieving optimal tracking control. The methodology introduced in this paper synergizes with the rolling time domain optimization mechanism, converting the perpetual time domain optimal control predicament into a succession of finite time domain control problems amenable to resolution. In contrast to Lyapunov model predictive control (LMPC) and sliding mode control (SMC), our proposed method employs the RHRL controller, which yields an explicit state feedback control law. This characteristic endows the controller with the dual capabilities of direct offline and online learning deployment. Within each prediction time domain, we employ a time-independent executive-evaluator network structure to glean insights into the optimal value function and control strategy. Furthermore, we substantiate the convergence of the RHRL algorithm in each prediction time domain through rigorous theoretical proof, with concurrent analysis to verify the stability of the closed-loop system. To conclude, USV trajectory control tests are carried out within a simulated environment.

Optimizing Critical Overloaded Power Transmission Lines with a Novel Unified SVC Deployment Approach Based on FVSI Analysis

This paper proposes a novel methodology to improve stability in a transmission system under critical conditions of operation when additional loads that take the system to the verge of stability are placed in weak bus bars according to the fast voltage stability index (FVSI). This paper employs the Newton–Raphson method to calculate power flows accurately and, based on that information, correctly calculate the FVSI for every transmission line. First, the weakest transmission line is identified by considering N−1 contingencies for the disconnection of transmission lines, and then all weak nodes associated with this transmission line are identified. Following this, critical scenarios generated by stochastically placed loads that will take the system to the verge of instability will be placed on the identified weak nodes. Then, the methodology will optimally size and place a single static VAR compensator SVC in the system to take the transmission system to the conditions before the additional loads are connected. Finally, the methodology will be validated by testing the system for critical contingencies when any transmission line associated with the weak nodes is disconnected. As a result, this paper’s methodology found a single SVC that will improve the system’s stability and voltage profiles to similar values when the additional loads are not connected and even before contingencies occur. The methodology is validated on three transmission systems: IEEE 14, 30, and 118 bus bars.

Insight into the mechanism of chlorinated nitroaromatic compounds anaerobic reduction with mackinawite (FeS) nanoparticles

Anaerobic biotechnology for wastewaters treatment can nowadays be considered as state of the art methods. Nonetheless, this technology exhibits certain inherent limitations when employed for industrial wastewater treatment, encompassing elevated substrate consumption, diminished electron transfer efficiency, and compromised system stability. To address the above issues, increasing interest is being given to the potential of using conductive non-biological materials, e,g., iron sulfide (FeS), as a readily accessible electron donor and electron shuttle in the biological decontamination process. In this study, Mackinawite nanoparticles (FeS NPs) were studied for their ability to serve as electron donors for p-chloronitrobenzene (p-CNB) anaerobic reduction within a coupled system. This coupled system achieved an impressive p-CNB removal efficiency of 78.3 ± 2.9% at a FeS NPs dosage of 1 mg/L, surpassing the efficiencies of 62.1 ± 1.5% of abiotic and 30.6 ± 1.6% of biotic control systems, respectively. Notably, the coupled system exhibited exclusive formation of aniline (AN), indicating the partial dechlorination of p-CNB. The improvements observed in the coupled system were attributed to the increased activity in the electron transport system (ETS), which enhanced the sludge conductivity and nitroaromatic reductases activity. The analysis of equivalent electron donors confirmed that the S2- ions dominated the anaerobic reduction of p-CNB in the coupled system. However, the anaerobic reduction of p-CNB would be adversely inhibited when the FeS NPs dosage exceeded 5 g/L. In a continuous operation, the p-CNB concentration and HRT were optimized as 125 mg/L and 40 h, respectively, resulting in an outstanding p-CNB removal efficiency exceeding 94.0% after 160 days. During the anaerobic reduction process, as contributed by the predominant bacterium of Thiobacillus with a 6.6% relative abundance, a mass of p-chloroaniline (p-CAN) and AN were generated. Additionally, Desulfomonile was emerged with abundances ranging from 0.3 to 0.7%, which was also beneficial for the reduction of p-CNB to AN. The long-term stable performance of the coupled system highlighted that anaerobic technology mediated by FeS NPs has a promising potential for the treatment of wastewater containing chlorinated nitroaromatic compounds, especially without the aid of organic co-substrates.

Ultrasound-assisted preparation of crumb rubber modified asphalt: Characterization and molecular dynamics simulation

The traditional method of crumb rubber modified asphalt (CRMA) preparation can improve the stability but is not conducive to cleaner production. From the perspective of process optimization, ultrasound is introduced into the crumb rubber modified asphalt preparation process, and the high temperature, high pressure and high energy accompanied by the cavitation effect are used to generate free radical triggering chemical effects at the two-phase interface between crumb rubber and asphalt. In this paper, the influence of ultrasound on the compatibility and stability of crumb rubber modified asphalt system was evaluated by combining experiment and molecular dynamics simulation. An experimental platform for ultrasound-assisted preparation of crumb rubber modified asphalt was established. The effects of ultrasonic on the physical properties of asphalt and crumb rubber modified asphalt were studied through Brookfield viscosity test, thin film oven aging test and Fourier infrared spectroscopy. The base, aged, and ultrasonically treated asphalt samples were simulated using molecular dynamics, and various parameters such as Cohesive Energy Density (CED), Mean Square Displacement (MSD), and Free Volume Fraction (FFV) of asphalt and its components were calculated and analyzed. The results showed that under the ultrasonic-assisted preparation, the agglomeration phenomenon of rubber particles is weakened, the particle size is reduced, the penetration degree is reduced, and the compatibility between rubber and asphalt is improved. Under the action of ultrasonic, the MSD and diffusion coefficient of crumb rubber modified asphalt are much higher than other kinds of asphalt, the dipole moment is increased, and the molecular motion range is wider. This indicates that the diffusion ability of crumb rubber modified asphalt is significantly enhanced under the external force of ultrasonic simulation. The molecular bonds of crumb rubber modified asphalt changes greatly, the energy decreases obviously, and the system stability increases. In conclusion, ultrasonic action on crumb rubber modified asphalt preparation is a green and effective way to improve system stability and compatibility.

Financial security of Arab countries: analysis of some aspects

Issues of ensuring the financial security of the country have always played an important role not only in times of crises but also in conditions of relatively stable functioning of the economy and financial system. Financial security, along with food and energy security, is part of national economic security and plays a leading role at the macro and micro economic levels. It is especially necessary to note the rapid development of digitalization processes which directly affect the stability of the financial system and its security. The financial systems of Arab countries, being included in the global financial system, are directly or indirectly exposed to almost all possible risks that arise and evolve in the global financial markets and in the global economy. Ensuring financial security in the countries of the Middle East and North Africa region is one of the top priorities for the leadership of these countries. These tasks boil down to, among other things, reducing sovereign risk ensuring unity in regulatory approaches to ensuring cross–border transactions, transparency in trade finance transactions taking into account the imposition of sanctions against some countries, and ensuring cybersecurity in the context of digitalization of financial processes remains an important aspect. This article examined and analyzed some of the aspects of the financial security of Arab countries including taking into account the inclusion of innovative processes in world practice, and there are also presented the problems of the countries of the Middle East and North Africa region which contribute to an increase in the likelihood of imbalance in processes to ensure the financial security of the region generally.

Nonlinear disturbance observer-based geometric attitude fault-tolerant control of quadrotors

This paper is concerned with nonlinear disturbance observer (DO)-based geometric attitude fault-tolerant control (FTC) problem of quadrotor unmanned aerial vehicles (UAVs) subject to system uncertainties, exogenous disturbances, and actuator faults. A disturbance observer-based control (DOBC) framework is devised to tackle the difficulties caused by system uncertainties and external disturbances. The FTC is proposed to cope with the occurrence of actuator faults which can be modelled as a constant loss of effectiveness. The proposed design scheme can provide an effective way to analyse the stability of the closed-loop system, which can ensure the asymptotical convergence of the error. The other method considers actuator failures as part of the lumped disturbance, and the attitude tracking problem of quadrotors concerning the lumped disturbance is solved by the DO-based control method, which can ensure the exponential convergence of the error. The numerical simulations are performed to illustrate the effectiveness of the design techniques.

Financial security of Arab countries: analysis of some aspects

Issues of ensuring the financial security of the country have always played an important role not only in times of crises but also in conditions of relatively stable functioning of the economy and financial system. Financial security, along with food and energy security, is part of national economic security and plays a leading role at the macro and micro economic levels. It is especially necessary to note the rapid development of digitalization processes which directly affect the stability of the financial system and its security. The financial systems of Arab countries, being included in the global financial system, are directly or indirectly exposed to almost all possible risks that arise and evolve in the global financial markets and in the global economy. Ensuring financial security in the countries of the Middle East and North Africa region is one of the top priorities for the leadership of these countries. These tasks boil down to, among other things, reducing sovereign risk ensuring unity in regulatory approaches to ensuring cross–border transactions, transparency in trade finance transactions taking into account the imposition of sanctions against some countries, and ensuring cybersecurity in the context of digitalization of financial processes remains an important aspect. This article examined and analyzed some of the aspects of the financial security of Arab countries including taking into account the inclusion of innovative processes in world practice, and there are also presented the problems of the countries of the Middle East and North Africa region which contribute to an increase in the likelihood of imbalance in processes to ensure the financial security of the region generally.