Enhance System Performance Research Articles

Enhancing cross-subject transfer performance for SSVEP identification using small data-based transferability evaluation

Cross-subject steady-state visual evoked potential-based brain-computer interfaces (SSVEP-BCIs) have attracted increasing attention in recent years due to their potential to reduce calibration efforts and improve usability. This study proposed an efficient cross-subject transfer method for SSVEP-BCI, which significantly reduced the calibration effort and enhanced system performance. By employing a minimal dataset obtained from the target subject, specifically, a single trial for each frequency, we calculated the similarity between the SSVEPs of the target subject and the source subjects. Based on the similarities, a transferability evaluation model was constructed, which was then used to assign weights to the source subjects. The features calculated from the source subjects were then weighted and summed to obtain the frequency recognition results. The proposed cross-subject transfer method was evaluated in two pipelines based on the ensemble task-related component analysis (eTRCA) and task-discriminant component analysis (TDCA), respectively. The proposed method in eTRCA-pipeline initially achieving accuracies of 96.98 ± 3.66 % and 88.97 ± 14.66 % in our dataset and the Benchmark dataset, respectively, at a data length of 1 s. After fusing the features of eTRCA with those of the extended canonical correlation analysis (eCCA), the method exhibited enhanced performance, elevating accuracies to 98.23 ± 2.68 % and 92.83 ± 10.75 %. Similarly, in TDCA-pipeline, accuracies initially reached 97.47 ± 3.88 % and 93.53 ± 10.22 % in our dataset and the Benchmark dataset, respectively, and after fusing TDCA features with eCCA features, they remarkably increased to 98.13 ± 2.89 % and 95.00 ± 8.43 %, respectively. This study offers a promising solution for the fast and effective calibration of SSVEP-BCI, paving the way for more practical and accessible BCI systems.

Numerical simulation of heat pipe solar system combined with finned thermal storage unit incorporating mixture of nanoparticles and paraffin

The core aim of this investigation is to simulate the melting of paraffin within a solar heat pipe unit combined with thermal storage unit, while taking into account the presence of metallic fins. To enhance system performance, Multi-Walled Carbon Nanotube (MWCNT) nanoparticles were blended into the paraffin material (RT82) using a homogeneous mixture approximation. The temperatures of the heat pipe and inner walls were derived from previous experimental research. Three distinct fin arrangements were utilized, and simulations were carried out employing numerical method. Validation procedures were undertaken to verify the accuracy of the modeling and the applied approximations, relying on both prior experimental data and numerical publications. The investigation presents data on the liquid fraction (LF), temperature (T), and stream function for diverse configurations. This holistic approach seeks to deepen comprehension of the interactions among these elements within a solar collector system, offering vital insights for performance optimization. The outcomes demonstrated a notable improvement in LF, increasing by roughly 15.15% at t = 1200s with the integration of MWCNT. Furthermore, with the passage of time from 400 s to 1200s, the incorporation of additives results in a notable rise in LF and T, demonstrating enhancements of approximately 97.74% and 130.8% correspondingly. Notably, the utilization of fins positioned at a 90o angle expedites the melting process, yielding a 38.24% LF increase compared to the base case at t = 1200s. Moreover, the impact of fins demonstrates a 3.32% increase over time. In essence, these results emphasize the effectiveness of incorporating MWCNTs and fine-tuning fin configurations to accelerate the melting process, offering valuable insights for the progress of solar thermal systems.

Low mutual-coupling MIMO antenna using dielectric resonators

This paper presents a design for a low-coupling multiple-input multiple-output (MIMO) antenna with two antenna elements. There is a dielectric resonator centrally and four inverted-F slots around on each element. This dielectric resonator consists of a dielectric block with an I-shaped metal pattern and is encircled by a metal ring with air holes. The use of inverted-F slots and the dielectric resonator effectively reduces the mutual coupling between the two antenna elements. Simulation and measurement results indicate that the designed MIMO antenna achieves a high level of isolation, maintains a low envelope correlation coefficient, and possesses a relatively high overall active reflection coefficient efficiency within the bandwidth of 6.41 GHz–6.62 GHz. These characteristics make the MIMO antenna perform exceptionally well in enhancing communication system performance, particularly in terms of signal quality, channel capacity, and system efficiency.

Performance enhancement of a three-phase grid-connected PV inverter system using fractional-order integral sliding mode controls

Grid-integrated photovoltaic (PV) systems hold significant promise for sustainable energy production. However, these systems often struggle with maintaining energy quality and stability in the face of fluctuating conditions. To address these challenges, this study proposes the use of fractional-order integral sliding mode control (FO-ISMC) for grid-connected PV systems. The system comprises solar panel arrays, a DC/DC boost converter with its controller, and a three-phase inverter integrated into the utility grid. The primary goals of this study are to maximize power extraction from the PV system and to regulate system currents, thereby improving effectiveness and power quality. The proposed method is further refined using the particle swarm optimization (PSO) algorithm to fine-tune parameter settings. By optimizing the command gains of the FOI-SMC, the PSO algorithm enhances system performance and stability. Leveraging fractional-order and integral terms provides the control signal with additional degrees of freedom, enhancing system performance in the presence of internal and external disturbances. Simulation results demonstrate the effectiveness of the proposed controller compared to the classical controller, where in the case of Irradiation taking the value of 500 W/m2, the proposed strategy reduced the values of constant voltage, active power, and reactive power by percentages estimated at 88.18%, 90%, and 70%, respectively, compared to the traditional strategy. Also, the overshoot value of active power was reduced in all completed cases compared to the traditional strategy by percentages estimated at 53.57%, 66.66%, and 65%, respectively. The proposed strategy reduced the response time of reactive power in all cases compared to the traditional strategy by percentages estimated at 58.59%, 28.80%, and 75%, respectively. These ratios show the high performance of the proposed control in improving the characteristics of the studied system compared to traditional control based on PI control.

Research Progress on Nonlinear Modeling of Electro-Hydraulic Servo Systems and Innovative Applications of Control Strategies

Abstract: In various specific application domains, electro-hydraulic servo systems are widely adopted due to their high power-to-volume ratio, superior dynamic response performance, and extremely high control accuracy. However, the inevitable presence of nonlinear factors in the system poses a series of challenges for precise mathematical modeling and the design and application of different forms of control strategies. This article aims to explore how various control strategies are specifically implemented to address the nonlinear characteristics of electro-hydraulic servo systems, building upon the research progress in modeling these systems considering nonlinear factors. Subsequently, the article summarizes their innovative applications in electro-hydraulic servo systems. Simultaneously, relevant patents and technologies were reviewed and summarized. The paper provides a detailed comparison and analysis of various nonlinear modeling methods, with a particular focus on the significance of neural networks and fuzzy logic control in enhancing the performance of electro-hydraulic servo systems. The article reveals significant advancements in modern control strategies in dealing with uncertainties and disturbances within the system, offering new perspectives and ideas for improving system efficiency and achieving energy resource conservation with technological progress. The review provides a series of practical recommendations aimed at optimizing the performance of electro-hydraulic servo systems. Despite progress in multiple research endeavors, future research should focus on further enhancing system performance and applying these strategies to a broader range of scenarios.

Parametric analysis for nanolubricant in vapor compression refrigeration cycle

With the escalating global energy crisis and the consequential surge in energy consumption, particularly attributed to air conditioning (AC) systems in buildings, there arises a pressing need for sustainable solutions to mitigate this escalating demand. Vapor compression refrigeration (VCR) cycles, ubiquitous across residential, commercial, and industrial sectors, represent a significant portion of global electricity consumption, exceeding 10%. This demand is further exacerbated in regions characterized by hot climates. Consequently, there is a critical imperative to address the environmental impact of these systems, particularly in terms of reducing their Global Warming Potential (GWP). In response to this imperative, this study aims to develop a comprehensive numerical model for VCR systems, focusing on the implementation of nanolubricants. The primary objective is to assess the impact of integrating Al2O3 nanoparticles into the lubricating oil (referred to as nanolubricant) on the performance of the VCR cycle. The scope of the study encompasses the investigation of nanolubricants within refrigeration systems, aiming to enhance their efficiency and environmental sustainability. Utilizing the Engineering Equation Solver (EES), a numerical model of a VCR cycle utilizing R-410A refrigerant is developed. The model specifically emphasizes the compressor component, which is flooded with a polyolester (POE) oil base. The study explores various parameters, including ambient conditions, refrigerant-to-oil dissolving ratio, and mass concentration of nanoparticles, to evaluate their influence on system performance. The results indicate a significant enhancement in performance when flooding the base oil before introducing Al2O3 nanoparticles, with further improvements observed upon nanoparticle integration. Specifically, the coefficient of performance (COP) of the VCR system exhibits a notable increase compared to the base case configuration. Additionally, the adoption of eco-friendly refrigerants, such as R-32, demonstrates promising COP values following nanoparticle implementation by up to 4%. Moreover, the study reveals a reduction in compressor discharge temperature by up to 20% with higher oil mass concentrations during nanolubricant implementation, indicating enhanced durability and longevity of the VCR system’s compressor. These findings underscore the potential of nanolubricants to contribute to both the efficiency and environmental sustainability of refrigeration systems. In conclusion, the findings of this study offer valuable insights into the utilization of nanolubricants in VCR cycles, highlighting their potential to enhance system performance and mitigate environmental impact. These advancements hold promise for the development of more sustainable refrigeration technologies in the face of mounting energy challenges.

IoT based weather monitoring system for temperature, humidity, rainfall and seismic detection in real time

This paper presents the design and implementation of an IoT-based weather monitoring system enhanced with seismic detection capabilities, employing Node MCU microcontroller and the Blynk mobile application platform. The system incorporates various sensors including a rain sensor, Light light-dependent resistor (LDR), a DHT11 sensor for temperature and humidity measurement, and an accelerometer (MPU6050) for earthquake detection. The hardware components are interconnected with the Node MCU microcontroller, facilitating real-time data acquisition from the sensors. Programming of the Node MCU is conducted using the Arduino IDE, enabling data transmission to the Blynk app via Wi-Fi connectivity. The Blynk app serves as the user interface, allowing seamless visualization and monitoring of weather parameters and seismic activity on smartphones. Key functionalities of the system include periodic data collection from sensors, transmission of sensor data to the Blynk server, and updating of graphical representations in the Blynk app interface. The accelerometer sensor is utilized to detect changes in acceleration, indicative of seismic disturbances. Threshold values are defined to trigger alerts within the Blynk app in the event of potential seismic activity. The implementation undergoes rigorous testing to ensure accuracy, reliability, and responsiveness under diverse environmental conditions. Considerations such as network stability, power efficiency, and data security are addressed to enhance system performance and longevity. The system demonstrates promising capabilities for real-time weather monitoring and seismic event detection, offering valuable insights for disaster preparedness and environmental analysis. IoT-based weather monitoring system integrated with seismic detection provides an effective solution for comprehensive environmental monitoring, leveraging the power of IoT technology and mobile applications for enhanced data accessibility and analysis. Further advancements and optimizations can be explored to extend the functionality and scalability of the system for broader applications in environmental science and disaster management.

Performance improvement study of nonlinear bionic suspension based on inerter and on–off control strategy

How to improve the dynamic performance of nonlinear suspension systems is a focus of attention. The combination of inerter and on–off control strategy can effectively improve the dynamic performance of linear suspension systems, but it will also bring some adverse effects. This paper puts forward a nonlinear suspension system performance enhancement scheme based on semi-active on–off control strategies of inerter to eliminate the adverse effects of the introduction of the inerter and to enhance the dynamic performance of nonlinear suspension systems. This paper takes the nonlinear double-diamond bionic kangaroo leg suspension system as an example and adopts the above scheme to carry out dynamic modeling, time–frequency domain dynamic characteristics analysis, and control characteristics research. The results show that the dynamic performance of the proposed nonlinear suspension system with passive inerter is partially better than that of the original suspension system in time–frequency domain, while the overall dynamic performance of the proposed nonlinear suspension system with semi-active inerter is better than that of the original suspension system. The proposed nonlinear suspension system with semi-active inerter shows good stability and adaptability under different working conditions, and the proposed control strategies can eliminate the adverse effects of passive inerter. The above results indicate the correctness of the proposed scheme and the effectiveness of the control strategies.

Downlink Learning-aided Precoding for Cell-Free networks Specially D esigned for beyond 5G Communication System

Objectives: With increase in number of access points in Cell-Free Massive Multiple Input Multiple Output (CFMM) system, spatial complexity of calculating precoding vector increases with traditional precoding schemes. So, to reduce computational complexity, network cost, and run time, a new deep learning -aided precoder is specially designed for CFMM system. The performance of downlink (DL) Cell-Free Massive Multiple Input Multiple Output (CFMM) system operating under Rayleigh fading channel model is analyze using new deep learning-based precoding scheme. Methods: We introduce new deep learning-aided precoder and an improved version of basic scalable pilot assignment algorithm which enhances system performance. We derive closed- form expression for average DL spectral efficiency (SE) for the proposed scheme, which is then compared with Minimum Mean Square Error Successive Interference Cancellation (MMSESIC), Regularized Zero Forcing (RZF), Least Square (LS) and Maximum Ratio (MR) combining techniques. We analyze the proposed scheme with perfect channel state information (CSI), instantaneous CSI, coherent transmission, non-coherent transmission, different pilot configuration. Findings: The spectral efficiency obtained with CFMM-MMSESIC and the proposed scheme is 3 bits/s/Hz, and 2.5bits/s/Hz respectively, which clearly indicates the difference of 20 % only. So, the proposed scheme gives near optimal results, and we can use simple linear combining techniques instead of complex non-linear combining techniques. Also, the proposed scheme with coherent data transmission gives performance curve, which is very close to MMSESIC scheme as desired. The performance of the proposed system is improved by reducing run time and computational complexity as compared to conventional linear precoding schemes. Novelty: The proposed precoder improves performance by reducing run time and computational complexity. Advanced pilot assignment algorithm enhances performance by reducing pilot contamination. Keywords: Cell-Free Massive Multiple Input Multiple Output, Pilot Contamination, Precoding, Minimum Mean Square Error Successive Interference Cancellation, Maximum Ratio, Regularized Zero Forcing (RZF), Least Square (LS)

Preliminary insights on the development of a continuous-flow solar system for the photocatalytic degradation of contaminants of emerging concern in water.

The ubiquity and impact of pharmaceuticals and pesticides, as well as their residues in environmental compartments, particularly in water, have raised human and environmental health concerns. This emphasizes the need of developing sustainable methods for their removal. Solar-driven photocatalytic degradation has emerged as a promising approach for the chemical decontamination of water, sparking intensive scientific research in this field. Advancements in photocatalytic materials have driven the need for solar reactors that efficiently integrate photocatalysts for real-world water treatment. This study reports preliminary results from the development and evaluation of a solar system for TiO2-based photocatalytic degradation of intermittently flowing water contaminated with doxycycline (DXC), sulfamethoxazole (SMX), dexamethasone (DXM), and carbendazim (CBZ). The system consisted of a Fresnel-type UV solar concentrator that focused on the opening and focal point of a parabolic trough concentrator, within which tubular quartz glass reactors were fixed. Concentric springs coated with TiO2, arranged one inside the other, were fixed inside the quartz reactors. The reactors are connected to a raw water tank at the inlet and a check valve at the outlet. Rotating wheels at the collector base enable solar tracking in two axes. The substances (SMX, DXC, and CBZ) were dissolved in dechlorinated tap water at a concentration of 1.0mg/L, except DXM (0.8mg/L). The water underwent sequential batch (~ 3 L each, without recirculation) processing with retention times of 15, 30, 60, 90, and 120min. After 15min, the degradation rates were as follows: DXC 87%, SMX 35.5%, DXM 32%, and CBZ 31.8%. The system processed 101 L of water daily, simultaneously removing 870, 355, 256, and 318µg/L of DXC, SMX, DXM, and CBZ, respectively, showcasing its potential for real-world chemical water decontamination application. Further enhancements that enable continuous-flow operation and integrate highly effective adsorbents and photocatalytic materials can significantly enhance system performance.

Dynamic performance enhancement of nonlinear AWS wave energy systems based on optimal super-twisting control strategy

This paper presents a Super-Twisting Algorithm (STA) sliding mode control technique as an alternative to the conventional Proportional-Integral (PI) control system. This application is specifically in the context of a nonlinear Archimedes Wave Swing (AWS) device, which functions as a wave energy converter system (WECS) connected to the power grid. The main goal is dynamic performance enhancement of such wave energy systems under network disturbances. Two STA controllers areessential for the rectifier control system in the grid-connected system to capture the most power from waves while limiting losses in the AWS linear generator. In addition, four STA controllers are incorporated into the inverter control loop to preserve the DC link and common coupling voltages at the preset values. The Honey-Badger Algorithm (HBA) is applied for the optimization of gain parameters of the STA controllers, which are compared to the PI gains adjusted using the coot, the hybrid augmented grey wolf optimizer and cuckoo, and PSO search techniques to assess the worthiness of adopting this new control approach. The grid-connected AWS experiences a variety of faults, includingsymmetrical and unsymmetrical faults with successful and unsuccessful breaker reclosures. Finally, the system is experimentally validated using the OP4510 real-time simulator. The experimental results reveal that the HBA-STA controllers outperformPI controllers in omitting fluctuations in the regulated variables, making the STA a strong contender as a control method.

Study of a Thermochemical Heat Storage Reactor Filled with Polyaluminum Sulfate for Low-Temperature Application

This paper investigates comprehensively the operational dynamics of a thermochemical heat storage (TCHS) reactor for low-temperature applications using polyaluminum sulfate and takes into consideration a developed simulation model with an experimentation validation. Significant concordances were found between the developed simulation model and the experimental results. Results reveal optimized conditions for the charging process using an electrical heater, with a heating temperature of 120°C at 10 K/min over 500 minutes. This achieves full material charging, with stabilized pressure drops at an equilibrium of 80 mbar, corresponding to a temperature of approximately 108°C, and yielding a thermal power of 950 W. An inlet vapor pressure of 18 mbar at 10°C for 5 hours is sufficient to completely discharge the bed, with pressure drops reaching around 30 mbar and a thermal power of 300 after reaction completion. Insights into conversion extents during both processes are provided, along with a remarkable thermal efficiency of 90% and a coefficient of performance (COP) of 97%, surpassing recommended theoretical values (50%). The study suggests further enhancing system performance through the design and implementation of a dedicated heat exchanger. The achievement of 75% of the targeted thermal power specification represents a significant milestone, offering valuable contributions towards the realization of sustainable technological advancements of both the reactor technology of TCHS and state-of-the-art thermal energy storage solutions. From the research, it is possible to infer further suggestions for enhancing this performance by designing and implementing a dedicated heat exchanger for both heat supply and retrieval mechanisms.

Tribological performance of ficus carica oil modified with ethylene vinyl acetate and sodium dodecyl benzenesulfonate

PurposeDue to the environmental issues caused by petroleum lubricants used in lubrication, the concept of creating various bio-lubricants requires research globally. Thus, this study aims to develop, characterize and test the base ficus carica oil (fig oil) for its ethylene vinyl acetate copolymer (EVA) and sodium dodecylbenzene sulfonate (SDBS) content.Design/methodology/approachThe sample characterization was done using the Fourier transmission infrared spectrum, whereas the morphologies of the EVA, SDBS particles and lubricated surfaces were carried out under scanning electron microscope equipment. To ensure the homogeneity of the solution (base oil and additives), the formulations were subjected to the sonication process. The anti-friction and anti-wear properties of EVA and SDBS particles as lubricant additives were investigated using a ball on a flat high-frequency reciprocating rig tribo-tester.FindingsAccording to the findings, the base oil’s anti-friction and anti-wear capabilities can be greatly enhanced by the additions. revealed that the best results were obtained when 1.2% EVA + 2% SDBS was applied for the examination of wear (597.8 µm) and friction coefficient (0.106). Commercial references were used, nevertheless, and the results were excellent. This is because the particles in the contact area during lubrication have strong solubility and quickly penetrate the contact zone. The lubricating mechanisms were explained by a tribological model of the EVA + SDBS and SDBS particles.Research limitations/implicationsThe coefficient of friction and wear reduction caused by the use of the additives will certainly enhance system performance and protect the machine components from excessive wear that could cause damage or failure.Originality/valueThe originality and uniqueness of this work are officially affirmed by the authors. The authors’ autonomous and original contribution to the development of sustainable lubrication is represented in this work. To the best of the authors’ knowledge, no other study has been published or made publicly available that duplicates the precise scope and goals of our research, and this conclusion is based on a thorough literature assessment.

Tube Blockage Solutions for Industrial Heat Exchangers

This study investigates the root causes of blockages in heat exchanger tubes and proposes effective mitigation strategies. Industrial heat exchangers face recurrent challenges from tube blockages, impairing operational efficiency. Through a combination of experimental analysis, computational modeling, and data-driven approaches, the research identifies the role of contaminants in causing pressure drops and outlines targeted maintenance protocols. Findings underscore the significance of proactive measures in optimizing heat exchange processes, offering valuable insights for enhancing system performance across diverse industrial applications. Highlights: Tube blockages disrupt production efficiency. Pressure drop due to blockages affects system performance. Analysis needed for prevention measures. Keywords: Production Process, Blockage, Exchangere

Effects of Battery Energy Storage Systems on the Frequency Stability of Weak Grids with a High-Share of Grid-Connected Converters

To achieve an energy sector independent from fossil fuels, a significant increase in the penetration of variable renewable energy sources, such as solar and wind power, is imperative. However, these sources lack the inertia provided by conventional thermo-electric power stations, which is essential for maintaining grid frequency stability. In this study, a grid resembling Madeira Island’s power generation mix was modeled using the Matlab/Simulink platform. The model included solar, wind, hydro, and thermo-electric generation to accurately represent the energy landscape of Madeira Island. Three scenarios were examined: one reflecting the current power generation on Madeira Island, a future scenario with a substantial rise in the percentage of photovoltaic (PV) generation, and the same future scenario but incorporating a battery energy storage system (BESS). Various analyses were conducted to assess the impact on frequency stability during a ground fault and rapid load/generation changes. In the future scenario without a BESS, the thermoelectric power plant generator desynchronized, leading to system collapse in several simulations. However, with the addition of a BESS, a significant improvement in frequency stability was observed. The thermoelectric power plant generator could return to a steady state after each disturbance. Furthermore, both the maximum frequency deviation and the absolute value of the Rate of Change of Frequency (ROCOF) were reduced, indicating enhanced system performance and stability.

Dynamic Load Balancing in Cloud Computing: A Review and a Novel Approach

In cloud computing, load balancing is essential since it guarantees effective resource utilisation and reduces response times. It effectively distributes incoming workload across available servers. Load balancing involves dividing tasks among multiple systems or resources over the internet. By distributing traffic and workloads, load balancing ensures that no server or computer is overloaded, underutilized, or idle in a cloud computing environment. To enhance overall performance in the cloud, it optimises a number of variables, including execution time, response time, and system stability. To increase the effectiveness and reliability of cloud services, load balancing evenly distributes traffic, workloads, and computing resources across the environment. The proposed method, Enhanced Dynamic Load Balancing for Cloud Computing, adjusts load distribution and maintains a balanced system by considering variables like server capacity, workload distribution, and system load. By incorporating these factors and employing adaptive threshold adjustment, this approach optimizes resource allocation and enhances system performance. Experimental research shows that the proposed new novel approach is more effective and efficient than current load balancing techniques. In this context of cloud computing, this ground-breaking method offers a workable substitute for dynamic load balancing.

Stability Analysis and Design of n-DOF Vibration Systems Containing Both Semi-Active and Passive Mechanical Controllers.

This paper is concerned with the stability analysis and design of the n-DOF (n-degree-of-freedom) mass-chain vibration systems containing both semi-active and passive mechanical controllers. Based on Lyapunov's stability theory, sufficient conditions are derived for the n-DOF vibration system containing a semi-active switched inerter and a passive mechanical network with the first-order admittance to be globally asymptotically stable. Furthermore, the optimization designs of a quarter-car vibration control system and a three-storey building vibration system are conducted together with the derived stability results, and the instability cases contradicting the stability conditions are presented for illustration. The optimization and simulation results show that the combination of semi-active and passive mechanical controllers in vibration systems can clearly enhance system performances in comparison with the conventional semi-active or passive control. The novelty of this paper is that the stability problem of a general n-DOF vibration system that simultaneously contains a semi-active controller and a first-order passive controller is investigated for the first time, where such a system combines the advantages of both semi-active and passive mechanical controllers. The investigations and results can provide an essential foundation for further exploring the stability problems of more general systems, and can be applied to the controller designs of many vibration systems in practice.

Enhancing security for physical layer communication in RIS-aided MIMO-NOMA systems in the presence of an eavesdropper

This paper investigates the potential of leveraging a reconfigurable intelligent surface (RIS) in the multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) wireless communication systems. In fact, NOMA improves spectral efficiency (SE) through power domain utilization, and RIS enhances the system performance by manipulating the propagation environment. In this paper, we investigate the physical layer security (PLS) of a RIS-aided MIMO-NOMA system serving two users in the presence of an eavesdropper (EV), where the channel state information (CSI) of the EV is unknown for the BS. To address the security challenge, we utilize secrecy outage probability (SOP) and minimize it by optimizing the RIS’s phase shift matrix, the beamforming vector, and the power allocation coefficients. Due to the non-convexity of the main optimization problem, we decompose the initial problem into three subproblems, and then, we propose an iterative approach to determine the unknown parameters alternately. The first subproblem involves obtaining the optimal beamforming vector and phase shift matrix using the semidefinite relaxation (SDR) method, which introduces high complexity. As an alternative, another algorithm is proposed based on the duality of the optimization problem, offering lower complexity and better accuracy for high-dimensional optimization problems. In this algorithm, the successive convex approximation (SCA) technique is employed to achieve the optimum phase shift matrix, and the stochastic gradient (SG) approach is used to determine the beamforming vector. Furthermore, the paper establishes the optimal values of power allocation coefficients by minimizing the difference between the SOPs of the two users. Finally, the simulation results demonstrate that the proposed power allocation coefficients scheme significantly enhances system performance compared to the existing fixed power allocation coefficients scheme.

Harris Hawks Optimization Algorithm for reducing THD using ZVT-ZCT-based QRCC: A comparative approach

This study proposes a novel solution to address harmonic issues in a Renewable Energy Resource System (RES) connected to the grid, using a Voltage Source Inverter (VSI) controlled by a QRCC based on Zero Voltage Transition and Zero Current Transition (ZVT-ZCT). We enhance system performance by integrating Harris Hawks Optimization (HHO) with the VSI. Key outcomes include evaluating the system's effectiveness in terms of voltage drop, current drop, real power, active power, and total harmonic distortion (THD). Notably, settling times for various converters are highlighted: 0.01 s for SEPIC, 0.008 s for CUK, 0.005 s for ZETA, and an impressive 0.0001 s for the Cascade converter. Under different operational conditions, open-loop operation yields a THD of 18.45%, reduced to 7.843% in closed-loop with PI controller. Optimization techniques further improve the system, achieving a low THD of 0.0549%. We emphasize the significance of MPPT-based INC-IR for cascade converters, resulting in a minimal switching loss of 0.38W, showcasing the system's efficiency in energy conversion.

Soft-switching dual active bridge converter-based bidirectional on-board charger for electric vehicles under vehicle-to-grid and grid-to-vehicle control optimization

Electric vehicles (EVs) are rapidly replacing conventional fuel vehicles, offering powerful, emission-free performance. This paper introduces an innovative three-phase bidirectional charger for grid-to-vehicle (G2V) and vehicle-to-grid (V2G) applications, strengthening the connection between EVs and the power grid. The charger employs a two-stage power conversion approach with advanced converters and a simplified dq-based charging control strategy. An efficient AC-DC converter facilitates smooth transitions between modes, responding to grid directives for active and reactive power. A soft-switching dual active bridge (SS-DAB) DC-DC converter optimally interfaces with the EV battery pack, while dual active LCL filters suppress harmonics, enhancing system performance. Simulated results confirm the charger’s effectiveness in a 3.5-kW prototype using MATLAB/Simulink. The proposed SS-DAB converter-based bidirectional on-board charger introduces a groundbreaking unified Voltage Source Converter (VSC) control approach, enabling efficient power transfer in both vehicle-to-grid (V2G) and grid-to-vehicle (G2V) modes. This innovation ensures rapid dynamic response, exceptional steady-state performance, and robustness against grid demand changes, optimizing EV integration.