Abstract
Many different technologies have been studied in relation to electrical generator control system management and condition monitoring. The ability to plan, control systems, and monitor them offers benefits for finances, operations, and technology. Electric generator manufacturers are drawn to this area ...
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Many different technologies have been studied in relation to electrical generator control system management and condition monitoring. The ability to plan, control systems, and monitor them offers benefits for finances, operations, and technology. Electric generator manufacturers are drawn to this area for this reason. The focus of this review paper is on the control system management of synchronous generators, with a particular emphasis on the utilization of Field Programmable Gate Array (FPGA) and microcontrollers with techniques such as Proportional-Integral (PI), Proportional-Integral-Derivative (PID), etc. Furthermore, monitoring the synchronous generator's condition has been introduced using Internet of Things (IoT) variable devices. Finally, the paper delves into the classification and thorough analysis of recent research suggesting control systems and monitoring models, including interactions with various kinds of power plants that run on synchronous generators. The survey results included many relevant articles and papers about the application of control systems to the Internet of Things.
Abstract
In this paper, a fuzzy controller is presented in order to achieve the maximum power in a solar cell. For improvement of the controller performance and achievement of the maximum power, the fuzzy controller variables are improved by the Grasshopper Optimization Algorithm (GOA). This algorithm has flexibility ...
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In this paper, a fuzzy controller is presented in order to achieve the maximum power in a solar cell. For improvement of the controller performance and achievement of the maximum power, the fuzzy controller variables are improved by the Grasshopper Optimization Algorithm (GOA). This algorithm has flexibility and fast convergence. In this paper, the ISE evaluation index is employed as the cost function of algorithm to verify the obtained results. The results show that under the supposed conditions, the power value of the solar cell utilizing the suggested algorithm has increased compared to other algorithms. In the simulation, the power value using the proposed algorithm is 182.3 watts and the cell efficiency in this case is 99.97%. Therefore, the achieved results show at least 0.03% and 1.2% improvement, respectively in power and efficiency, compared to some examined methods.
Abstract
Controlling a cart-pendulum system involves both swinging the pendulum up and maintaining its upright position. Typically, separate controllers are used for the swing-up and stabilization phases. This paper presents the implementation of a Fractional Order Proportional-Integral-Derivative (FOPID) controller ...
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Controlling a cart-pendulum system involves both swinging the pendulum up and maintaining its upright position. Typically, separate controllers are used for the swing-up and stabilization phases. This paper presents the implementation of a Fractional Order Proportional-Integral-Derivative (FOPID) controller for the cart-pendulum system. A novel metaheuristic method, Class Topper Optimization (CTO), is utilized to design and optimize the FOPID controller’s performance for both the cart and pendulum. The study focuses on the pendulum angle and arm angle as key parameters. Results indicate that the proposed approach outperforms existing methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO).
Abstract
Power distribution networks have become more interested in Distributed Generations (DG) due to their potential for reducing power loss and improving system dependability. Discovering the optimal site, size, and reconfiguration strategy for a DG-based distribution network using a metaheuristic algorithm ...
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Power distribution networks have become more interested in Distributed Generations (DG) due to their potential for reducing power loss and improving system dependability. Discovering the optimal site, size, and reconfiguration strategy for a DG-based distribution network using a metaheuristic algorithm is the main goal of this study. The multi-objective and multi-constrained feature of the Whale Optimization Algorithm (WOA) makes it a useful optimization technique for network reconfiguration. In this paper, the forwardbackward load flow technique is employed due to its easy implementation, quick and reliable convergence. The recommended approach is validated through two different test systems. Four different scenarios are considered. Improvements in power loss reduction and voltage profile illustrate the effectiveness of the proposed technique. The obtained results showed that DG allocation after network reconfiguration resulted in a greater reduction of power losses and refinement of the voltage profile of the network. Also, a comparisonis employed with other optimization methods, it can be seen that the suggested method’s performance is clearly superior, as shown by the numerical data. Losses were reduced by 67.8% and 63.21% on IEEE 33 and 69 bus systems, respectively, when using the suggested strategy. All the simulations are conducted through MATLAB.
Abstract
The new pattern of user traffic generation in recent years and the variety of traffic services including data, voice and video have led to a large load in the access of cellular networks. One of the promising solutions in the field of reducing this traffic load is data offloading, which is based on exploiting ...
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The new pattern of user traffic generation in recent years and the variety of traffic services including data, voice and video have led to a large load in the access of cellular networks. One of the promising solutions in the field of reducing this traffic load is data offloading, which is based on exploiting the unused bandwidth of wireless technologies overlapping with the cellular network. As a widespread technology, Wi-Fi networks have been proposed as a suitable solution for data offloading in cellular networks. Considering the effect of access points (APs) on the performance of Wi-Fi networks, deploying APs can affect the efficiency and cost of Wi-Fi-based data offloading. This issue is the main research part of the current paper. In this paper, an optimization problem is proposed to find the best location for the Wi-Fi APs, providing the maximum performance metric for offloading. Two optimization algorithms are proposed to solve the problem: the Krill Herd Algorithm (KHA) and the Greedy algorithm. The evaluation results indicate that the feature of global optima in the exploration phase of the KHA algorithm leads to finding a better location of the APs than the Greedy algorithm.
Abstract
Nine switch converters (NSCs) are power electronic devices that utilize nine power switches to convert electrical energy from one form to another. These converters are commonly used in various applications within the power industry. In fact, this type of converter is a multi-port power electronic device ...
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Nine switch converters (NSCs) are power electronic devices that utilize nine power switches to convert electrical energy from one form to another. These converters are commonly used in various applications within the power industry. In fact, this type of converter is a multi-port power electronic device that consists of two three-phase terminals and a DC link, similar to the twelve-switch back-to-back (BTB) converter. However, it distinguishes itself by reducing the number of active switches by 25%. Nine switch converters offer several advantages over traditional converters. They can provide improved efficiency, reduced harmonic distortion and enhanced control capabilities. Additionally, they can handle higher power levels and operate at higher frequencies, making them suitable for a wide range of power industry applications. Furthermore, they are cost-effective, compact, and adaptable to higher power levels. By distributing voltage and current across fewer switches, the overall stress on individual components is reduced, which can enhance the lifespan and reliability of the converter. This paper summarizes the various utilizations of NSCs in modern power systems and briefly reviews the related challenges and future prospects.
Abstract
The Modular Multilevel Converter (MMC) HVDC system is becoming increasingly significant in contemporary power grids as power electronics technology continues to evolve. It is essential to provide protection in large DC circuits to maintain stability and security during faults. This paper presents a comparative ...
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The Modular Multilevel Converter (MMC) HVDC system is becoming increasingly significant in contemporary power grids as power electronics technology continues to evolve. It is essential to provide protection in large DC circuits to maintain stability and security during faults. This paper presents a comparative analysis of the travelling wave-based protection schemes of PMGMW and CBTW, which were originally developed for LCC HVDC systems and have been adapted for a two-terminal MMC HVDC system. In order to assess fault resistance endurance, fault identification accuracy, and processing time under a variety of fault conditions, simulations were conducted in PSCAD/EMTDC. The results suggest that Pole Mode Ground Mode Wave’s (PMGMW) scheme is more resilient to high resistance faults, maintaining accuracy at fault resistances of up to 100 Ω, while Change in Backward Travelling wave’s (CBTW) scheme is less resilient to high resistance faults but demonstrates quicker fault identification with reduced processing time. Consequently, this investigation further solidifies the insights into the improvement of current protection systems for MMC HVDC applications.
Abstract
Energy consumption is becoming a pressing concern in today’s digital era, driven by the rapid pace of innovation and the increasing demand for faster computational devices. Over the decades, global energy consumption trends have undergone significant changes, with far-reaching implications for ...
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Energy consumption is becoming a pressing concern in today’s digital era, driven by the rapid pace of innovation and the increasing demand for faster computational devices. Over the decades, global energy consumption trends have undergone significant changes, with far-reaching implications for the environment, economy, and society. This paper is aimed at conducting a comprehensive analysis of the trend in global energy consumption focusing on the interplay between economic growth, technological advancements, and environmental sustainability and assessing whether consumption increased or decreased as well as examining the factors driving these changes. The study covers a time span from 1900 historical data with a projection of up to 2050 to contemporary energy scenarios and examines energy consumption patterns across various countries like China, USA, India, South Korea, South Africa and Australia with particular emphasis on both developed and emerging markets. Utilizing an empirical methodology that includes data collection from reputable sources such as the Energy Institute and the U.S Department of Energy and analytical techniques, the study employs quantitative analysis to assess shifts in energy consumption and the transition towardsrenewable energy sources. The main findings indicate a significant increase in global energy demand driven by population growth and urbanization, alongside a notable shift towards renewable energy adoption. The study highlights the critical role of technological innovations in enhancing energy efficiency and reducing reliance on fossil fuels. Furthermore, it identifies the need for comprehensive policy frameworks that promote sustainable energy practices and investment in renewable technologies. The relevant policy implications from the study suggest that governments and stakeholders must prioritize the development of policies that facilitate the transition to renewable energy, enhance energy efficiency, and support technological advancements. By addressing these areas, the study contributes to the discourse on achieving a sustainable energy future and mitigating the environmental impacts of energy consumption.
Abstract
This study examines power system stability through the application of the improved sine cosine algorithm (ISCA). To minimize the oscillation of the system, two damping controllers have been used, the first one is power system stabilizer (PSS) and second one is static synchronous series compensator (SSSC). ...
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This study examines power system stability through the application of the improved sine cosine algorithm (ISCA). To minimize the oscillation of the system, two damping controllers have been used, the first one is power system stabilizer (PSS) and second one is static synchronous series compensator (SSSC). A single machine infinite bus (SMIB) is implemented to analyze the stability performance. The various parameters of PSS and SSSC have been tuned with the use of the ISCA approach, which improves the system performance. The main aim of this work is to reduce the speed deviation of rotor. A comparative analysis has been carried out with traditional sine cosine algorithm (SCA) on performance basis. The fitness value (ITAE) of SCA and ISCA are found to be 0.0018573 and 0.0018518 respectively. The SMIB system is tested with different loading such as nominal loading (NL), light loading (LL), heavy loading (HL) condition. To check the robustness of the proposed system, various faults (LLLG fault, LLG fault, LL fault, LG fault) has been applied to the system and results are compared with ISCA optimized controller.
Abstract
It is crucial to monitor and diagnose cardiac function early to prevent the development of future, more severe issues. This study categorized 193 male and female subjects into three groups based on their ECG signals obtained during an exercise test: healthy, myocardial infarction, and left bundle branch ...
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It is crucial to monitor and diagnose cardiac function early to prevent the development of future, more severe issues. This study categorized 193 male and female subjects into three groups based on their ECG signals obtained during an exercise test: healthy, myocardial infarction, and left bundle branch block. The data were then processed and converted into images representing three time-frequency representations: a spectrogram, a scalogram, and a spectrum. These images were used as input for two pre-trained networks through transfer learning. The ResNet-18 and GoogLeNet networks were utilized in this study. The ResNet-18 network achieved an accuracy of 88.64% for the spectrogram, 98.41% for the scalogram, and 83.33% of the spectrum. The results for the GoogLeNet network were as follows: 77.27% for the pectrogram, 97.62% for the scalogram, and 78.57% of the spectrum.
Abstract
With a tropical climate in Malaysia, varieties of vegetables can grow all year round. Nevertheless, during the hot season, watering the plant is challenging, especially for vegetables that are intolerant to heat such as tomato plants. Over-watering or under-watering could decrease the yield and quality ...
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With a tropical climate in Malaysia, varieties of vegetables can grow all year round. Nevertheless, during the hot season, watering the plant is challenging, especially for vegetables that are intolerant to heat such as tomato plants. Over-watering or under-watering could decrease the yield and quality of tomatoes. Therefore, in this study, we proposed an efficient irrigation system based on Hargreaves’s potential evapotranspiration to improve the yield and quality of tomato plants in Melaka, Malaysia. Using the Hargreaves equation, the correlation between the surrounding temperature and the amount of water needed by the tomato plants is investigated. Three growth stages are considered: early stage (0−30 days of planting), middle stage (31−76 days of planting), and final stage (77−105 days of planting). Based on a 30-day analysis, on average, tomato plants require 45.5 mL/day, 87.4 mL/day, and 60.8 mL/day respectively for the early, middle, and final stages of growth. A mobile monitoring application is also developed using MIT App Inventor for users to monitor the temperature, humidity, soil moisture, pH level, status of water pumps, and the amount of water released tothe plants. The proposed system can increase the efficiency of the irrigation process and ultimately, reduce the farming cost.
Abstract
In the quest for sustainable energy solutions, this study analyses the hybrid solar photovoltaic (PV)-diesel generator system’s feasibility for reliable electricity supply to a mini-mart in Ajase-Ipo, Nigeria. Utilizing HOMER software, the system was modelled and optimized with a focus on both ...
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In the quest for sustainable energy solutions, this study analyses the hybrid solar photovoltaic (PV)-diesel generator system’s feasibility for reliable electricity supply to a mini-mart in Ajase-Ipo, Nigeria. Utilizing HOMER software, the system was modelled and optimized with a focus on both technical and economic factors. The optimal configuration comprises a 10.2 kW solar PV system, 8 batteries, a 6-kW converter, and a 10-kW diesel generator, meeting the annual energy demand of 29,200 kWh. The system’s technical performance is highlighted by a capacity utilization factor of 17.9% and a performance ratio of 82.16%, demonstrating the efficiency of the solar PV system. However, heavy reliance on diesel fuel, with an annual consumption of 5,632 litres, leads to a high levelized cost of energy (LCOE) of 306.16 per kWh. This underscores the need for strategies to reduce diesel dependency and improve long-term economic viability through improved solar capture and optimized battery storage. The system also demonstrates significant environmental benefits, with CO2 emissions reduced by 8,614 kg annually, alongside reductions in other harmful pollutants such as CO, SO2, and NOx. These findings reinforce the potential of renewable energy to provide a more sustainable, cost-effective, and environmentally friendly solution for electricity generation in similar contexts.
Abstract
Heroin is a highly addictive drug with devastating effects on various parts of the body, including the digestive system, nervous system, and mental health, and it can lead to premature death. One of the most destructive impacts of heroin use is on the brain. Electroencephalograms (EEG) indicate the brain’s ...
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Heroin is a highly addictive drug with devastating effects on various parts of the body, including the digestive system, nervous system, and mental health, and it can lead to premature death. One of the most destructive impacts of heroin use is on the brain. Electroencephalograms (EEG) indicate the brain’s activity in the physiological and psychological states of heroin addicts. Identifying distinguishing features is crucial for processing these signals and determining the differences between the EEGs of healthy individuals and addicts. The frequency and time domain features extracted from different channels of EEG vary, but identifying distinguishing features can aid in better analysis of these signals. This article uses the Davies-Bouldin criterion to determine distinguishing frequency and time domain features. EEGs of heroin addicts (15 individuals) and healthy individuals (15 individuals) were extracted from 16 different channels. The distinguishing feature with the lowest Davies-Bouldin index value was selected. The results of this study show that inpeople addicted to heroin, the frequency power spectrum in the upper alpha subband of the O1 channel has decreased. Additionally, approximate entropy is increased in the Cz channel of heroin addicts. To evaluate the distinguishing features, support vector machine classification has been used to distinguish addicts from healthy individuals. The sensitivity and accuracy of distinguishing an addicted person from a healthy person in the approximate entropy feature are 91.50% and 91.81%, respectively, and in the power spectrum feature in the upper alpha subband of the O1 channel, they are 95.92% and 92.40%, respectively. Compared to other studies, the obtained results confirm the distinction and superiority of these features in terms of precision and accuracy. According to the results, the analysis of frequency and time domain features of brain signals can help to better understand the effects of heroin consumption on brain activity. This study may help provide solutions to improve the treatment and prevention of heroin addiction.
Abstract
This paper presents a power management and control strategy for a residential DC microgrid (DCMG) incorporating photovoltaic (PV) systems, fuel cells (FCs), and a hybrid energy storage system (HESS). The fluctuations in the DC bus voltage, arising from intermittent PV generation and variable load conditions, ...
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This paper presents a power management and control strategy for a residential DC microgrid (DCMG) incorporating photovoltaic (PV) systems, fuel cells (FCs), and a hybrid energy storage system (HESS). The fluctuations in the DC bus voltage, arising from intermittent PV generation and variable load conditions, are mitigated by the HESS, which comprises both batteries and supercapacitors (SCs). This control strategy adopts, batteries to handle slow-frequency power surges, whereas SCs are employed to manage rapid frequency fluctuations effectively. The proposed controllers are optimized using an evolution-based Genetic Algorithm (GA), eliminating the need for extensive mathematical modeling of the system. Comparative analysis between the GA-tuned and conventionally tuned controllers is conducted based on performance metrics, including overshoot, undershoot, and settling time. The simulation results indicate that the proposed controller performs satisfactorily, achieving a maximum overshoot of 3.08%, a maximum undershoot of 2.95%, and a settling time of 44.5 ms. To further assess the efficacy and robustness of the controllers, they are subjected todisturbances in sensor readings and variations in system parameters within a range of ±25% of their nominal values. Additionally, to validate the practical applicability of the proposed system, the simulation results are corroborated using a real-time FPGA-based simulator (OP 5700).
Abstract
With the development of quantum computing technology, the current cryptographic systems face significant threats. Quantum algorithms, such as Shor’s algorithm, have demonstrated the capability to efficiently solve mathematical problems upon which traditional cryptographic protocols rely for security. ...
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With the development of quantum computing technology, the current cryptographic systems face significant threats. Quantum algorithms, such as Shor’s algorithm, have demonstrated the capability to efficiently solve mathematical problems upon which traditional cryptographic protocols rely for security. This emphasizes the critical need for Post-Quantum Cryptography (PQC) as a preemptive measure against the potential vulnerabilities posed by quantum computers. There are diverse signature schemes available, each exhibiting unique performance characteristics. The selection of an optimal scheme tailored to specific applications is necessary for ensuring both efficiency and security. To address this, a novel approach based on Evaluating Distance from Average Solution (EDAS) can be employed to rank the PQC algorithms based on the compromise score computed within the algorithm. In the pursuit of evaluating various schemes, signatures are generated using SPHINCS+-Haraka-128s-simple, SPHINCS+-Haraka-256f-simple, Supersingular Isogeny Key Encapsulation (SIKE), Falcon-1024 and Dilithium5. These schemes represent a spectrum of post quantum cryptographic techniques, each with its strengths and weaknesses. The performance metrics are systematically measured to provide a quantitative basis for comparison. Key aspects, including the efficiency of generating keys, signing processes, and verification procedures, are scrutinized to capture the schemes’ overall capabilities. The EDAS is then calculated for each metric using the weight computed by Eigenvector or Real Time Aggregation strategies, offering a nuanced perspective by accounting for the distance of each scheme’s performance from the average solution. By considering these findings, stakeholders can make informed decisions about which scheme aligns best with their particular security and efficiency requirements, thus contributing to a more robust and tailored digital signature implementation.
Abstract
Fifth Generation for Railways (5G-R) is a promising technology that seeks to improve safety, efficiency, and passenger experience by supporting a variety of services, such as real-time monitoring, predictive maintenance, autonomous operation, and passenger entertainment by accessing the Internet during ...
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Fifth Generation for Railways (5G-R) is a promising technology that seeks to improve safety, efficiency, and passenger experience by supporting a variety of services, such as real-time monitoring, predictive maintenance, autonomous operation, and passenger entertainment by accessing the Internet during trips, thus starting a new era of smart and efficient railway transportations. However, 5G-R suffers from the termed inter-carrier interference (ICI) problem due to the Doppler shift phenomenon especially when operating in high-mobility environments, such as high-speed railway (HSR) as it depends on orthogonal frequency division multiplexing (OFDM) technology. Our aim in this paper is to reduce the Doppler shift effect in the 5G-R system environment by incorporating the orthogonal time frequency space (OTFS) technology. Recently, OTFS was introduced as an effective ICI canceler. We referred to this solution as the OTFS-based 5G-R system. In order to verify the effectiveness of the proposed solution, we compare its performance with that based on OFDM in different HSR environments using quadrature amplitude modulation (QAM) schemes. Further performance evaluation process was conducted including the use of two different equalization techniques at the receiving side. Matlab was used to implement the aforementioned solution. Results confirmed the superiority of the proposed solution since it shows lower BER values. Results also confirmed the effectiveness of the proposed solution in reducing the Doppler effect because it almost shows identical performance regardless the difference in speeds.
Abstract
The use of Grid Forming Methodology (GFM) in grid-connected systems represents an innovative approach to improving the stability and flexibility of power grids. This article will elucidate the methodology, assess its frequency-related performance and stability under disturbances like load changes, and ...
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The use of Grid Forming Methodology (GFM) in grid-connected systems represents an innovative approach to improving the stability and flexibility of power grids. This article will elucidate the methodology, assess its frequency-related performance and stability under disturbances like load changes, and emphasize the importance of the droop control coefficient. Based on the frequency derivative, which gives more information compared to the frequency, we used the rate of change of frequency (RoCoF) instead of frequency as an indicator to compare different scenarios and highlight differences in performance after changes in loads. The RoCoF factor and the critical clearing time are determined as metrics to compare system performance and stability. To determine the gain of the controller, the Result adaptive PID controller is performed, and its performance is compared to the classical PID controller based on the trial/error method. In the rest of the article, we relied on controlling the RAPID controller, which gave the best performance. Finally, theeffectiveness and accuracy of the method were verified through simulation.
Abstract
Multilevel inverters (MLIs) are commonly used in photovoltaic power stations, wind farms, and other forms of renewable energy generation. This study presents a new novel multi-gain switched capacitor (SC) based structural approach. The voltage gain of the proposed design (PD) can be increased threefold ...
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Multilevel inverters (MLIs) are commonly used in photovoltaic power stations, wind farms, and other forms of renewable energy generation. This study presents a new novel multi-gain switched capacitor (SC) based structural approach. The voltage gain of the proposed design (PD) can be increased threefold by utilizing two switching capacitors and nine switches. Additional significant benefits of the PD include lower voltage stress, an inherent self-balancing of the capacitor voltage, and a minimal amount of switching components. A backside H-bridge is not required to generate negative voltage levels. The PD provides a detailed explanation of the structural analysis, the self-balancing mechanism, the optimum capacitance value, and the control approach. In order to highlight the advantages of the PD, a fair comparison is presented with the most recent seven-level single-source topologies. Finally, Simulation results confirm the accuracy of the theoretical analysis and a prototype has been constructed to demonstrate that the practical findings are doable andsuccessful, with the efficiency tested reaching 96.95%.
