System Performance Research Articles

Bidirectional DC-DC Converter and Improved Electrical Vehicle Dynamic Response Control

Background: In automotive applications where bidirectional power flow is necessary to lighten the power system, dual active bridge (DAB) converters are frequently employed. Variations in the required output voltage, erratic input voltage, and shifting loads all have an impact on this converter. As a result, converter performance has to be improved. To increase efficiency, the current stress of the DC-DC converter must be optimised. This paper proposes a control scheme for the coupled inductor bidirectional DC-DC (CIB DC-DC) converter utilising both model predictive control (MPC) and a proportional-integral (PI) controller. The integration of these control techniques aims to enhance the performance and efficiency of the converter. Methods: The MPC algorithm is employed to predict the converter's future behaviour based on a dynamic model, taking into account system constraints and performance criteria. By optimising the control action over a finite time horizon, the MPC algorithm ensures an optimal response, considering the current state and anticipated changes. Additionally, a PI controller is incorporated to augment the control strategy. The proportional component of the PI controller enables a fast initial response to the error between the desired and actual converter outputs. The integral component eliminates steady-state errors and provides robustness against disturbances, resulting in improved overall system performance. Results: The proposed control scheme is implemented and evaluated through simulations and experimental tests on a prototype converter. The results demonstrate the effectiveness of the combined MPC and PI controller approach. Conclusion: The coupled inductor bidirectional DC-DC (CIB DC-DC) converter using MPC can provide precise control of power flow between two voltage domains, enabling efficient bidirectional power transfer. The predictive capabilities of MPC allow it to adapt to varying load conditions and respond quickly to changes, ensuring stable operation and accurate regulation of voltage and current. Overall, the coupled inductor bidirectional DC-DC converter controlled using MPC over PI offers improved performance, efficiency, and flexibility compared to traditional control methods. MPC can handle the complex dynamics response and non-linear characteristics of the converter, making it suitable for bi-directional vehicle charging applications, where precise control and high efficiency can be achieved.

A Novel Free-Air Diesel and Ozone Enrichment (FADOE) Research Platform

Air pollution is an escalating concern in the modern world, posing substantial threats to ecosystems processes. While the importance of comprehending the impact of pollutants on natural environments is evident, conducting rigorous field-based experiments presents formidable challenges. Elevating pollutant concentrations within open air environments in a controlled manner is complex. Nonetheless, such real-world experiments are invaluable for revealing the genuine influence of air pollutants on ecosystems and their functioning. Field-scale measurements have emerged as a pivotal avenue for advancing our understanding of the interactions between air pollutants and the natural world, providing unique insights into ecosystem dynamics, including critical processes like pollination and natural pest regulation. In atmospheric and ecological research, free-air exposure systems have proven effective in elevating carbon dioxide (CO2) and ozone (O3) concentrations, facilitating the exploration of their ecological consequences. Yet, nitrogen oxides (NOx), a class of pollutants with significant ecological and atmospheric relevance, have largely eluded field-based ecological investigations. This paper introduces the recently developed FADOE (Free-Air Diesel and Ozone Enrichment) platform, which allows the elevation of O3 and diesel exhaust (including NOx) within a field-scale context. Comprehensive information on the system's design, construction, and performance data from the 2023 summer season is presented.• Air pollution and ecosystem functioning• Elevated ozone and nitrogen oxides (NOx)• Free-air exposure systems for field scale measurements.

Enhancing of single-stage grid-connected photovoltaic system using fuzzy logic controller

The power generated by photovoltaic (PV) systems is influenced by environmental factors. This variability hampers the control and utilization of solar cells' peak output. In this study, a single-stage grid-connected PV system is designed to enhance power quality. Our approach employs fuzzy logic in the direct power control (DPC) of a three-phase voltage source inverter (VSI), enabling seamless integration of the PV connected to the grid. Additionally, a fuzzy logic-based maximum power point tracking (MPPT) controller is adopted, which outperforms traditional methods like incremental conductance (INC) in enhancing solar cell efficiency and minimizing the response time. Moreover, the inverter's real-time active and reactive power is directly managed to achieve a unity power factor (UPF). The system's performance is assessed through MATLAB/Simulink implementation, showing marked improvement over conventional methods, particularly in steady-state and varying weather conditions. For solar irradiances of 500 and 1,000 W/m<sup>2</sup>, the results show that the proposed method reduces the total harmonic distortion (THD) of the injected current to the grid by approximately 46% and 38% compared to conventional methods, respectively. Furthermore, we compare the simulation results with IEEE standards to evaluate the system's grid compatibility.

Enhancing ANPR accuracy for staff car verification using convolutional neural networks and RegEX correction

This research paper presents the development and evaluation of an Automatic Number Plate Recognition (ANPR) system using Convolutional Neural Networks (CNN) with Regex correction. The aim is to enhance the accuracy and effectiveness of car verification and security processes at First Technical University, Ibadan. The ANPR system was implemented both without Regex correction and with Regex correction. The evaluation results demonstrate significant improvements in the system's performance when CNN with Regex correction is employed. The CNN-based ANPR system achieves a precision of 1.00, recall of 0.90, and F1-score of 0.95 in accurately identifying number plates. These scores indicate increased accuracy and reduce false positives compared to the system without Regex correction. The integration of CNN and Regex correction effectively handles variations and errors in the number plate data, leading to a reliable and efficient car verification process. Future work can focus on further refining the CNN model and optimizing the Regex correction algorithms to enhance the system's accuracy and robustness. The developed ANPR system, utilizing CNN with Regex correction, shows great potential for enhancing car verification and security in various domains, including law enforcement, parking management, and traffic monitoring

Random access memory page caching: a strategy for enhancing shared virtual memory multicomputer systems performance

This study examines a modified approach to optimizing the performance of support vector machine (SVM)-type multicomputer systems through a distinct type of caching method that allocates space in the random access memory (RAM) of a computing node for caching pages. The article extensively describes research on enhancing the performance of the SVM system through memory page caching in RAM at the hardware level by implementing the SVM system based on field-programmable gate arrays (FPGA). A systematic comparative evaluation highlights a discernible enhancement in system performance relative to systems not equipped with the revised caching algorithm. These findings could prove instrumental for subsequent studies focused on optimizing the performance of SVM systems, providing empirical data to inform future investigations and potential applications in multicomputer system performance enhancement.

Enhancing power conversion efficiency in five-level multilevel inverters using reduced switch topology

This paper presents extensive research on improving the power conversion efficiency of five-level multilevel inverters (MLIs) by utilizing a reduced switch topology. MLIs have received an abundance of focus because of their ability to generate high-quality output waveforms and have better harmonic outcomes than traditional two-level inverters. The high number of switches in MLIs, on the other hand, can result in increased power losses and lower overall efficiency. In this paper, a novel reduced switch topology for five-level MLIs, which is having five switches is proposed with the aim of minimizing power losses while preserving superior performance due to lesser number of switches. To achieve efficient power conversion, the proposed topology employs advanced pulse width modulation control strategies and optimized switching patterns. The simulation results show that the minimized switch topology improves the power conversion efficiency of the five-level MLI, resulting in lower losses and better overall system performance. The total harmonic distortion (THD) value of the output current has been reduced to 7.12% and the efficiency has been achieved to 96.92%. The findings of this investigation help to advance MLI technology, allowing for more efficient and reliable power conversion in a variety of applications such as renewable energy systems, electric vehicles, and industrial drives.

Risk, Sensitive Analysis, and Optimization of a New Multi-generation System Activated by Solar and Biomass Energies

In recent years, the use of clean energies has become much more important due to the increase of environmental pollutants and the reduction of fossil fuel resources. Another important parameter in the establishment of energy systems is the assessment of the risks caused by the construction of the system and the provision of operational solutions to manage and reduce these risks. In this research, a new multi-generation system that is activated using solar and biomass energies has been evaluated thermodynamically and thermo-risky. This system consists of a Brayton cycle, a steam Rankine cycle, a transcritical CO2 cycle, a proton membrane electrolyzer (PEME) unit, and an internal combustion engine (ICE). A notable characteristic of the proposed system is its capability to recover waste heat from the gas turbine cycle, which is subsequently utilized to drive both a steam Rankine cycle and a transcritical CO2 cycle. The sensitivity analysis has been performed to investigate the effects of the input parameters on the system performance and finally, an optimization for the effective parameters of the system has been conducted. The results of the calculations show that the proposed system has energy and exergy efficiencies of 22.05% and 15.93%, respectively. The risk analysis was conducted by considering the potential hazards such as jet fires, jet of combusted gases, and system overpressure. The analysis indicates that the system poses a low level of risk. The overall risk, along with the risk per unit of system exergy, has been estimated at 4.247 ×10-8 injuries/year and 3.73 ×10-11 injuries/year.kW, respectively. In optimal conditions, the energy and exergy efficiency of the system reaches 25.79% and 19.08%.

Optimal coordination of directional over current relays for distribution systems using hybrid GWO-CSA

Coordination of protective relays is a critical aspect of electrical distribution systems, ensuring effective and reliable protection against faults. In modern power systems, the integration of distributed generation (DG) sources adds complexity to the coordination task. The dynamic nature of DG systems requires adaptive relay settings that can swiftly detect and isolate faults while minimizing potential damage and downtime. The purpose of this research is to improve the coordination of directional over current relays in electrical distribution systems, particularly in DG systems. An optimization technique combining the grey wolf optimization (GWO) and cuckoo search algorithm (CSA) is developed to identify the best relay settings that reduce overall operation time while ensuring excellent fault identification and isolation. To address relay faults caused by DG integration, a suitable primary and backup relay design is chosen, and the influence of time multiplier settings (TMS) on system performance and reliability is investigated. The proposed GWO-CSA technique is evaluated and implemented on IEEE 3, 8 and 15-bus systems using MATLAB. Simulation results show that the GWO-CSA strategy outperforms well compared to previous algorithms, enabling optimal coordination and increased protection in DG systems while drastically lowering relay operating time.

High nitrogen removal and electricity generation of anaerobic fluidized bed coupled microbial fuel cell for Anammox

The current challenge in wastewater denitrification lies in the treatment of low carbon to nitrogen ratio(C/N) wastewater. Integrating Anaerobic Ammonia Oxidation(Anammox) with a microbial fuel cell(MFC) enables simultaneous pollutant removal and electricity generation, leading to enhanced treatment efficiency and reduced energy consumption. However, achieving stable and effective treatment effects under high nitrogen concentration conditions remains a general research difficulty. The Anaerobic fluidized bed MFC(AFB-MFC) experiment successfully integrated Anammox ammonia oxidizing bacteria (AnAOB) into the anode and cathode chambers, resulting in a continuous operation for 258 days. The reactor successfully initiated operation within 48 days and maintained stable performance within an NLR range of 0.5-1.0 kgN/m3/d. The system performance was found to be influenced by DO and substrate concentration, demonstrating consistent high nitrogen removal ability across different HRT. Ultimately, the Anammox AFB-MFC achieved a nitrogen removal efficiency (NRE) of 96.89%, while its power generation performance gradually improved, yielding a final output voltage ranging from 370 to 420mV. The microbial community within the reactor comprised diverse electricity-producing bacteria and AnAOB. This study highlights the excellent denitrification and power generation potential of Anammox AFB-MFC under low energy consumption conditions and provides theoretical groundwork for the practical implementation of Anammox.

Load frequency control of interconnected power system using cuckoo search algorithm

This paper presents a new time-domain multi-objective function approach for solving load frequency control issue in an interconnected power system. The performance of interconnected power system in each area is validated for overshoot and settling time values of frequency change and tie-line power exchange. An objective function is created with the goal of enhancing proportional integral derivative (PID) controller settings by reducing overshoot and achieving faster time-domain settling times. The efficiency of the proposed time-domain multi-objective function is evaluated in a two-area thermal power plant using a nature-inspired cuckoo search optimization (CSA) technique. By comparing the time-domain simulation results of the test system with the existing integral error-based objective functions IAE, ISE, ITAE, and ITSE, the proposed objective function is validated. Further, a sensitivity analysis were carried out to analyze the robustness of the proposed multi-objective function under various uncertain conditions.

Improving The Dynamic Performance of Two-area System Based Integration of RES

Improving The Dynamic Performance of Two-area System Based Integration of RES

Performance and compensation method of first-order liquid crystal beam-steering system under continuous wave laser irradiation

The effects of laser irradiation thermal deposition on the performance degradation of liquid crystal (LC) devices in high-power laser systems are extremely vital. In this study, the first-order beam-steering system (FBS) was developed using a passive liquid crystal polarization grating (LCPG) and liquid crystal adjustable wave-plate (LCAW). The LCPG was prepared by holographic exposure technology, and the LCAW was prepared using the standard LC cell preparation process. We investigated the influences of diffraction efficiency of FBS under a 1070-nm continuous-wave (CW) laser irradiation. The energy is concentrated in the −1st order at first. When the half-wave retardation was reached, all the energy is concentrated in the +1st order (∼97 %), and the beam is deflected. Once the phase retardation decreases below the half-wave retardation, the energy gradually reconcentrates in the −1st order. When the LCAW fails, the diffraction the energy is refocused to the −1st order by the LCPG. The results indicated that both thermal deposition and driving voltage reduce the phase retardation of the LCAW, generating a variation of energy between in ±1st orders. By reducing the driving voltage, this half-wave retardation can be recovered under a certain half-wave voltage and laser power density, and the diffraction efficiency of the +1st order can be compensated to ∼97 %. If the reduced phase retardation is not less than half-wave, the FBS can still be modulated in high-power continuous lasers. Our research provides a reference for the development of beam-steering technology based on LC materials in high-power laser systems.

Experimental study of smoke characteristics in a double-deck tunnel with multiple point extraction using a branch pipe

A reduced scale 1:8 double-deck tunnel model was built to study smoke control performance of a semi-transverse ventilation system using a branch pipe to connect the lower deck tunnel to the upper smoke duct. 41 experiments were conducted to analyze the effects of different activation modes of smoke vents, heat release rate (HRR), and exhaust smoke rates on smoke spread distance. An optimum smoke control mode was found by activating two vents near the fire source when the heat release rate was 44.19 kW (8 MW at full scale) and the fan's extraction rate was 0.66 m3/s (120 m3/s at full scale) using a branch pipe. Results showed that as HRRs rise, the smoke spread distance first increases and then remains constant. The ratio of the smoke spreading distance on the upstream side of the fire to the total smoke spreading distance was 0.4 in this experimental setup. Furthermore, fire smoke spread characteristics were quantified for a typical ventilation design.

Three-phase model of SCIG-based variable speed wind turbine for unbalanced DSLF analysis

Steady state performances of the electric power distribution system are normally assessed or evaluated based on load flow analysis. To properly carry out the analysis, a valid steady state load flow model of each distribution system component, including the wind power plant (WPP), needs to be developed. The present paper proposes a method for modeling and integrating squirrel cage induction generator (SCIG)-based variable speed WPP into a three-phase unbalanced distribution system load flow (DSLF) analysis. The proposed method is based on a single-phase T-circuit model of fixed speed WPP, which has successfully been applied to balanced electric power systems. In the present work, the single-phase T-circuit model is extended and modified to be used in steady state load flow analysis of three-phase unbalanced distribution systems embedded with SCIG-based variable speed WPP. Results of the case studies confirm the validity of the proposed method.

Particle swarm optimization based sliding mode control for maximum power point tracking in solar PV systems

One of the most significant renewable energies is photovoltaic (PV) energy, however it has a low efficiency due to its variable maximum power point that depends on weather conditions. In order to guarantee the system's best performance, intelligent algorithms can effectively track this point in real-time utilizing the maximum power point tracking (MPPT) method. Consequently, it is crucial to maximize the use of the solar energy that has been captured as well as the PV system's generated electricity. Variations in solar irradiance affects the amount of electric energy obtained from solar arrays. For efficient extraction of electricity from solar PV systems, MPPT algorithms are required. Sliding mode control (SMC) can be used in the control of nonlinear systems. However, the effectiveness of SMC can be improved by the choice of the sliding coefficients. In this paper, optimal search using particle swarm optimization (PSO) is used in the design of the sliding manifold. Results obtained via simulations showed that MPPT tracking efficiencies obtained for the PSO based SMC and the conventional SMC are 99.65% and 96.79% respectively. That means, PSO based SMC is 2.86% better than conventional SMC.

Autonomous vehicle tracking control for a curved trajectory

Recently, research about trajectory tracking of autonomous vehicles has significantly contributed to the development of autonomous vehicle technology, particularly with novel control methods. However, tracking a curved trajectory is still a challenge for autonomous vehicles. This research proposes a state feedback linearization with observer feedback to overcome some difficulties arising from such a path. This approach suits a complex nonlinear system such as an autonomous vehicle. This method also has been compared with the linear-quadratic regulator (LQR) method. So, the goal of this research is to improve the control system performance of autonomous vehicles that are stable enough to navigate a curved path. Moreover, the study shows that the developed control law can track the curved path and solve existing problems. However, improvements are still necessary for the vehicle's performance and robustness.

Enhancing Low Voltage Ride-Through Resilience using Empowering Solar Energy Strategies

The rapid advancement of Low Voltage Ride-Through (LVRT) technology has been highlighted by the exponential rise of photovoltaic (PV) generation systems. An extensive analysis of LVRT methods specifically designed for PV generating systems is presented in this research. Important topics like main causes, current control schemes, power balance and overall solutions are the main focus of the review. Moreover, it provides comprehensive insights and elaborates on integrated solutions intended for large-scale PV systems. The objective of this research is to improve the resilience and reliability of renewable energy sources, especially solar photovoltaic systems, against grid disruptions and voltage changes by investigating LVRT approaches in solar power systems. Enhancing the integration of solar power systems into current electrical grids, reducing downtime, and optimizing system performance are the objectives in order to accelerate the shift to a more resilient and sustainable energy infrastructure.

Voltage stability index: a review based on analytical method, formulation and comparison in renewable dominated power system

In an interconnected complex power system network voltage stability evaluation is indispensable to guarantee secure power system operation. To further increase the system performance and to make the system safer assessment, the voltage stability improvement is obligatory. In the various literature different voltage security assessment method using the voltage stability index has been presented. Different lists proposed in literature can be utilized to realize the weak buses and weak transmission lines to enacting the countermeasures against issues of voltage insecurity. Additionally, the arrangement and measuring of inexhaustible assets, on the web and disconnected observing of force framework and the measure of load to be shed at whatever point essential. This paper shows a survey on the different voltage stability index from various perspectives. The audit results on various record gives a far and wide logical to perceive the impending works in this field and to choose the best index for variety of applications such as voltage security assessment, renewable energy integration, distributed generation (DG) placement and sizing, online monitoring of the power system, and shedding of load.

Comprehensive review and analysis of photovoltaic energy conversion topologies

Energy conversion is a pivotal process with widespread applications, spanning renewable energy systems, electric vehicles, and industrial power grids. Selecting the right energy conversion topology is critical for optimizing system performance, efficiency, and reliability. This comprehensive review paper provides a thorough overview of energy conversion topologies used in photovoltaic (PV) panel systems, as well as their applicability in diverse domains. Furthermore, the paper conducts a detailed analysis of commonly employed energy conversion topologies. Each topology is meticulously examined based on its operating principles, advantages, drawbacks, and typical use cases. This comprehensive review serves as an invaluable resource for researchers, engineers, and practitioners engaged in the dynamic field of energy conversion, offering insights into both wind energy and photovoltaic panel systems.

Electrical signal interference minimization using appropriate core material for 3D integrate circuit at high frequency applications

As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.