Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstruc...Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.展开更多
This paper stuides the structures of 4H SiC floating junction Schottky barrier diodes. Some structure parameters of devices are optimized with commercial simulator based on forward and reverse electrical characteristi...This paper stuides the structures of 4H SiC floating junction Schottky barrier diodes. Some structure parameters of devices are optimized with commercial simulator based on forward and reverse electrical characteristics. Compared with conventional power Schottky barrier diodes, the devices are featured by highly doped drift region and embedded floating junction layers, which can ensure high breakdown voltage while keeping lower specific on-state resistance, and solve the contradiction between forward voltage drop and breakdown voltage. The simulation results show that with optimized structure parameter, the breakdown voltage can reach 4.36 kV and the specific on-resistance is 5.8 mΩ.cm2 when the Baliga figure of merit value of 13.1 GW/cm2 is achieved.展开更多
In order to strengthen their security issues,electrical companies devote particular efforts to developing and enhancing their fraud detection techniques that cope with the information and communication technologies in...In order to strengthen their security issues,electrical companies devote particular efforts to developing and enhancing their fraud detection techniques that cope with the information and communication technologies integration in smart grid fields.Having been treated earlier by several researchers,various detection schemes adapted from attack models that benefit from the smart grid topologies weaknesses,aiming primarily to the identification of suspicious incoming hazards.Wireless meshes have been extensively used in smart grid communication architectures due to their facility,lightness of conception and low cost installation;however,the communicated packets are still exposed to be intercepted maliciously in order either to falsify pertinent information like the smart meter readings,or to inject false data instead,aiming at electricity theft during the communication phase.For this reason,this paper initiates a novel method based on RSA cryptographic algorithm to detect electricity fraud in smart grid.This new method consists of generating two different cryptograms of one electricity measurement before sending,after which the recipient is used to find the same value after decrypting the two cyphers in a normal case.Otherwise,a fraudulent manipulation could occur during the transmission stage.The presented method allows us to kill two birds with one stone.First,satisfactory outcomes are shown:the algorithm accuracy reaches 100%,from one hand,and the privacy is protected thanks to the cryptology concept on the other hand.展开更多
This paper proposes to study the impacts of electrical line losses due to the connection of distributed generators (DG) to 22kV distribution system of Provincial Electricity Authority (PEA). Data of geographic informa...This paper proposes to study the impacts of electrical line losses due to the connection of distributed generators (DG) to 22kV distribution system of Provincial Electricity Authority (PEA). Data of geographic information systems (GIS) including the distance of distribution line and location of load being key parameter of PEA is simulated using digital simulation and electrical network calculation program (DIgSILENT) to analyze power loss of the distribution system. In addition, the capacity and location of DG installed into the distribution system is considered. The results are shown that, when DG is installed close to the substation, the electrical line losses are reduced. However, if DG capacity becomes larger and the distance between DG and load is longer, the electrical line losses tend to increase. The results of this paper can be used to create the suitability and fairness of the fee for both DG and utility.展开更多
Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems.This study presents a new optimization method based on an unu...Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems.This study presents a new optimization method based on an unusual geological phenomenon in nature,named Geyser inspired Algorithm(GEA).The mathematical modeling of this geological phenomenon is carried out to have a better understanding of the optimization process.The efficiency and accuracy of GEA are verified using statistical examination and convergence rate comparison on numerous CEC 2005,CEC 2014,CEC 2017,and real-parameter benchmark functions.Moreover,GEA has been applied to several real-parameter engineering optimization problems to evaluate its effectiveness.In addition,to demonstrate the applicability and robustness of GEA,a comprehensive investigation is performed for a fair comparison with other standard optimization methods.The results demonstrate that GEA is noticeably prosperous in reaching the optimal solutions with a high convergence rate in comparison with other well-known nature-inspired algorithms,including ABC,BBO,PSO,and RCGA.Note that the source code of the GEA is publicly available at https://www.optim-app.com/projects/gea.展开更多
Three-dimensional holey nitrogen-doped carbon matrixes decorated with molybdenum dioxide(MoO_(2))nanoparticles have been successfully synthesized via a NaCl-assisted template strategy.The obtained MoO_(2)/C composites...Three-dimensional holey nitrogen-doped carbon matrixes decorated with molybdenum dioxide(MoO_(2))nanoparticles have been successfully synthesized via a NaCl-assisted template strategy.The obtained MoO_(2)/C composites offered multi-advantages,including higher specific surface area,more active sites,more ions/electrons transmission channels,and shorter transmission path due to the synergistic effect of the uniformly distributed MoO_(2) nanoparticles and porous carbon structure.Especially,the oxygen vacancies were introduced into the prepared composites and enhanced the Li^(+)intercalation/deintercalation process during electrochemical cycling by the Coulomb force.The existence of the local built-in electric field was proved by experimental data,differential charge density distribution,and density of states calculation.The uniquely designed structure and introduced oxygen vacancy defects endowed the MoO_(2)/C composites with excellent electrochemical properties.In view of the synergistic effect of the uniquely designed morphology and introduced oxygen vacancy defects,the MoO_(2)/C composites exhibited superior electrochemical performance of a high capacity of 918.2 mAh g^(-1) at 0.1 A g^(-1) after 130 cycles,562.1 mAh g^(-1) at 1.0 A g^(-1) after 1000 cycles,and a capacity of 181.25 mAh g^(-1) even at 20.0 A g^(-1).This strategy highlights the path to promote the commercial application of MoO_(2)-based and other transition metal oxide electrodes for energy storage devices.展开更多
The Firefly Algorithm(FA)is a highly efficient population-based optimization technique developed by mimicking the flashing behavior of fireflies when mating.This article proposes a method based on Differential Evoluti...The Firefly Algorithm(FA)is a highly efficient population-based optimization technique developed by mimicking the flashing behavior of fireflies when mating.This article proposes a method based on Differential Evolution(DE)/current-to-best/1 for enhancing the FA's movement process.The proposed modification increases the global search ability and the convergence rates while maintaining a balance between exploration and exploitation by deploying the global best solution.However,employing the best solution can lead to premature algorithm convergence,but this study handles this issue using a loop adjacent to the algorithm's main loop.Additionally,the suggested algorithm’s sensitivity to the alpha parameter is reduced compared to the original FA.The GbFA surpasses both the original and five-version of enhanced FAs in finding the optimal solution to 30 CEC2014 real parameter benchmark problems with all selected alpha values.Additionally,the CEC 2017 benchmark functions and the eight engineering optimization challenges are also utilized to evaluate GbFA’s efficacy and robustness on real-world problems against several enhanced algorithms.In all cases,GbFA provides the optimal result compared to other methods.Note that the source code of the GbFA algorithm is publicly available at https://www.optim-app.com/projects/gbfa.展开更多
Electric vehicles(EVs)have received special consideration from modern society over the past several years.Although EVs are a fine example of environmentally friendly technology and have many advantages,they relatively...Electric vehicles(EVs)have received special consideration from modern society over the past several years.Although EVs are a fine example of environmentally friendly technology and have many advantages,they relatively increase the electricity demand upon a power grid as well.Therefore,their negative impact on busvoltage and line losses should be analyzed.In this study,the effect of EV loads and their penetration on bus voltage and line losses of an IEEE-33 bussystem has been examined via two scenarios.It is important to mention that the effect of EVs on the rate of air pollution,produced by fossil fuel electricity generators,has been investigated throughout the study.Also,the key role of demand response programs in the reduction of EVs’negative effects on the grid has also been discussed in the last scenario.Generally,the simulation of this paper provides a novel and wider perspective on EVs and their effect on grids and environmental pollution.展开更多
With penetration growing of renewable energy sources which integrated into power system have caused problems on grid stability. Electric Vehicles (EV) are one of the renewable energy sources that can bring significant...With penetration growing of renewable energy sources which integrated into power system have caused problems on grid stability. Electric Vehicles (EV) are one of the renewable energy sources that can bring significant impacts to power system during their charging and discharging operations. This article established a model of single machine infinite bus (SMIB) power system considering EV as a case study of load disturbance for power system oscillation. The objective of this research is to enhance stability and overcome the drawbacks of traditional control algorithms such as power system stabilizer (PSS), PID controller and fuzzy logic controller (FLC). The implementation’s effect of FLC parallel with PID controller (Fuzzy-PID) has been shown in this paper. The speed deviation (?ω) and electrical power (Pe) are the important factors to be taken into consideration without EV (only change in mechanical torque), EV with change in the mechanical torque and sudden plug-in EV. The obtained result by nonlinear simulation using Matlab/Simulink of a SMIB power system with EV has shown the effectiveness of using (Fuzzy-PID) against all disturbances.展开更多
Electricity price forecasting(EPF)is important for energy system operations and management which include strategic bidding,generation scheduling,optimum storage reserves scheduling and systems analysis.Moreover,accura...Electricity price forecasting(EPF)is important for energy system operations and management which include strategic bidding,generation scheduling,optimum storage reserves scheduling and systems analysis.Moreover,accurate EPF is crucial for the purpose of bidding strategies and minimizing the risk for market participants in the competitive electricity market.Nevertheless,accurate time-series prediction of electricity price is very challenging due to complex nonlinearity in the trend of electricity price.This work proposes a mid-term forecasting model based on the demand and price data,renewable and non-renewable energy supplies,the seasonality and peak and off-peak hours of working and nonworking days.An optimized Gated Recurrent Unit(GRU)which incorporates Bagged Regression Tree(BTE)is developed in the Recurrent Neural Network(RNN)architecture for the mid-term EPF.Tanh layer is employed to optimize the hyperparameters of the heterogeneous GRU with the aim to improve the model’s performance,error reduction and predict the spikes.In this work,the proposed framework is assessed using electricity market data of five major economical states in Australia by using electricity market data from August 2020 to May 2021.The results showed significant improvement when adopting the proposed prediction framework compared to previous works in forecasting the electricity price.展开更多
The growing need for renewable energy and zero carbon dioxide emissions has fueled the development of thermoelectric generators with improved power generating capability.Along with the endeavor to develop thermoelectr...The growing need for renewable energy and zero carbon dioxide emissions has fueled the development of thermoelectric generators with improved power generating capability.Along with the endeavor to develop thermoelectric materials with greater figures of merit,the geometrical and structural optimization of thermoelectric generators is equally critical for maximum power output and efficiency.Green energy strategies that are constantly updated are a viable option for addressing the global energy issue while also protecting the environment.There have been significant focuses on the development of thermoelectric modules for a range of solar,automotive,military,and aerospace applications in recent years due to various advantages including as low vibration,great reliability and durability,and the absence of moving components.In order to enhance the system performance of the thermoelectric generator,an artificial neural network(ANN)based algorithm is proposed.Furthermore,to achieve high efficiency and system stability,a buck converter is designed and deployed.Simulation and experimental findings demonstrate that the suggested method is viable and available,and that it is almost similar to the real value in the steady state with the least power losses,making it ideal for vehicle exhaust thermoelectric generator applications.Furthermore,the proposed hybrid algorithm has a high reference value for the development of a dependable and efficient car exhaust thermoelectric generating system.展开更多
With the increasing development of EVs, the energy demand from theconventional utility grid increases in proportion. On the other hand, photovoltaic(PV) energy sources can overcome several problems when charging EVs f...With the increasing development of EVs, the energy demand from theconventional utility grid increases in proportion. On the other hand, photovoltaic(PV) energy sources can overcome several problems when charging EVs from theutility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PV array, a lithium-ion battery representing the EV battery, and alead-acid battery representing the energy storage system (ESS). A bidirectionalDC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging the EV battery. The proposed controllers achieve maximum power extraction from the PV and regulate the DC-linkvoltage. It also controls the voltage and current levels of both the ESS and the EVduring the charging/discharging process. The study has been applied to two caseswith different power levels. Analysis, simulation, and implementation of the proposed system are presented. A 120 W laboratory prototype is carried out to verifythe system performance, experimentally. Design guides for higher power levelsare proposed to help in choosing the proper parameters of the converters. Boththe simulation and experimental results are matched and verify the highperformance of the proposed system.展开更多
The research aimed to propose a non-destructive technology to control subterranean termites Coptotermes curvignathus Holmgren infestation based on electromagnetic waves. A portable apparatus for this technology has be...The research aimed to propose a non-destructive technology to control subterranean termites Coptotermes curvignathus Holmgren infestation based on electromagnetic waves. A portable apparatus for this technology has been built and its experiment is presented in this paper. Some electrical parameters were measured and analyzed along with their effects to the termites. The experiment using frequency range between 30 Hz - 600 kHz has been done. The average error of the apparatus by comparing the result with the direct measurement using oscilloscope was also measured. The highest error value appeared at 600 kHz with frequency error 6.05 kHz. The highest error of voltage (i.e. 0.186 Volt) appeared at 100 kHz. For safetiness, the highest magnetic field at 300 kHz was 0.1815 μT and at 500 kHz was 0.00725 μT which were safe for human. The average value of termites mortality was higher on irradiation time 120 minutes than 60 minutes respectively in all test frequency: 300 kHz, 400 kHz, 500 kHz and 600 kHz. This paper presents an important information of the electromagnatic-based technology for environmental friendly termites control in spite of using the insecticides.展开更多
The classical minimization of power losses in transmission lines is dominated by artificial intelligence techniques, which do not guarantee global optimum amidst local minima. Revolutionary and evolutionary techniques...The classical minimization of power losses in transmission lines is dominated by artificial intelligence techniques, which do not guarantee global optimum amidst local minima. Revolutionary and evolutionary techniques are encumbered with sophisticated transformations, which weaken the techniques. Power loss minimization is crucial to the efficient design and operation of power transmission lines. Minimization of losses is one way to meet steady grid supply, especially at peak demand. Thus, this paper has presented a gradient technique to obtain optimal variables and values from the power loss model, which efficiently minimizes power losses by modifying the traditional power loss model that combines Ohm and Corona losses. Optimality tests showed that the unmodified model does not support the minimization of power losses on transmission lines as the Hessian matrix portrayed the maximization of power losses. However, the modified model is consistent with the gradient method of optimization, which yielded optimum variables and values from the power loss model developed in this study. The unmodified (modified) models for Bujagali-Kawanda 220 kV and Masaka West-Mbarara North 132 kV transmission lines in Uganda showed maximum power losses of 0.406 (0.391) and 0.452 (0.446) kW/km/phase respectively. These results indicate that the modified model is superior to the unmodified model in minimizing power losses in the transmission lines and should be implemented for the efficient design and operation of power transmission lines within and outside Uganda for the same transmission voltages.展开更多
The FREEDM （future renewable electric energy delivery and management） system is a smart distribution system that facilitates seamless integration of high-penetration DRER （distributed renewable energy resources） a...The FREEDM （future renewable electric energy delivery and management） system is a smart distribution system that facilitates seamless integration of high-penetration DRER （distributed renewable energy resources） and DESD （distributed energy storage devices） with the existing distribution system. Protection schemes have been proposed to detect the overcurrent faults throughout the FREEDM system, according to its requirements. In this paper the time inverse directional over current protection coordination scheme is developed as a backup protection when the primary protection communication failed. The proposed scheme is applied to FREEDM network using conventional mathematical model. To speed up the fault clearing time without coordination loss, the settings of the proposed relays in the two directions are minimized using genetic algorithm. The developed methods are validated using ETAP software. The results ensure that the faults throughout the FREEDM system sections are detected and the relays tripping time are minimized.展开更多
This paper presented the simulation results of the three phase electrical systems supplied by four wires with power quality problems, to which the parallel 3-leg APF （active power filters） are connected. The purpose...This paper presented the simulation results of the three phase electrical systems supplied by four wires with power quality problems, to which the parallel 3-leg APF （active power filters） are connected. The purpose of this study is to analyze the results obtained in these conditions in order to observe the limits of the 3-leg active power filters and to form a foundation for the future studies of the 4-leg active power filters. For a complete analysis, the APF will be controlled by four control methods： synchronous reference system control, indirect control, instantaneous p-q theory control, and positive sequence control. The analysis will watch the power quality indicators： THD （total harmonic distortion factor）, PF （power factor）, Iunb （unbalance factor）.展开更多
Objective:To assess the effects of turmeric extract and its compounds on oxidative stress,inflammation,and apoptosis in acetaminophen-induced liver injury.Methods:HepG2 cells were administered with acetaminophen(40 mM...Objective:To assess the effects of turmeric extract and its compounds on oxidative stress,inflammation,and apoptosis in acetaminophen-induced liver injury.Methods:HepG2 cells were administered with acetaminophen(40 mM)to induce hepatotoxicity,followed by treatment with turmeric extract and its isolated compounds including curcumin,demethoxycurcumin,bis-demethoxycurcumin and ar-turmerone at 5,25,and 125μg/mL.IL-1β,IL-6,and IL-10 levels were quantified with ELISA kits.Further,qRT-PCR was used to analyze the mRNA expression of JNK,Casp-9,and Casp-3.Meanwhile,the levels of nitric oxide and lactate dehydrogenase were analyzed using colorimetric assay.Results:Acetaminophen administration caused an increase in the levels of lactate dehydrogenase,nitric oxide,IL-1β,IL-6,and the mRNA expression of JNK,Casp-9,and Casp-3 in HepG2 cells while reducing IL-10 levels.Treatment with turmeric extract,curcumin,demethoxycurcumin,bis-demethoxycurcumin,and ar-turmerone lowered IL-1β,IL-6,nitric oxide,and lactate dehydrogenase levels,downregulated the mRNA expression of JNK,Casp-9,and Casp-3,and increased IL-10 levels.Conclusions:Turmeric extract and its compounds have significant hepatoprotective activity and could be further explored for the treatment of liver damage.展开更多
Epilepsy is a long-term neurological condition marked by recurrent seizures,which result from abnormal electrical activity in the brain that disrupts its normal functioning.Traditional methods for detecting epilepsy t...Epilepsy is a long-term neurological condition marked by recurrent seizures,which result from abnormal electrical activity in the brain that disrupts its normal functioning.Traditional methods for detecting epilepsy through machine learning typically utilize discrete-time models,which inadequately represent the continuous dynamics of electroencephalogram(EEG)signals.To overcome this limitation,we introduce an innovative approach that employs Neural Ordinary Differential Equations(NODEs)to model EEG signals as continuous-time systems.This allows for effective management of irregular sampling and intricate temporal patterns.In contrast to conventional techniques,such as Convolutional Neural Networks(CNNs)and Recurrent Neural Networks(RNNs),which necessitate fixedlength inputs and often struggle with long-term dependencies,our framework incorporates:(1)a NODE block to capture continuous-time EEG dynamics,(2)a feature extraction module tailored for seizure-specific patterns,and(3)an attention-based fusion mechanism to enhance interpretability in classification.When evaluated on three publicly accessible EEG datasets,including those from Boston Children’s Hospital and the Massachusetts Institute of Technology(CHB-MIT)and the Temple University Hospital(TUH)EEG Corpus,the model demonstrated an average accuracy of 98.2%,a sensitivity of 97.8%,a specificity of 98.3%,and an F1-score of 97.9%.Additionally,the inference latency was reduced by approximately 30%compared to standard CNN and Long Short-Term Memory(LSTM)architectures,making it well-suited for real-time applications.The method’s resilience to noise and its adaptability to irregular sampling enhance its potential for clinical use in real-time settings.展开更多
We demonstrated a new type of MAX phase material,chromium titanium aluminum carbide(Cr_(2)TiAlC_(2)) polymer film,to generate a passively Q-switched erbium-doped fiber laser(EDFL).The film thickness was measured to be...We demonstrated a new type of MAX phase material,chromium titanium aluminum carbide(Cr_(2)TiAlC_(2)) polymer film,to generate a passively Q-switched erbium-doped fiber laser(EDFL).The film thickness was measured to be around 45 μm,which was fabricated using the embedding method with polyvinyl alcohol(PVA) polymer as hoster.The saturable absorber(SA) film demonstrates a dual-wavelength passively Q-switched EDFL which operates at 1 531 nm and 1 560.19 nm,respectively.The Q-switching pulse duration could be varied from 2.46 μs to 770 ns,while the repetition rate varied from 92.76 kHz to 106.6 kHz with an increasing input pumping range from 154 mW to 300 mW.The maximum output power and pulse energy of 15.05 mW and 141.18 nJ were obtained at the maximum input power of 300 mW,respectively.展开更多
Permanent Magnet Synchronous Motors(PMSMs)are widely employed in high-performance drive applications due to their superior efficiency and dynamic capabilities.However,their control remains challenging owing to nonline...Permanent Magnet Synchronous Motors(PMSMs)are widely employed in high-performance drive applications due to their superior efficiency and dynamic capabilities.However,their control remains challenging owing to nonlinear dynamics,parameter variations,and unmeasurable external disturbances,particularly load torquefluctuations.This study proposes an enhanced Interconnection and Damp-ing Assignment Passivity-Based Control(IDA-PBC)scheme,formulated within the port-controlled Hamiltonian(PCH)framework,to address these limitations.A nonlinear disturbance observer is embedded to estimate and compensate,in real time,for lumped mis-matched disturbances arising from parameter uncertainties and external loads.Additionally,aflatness-based control strategy is employed to generate the desired current references within the nonlinear drive system,ensuring accurate tracking of time-varying speed commands.This integrated approach preserves the system’s energy-based structure,enabling systematic stability analysis while enhancing robustness.The proposed control architecture also maintains low complexity with a limited number of tunable parameters,facilitating practical implementation.Simulation and experimental results under various operating conditions demonstrate the effectiveness and robustness of the proposed method.Comparative analysis with conventional proportional-integral(PI)control and standard IDA-PBC strategies confirms its capability to handle disturbances and maintain dynamic performance.展开更多
基金funded by the Directorate of Research and Community Service,Directorate General of Research and Development,Ministry of Higher Education,Science and Technologyin accordance with the Implementation Contract for the Operational Assistance Program for State Universities,Research Program Number:109/C3/DT.05.00/PL/2025.
文摘Sudden wildfires cause significant global ecological damage.While satellite imagery has advanced early fire detection and mitigation,image-based systems face limitations including high false alarm rates,visual obstructions,and substantial computational demands,especially in complex forest terrains.To address these challenges,this study proposes a novel forest fire detection model utilizing audio classification and machine learning.We developed an audio-based pipeline using real-world environmental sound recordings.Sounds were converted into Mel-spectrograms and classified via a Convolutional Neural Network(CNN),enabling the capture of distinctive fire acoustic signatures(e.g.,crackling,roaring)that are minimally impacted by visual or weather conditions.Internet of Things(IoT)sound sensors were crucial for generating complex environmental parameters to optimize feature extraction.The CNN model achieved high performance in stratified 5-fold cross-validation(92.4%±1.6 accuracy,91.2%±1.8 F1-score)and on test data(94.93%accuracy,93.04%F1-score),with 98.44%precision and 88.32%recall,demonstrating reliability across environmental conditions.These results indicate that the audio-based approach not only improves detection reliability but also markedly reduces computational overhead compared to traditional image-based methods.The findings suggest that acoustic sensing integrated with machine learning offers a powerful,low-cost,and efficient solution for real-time forest fire monitoring in complex,dynamic environments.
基金Project supported by the Open Fund of Key Laboratory of Wide Bandgap Semiconductor Materials and Devices, Ministry of Education of China
文摘This paper stuides the structures of 4H SiC floating junction Schottky barrier diodes. Some structure parameters of devices are optimized with commercial simulator based on forward and reverse electrical characteristics. Compared with conventional power Schottky barrier diodes, the devices are featured by highly doped drift region and embedded floating junction layers, which can ensure high breakdown voltage while keeping lower specific on-state resistance, and solve the contradiction between forward voltage drop and breakdown voltage. The simulation results show that with optimized structure parameter, the breakdown voltage can reach 4.36 kV and the specific on-resistance is 5.8 mΩ.cm2 when the Baliga figure of merit value of 13.1 GW/cm2 is achieved.
文摘In order to strengthen their security issues,electrical companies devote particular efforts to developing and enhancing their fraud detection techniques that cope with the information and communication technologies integration in smart grid fields.Having been treated earlier by several researchers,various detection schemes adapted from attack models that benefit from the smart grid topologies weaknesses,aiming primarily to the identification of suspicious incoming hazards.Wireless meshes have been extensively used in smart grid communication architectures due to their facility,lightness of conception and low cost installation;however,the communicated packets are still exposed to be intercepted maliciously in order either to falsify pertinent information like the smart meter readings,or to inject false data instead,aiming at electricity theft during the communication phase.For this reason,this paper initiates a novel method based on RSA cryptographic algorithm to detect electricity fraud in smart grid.This new method consists of generating two different cryptograms of one electricity measurement before sending,after which the recipient is used to find the same value after decrypting the two cyphers in a normal case.Otherwise,a fraudulent manipulation could occur during the transmission stage.The presented method allows us to kill two birds with one stone.First,satisfactory outcomes are shown:the algorithm accuracy reaches 100%,from one hand,and the privacy is protected thanks to the cryptology concept on the other hand.
文摘This paper proposes to study the impacts of electrical line losses due to the connection of distributed generators (DG) to 22kV distribution system of Provincial Electricity Authority (PEA). Data of geographic information systems (GIS) including the distance of distribution line and location of load being key parameter of PEA is simulated using digital simulation and electrical network calculation program (DIgSILENT) to analyze power loss of the distribution system. In addition, the capacity and location of DG installed into the distribution system is considered. The results are shown that, when DG is installed close to the substation, the electrical line losses are reduced. However, if DG capacity becomes larger and the distance between DG and load is longer, the electrical line losses tend to increase. The results of this paper can be used to create the suitability and fairness of the fee for both DG and utility.
文摘Over the past years,many efforts have been accomplished to achieve fast and accurate meta-heuristic algorithms to optimize a variety of real-world problems.This study presents a new optimization method based on an unusual geological phenomenon in nature,named Geyser inspired Algorithm(GEA).The mathematical modeling of this geological phenomenon is carried out to have a better understanding of the optimization process.The efficiency and accuracy of GEA are verified using statistical examination and convergence rate comparison on numerous CEC 2005,CEC 2014,CEC 2017,and real-parameter benchmark functions.Moreover,GEA has been applied to several real-parameter engineering optimization problems to evaluate its effectiveness.In addition,to demonstrate the applicability and robustness of GEA,a comprehensive investigation is performed for a fair comparison with other standard optimization methods.The results demonstrate that GEA is noticeably prosperous in reaching the optimal solutions with a high convergence rate in comparison with other well-known nature-inspired algorithms,including ABC,BBO,PSO,and RCGA.Note that the source code of the GEA is publicly available at https://www.optim-app.com/projects/gea.
基金financially supported by the National Natural Science Foundation of China(No.52207249)the research program of Top Talent Project of Yantai University(No.1115/2220001)+1 种基金the Yantai Basic Research Project(No.2022JCYJ04)the Science Fund of Shandong Laboratory of Advanced Materials and Green Manufacturing(No.AMGM2021F11).
文摘Three-dimensional holey nitrogen-doped carbon matrixes decorated with molybdenum dioxide(MoO_(2))nanoparticles have been successfully synthesized via a NaCl-assisted template strategy.The obtained MoO_(2)/C composites offered multi-advantages,including higher specific surface area,more active sites,more ions/electrons transmission channels,and shorter transmission path due to the synergistic effect of the uniformly distributed MoO_(2) nanoparticles and porous carbon structure.Especially,the oxygen vacancies were introduced into the prepared composites and enhanced the Li^(+)intercalation/deintercalation process during electrochemical cycling by the Coulomb force.The existence of the local built-in electric field was proved by experimental data,differential charge density distribution,and density of states calculation.The uniquely designed structure and introduced oxygen vacancy defects endowed the MoO_(2)/C composites with excellent electrochemical properties.In view of the synergistic effect of the uniquely designed morphology and introduced oxygen vacancy defects,the MoO_(2)/C composites exhibited superior electrochemical performance of a high capacity of 918.2 mAh g^(-1) at 0.1 A g^(-1) after 130 cycles,562.1 mAh g^(-1) at 1.0 A g^(-1) after 1000 cycles,and a capacity of 181.25 mAh g^(-1) even at 20.0 A g^(-1).This strategy highlights the path to promote the commercial application of MoO_(2)-based and other transition metal oxide electrodes for energy storage devices.
文摘The Firefly Algorithm(FA)is a highly efficient population-based optimization technique developed by mimicking the flashing behavior of fireflies when mating.This article proposes a method based on Differential Evolution(DE)/current-to-best/1 for enhancing the FA's movement process.The proposed modification increases the global search ability and the convergence rates while maintaining a balance between exploration and exploitation by deploying the global best solution.However,employing the best solution can lead to premature algorithm convergence,but this study handles this issue using a loop adjacent to the algorithm's main loop.Additionally,the suggested algorithm’s sensitivity to the alpha parameter is reduced compared to the original FA.The GbFA surpasses both the original and five-version of enhanced FAs in finding the optimal solution to 30 CEC2014 real parameter benchmark problems with all selected alpha values.Additionally,the CEC 2017 benchmark functions and the eight engineering optimization challenges are also utilized to evaluate GbFA’s efficacy and robustness on real-world problems against several enhanced algorithms.In all cases,GbFA provides the optimal result compared to other methods.Note that the source code of the GbFA algorithm is publicly available at https://www.optim-app.com/projects/gbfa.
文摘Electric vehicles(EVs)have received special consideration from modern society over the past several years.Although EVs are a fine example of environmentally friendly technology and have many advantages,they relatively increase the electricity demand upon a power grid as well.Therefore,their negative impact on busvoltage and line losses should be analyzed.In this study,the effect of EV loads and their penetration on bus voltage and line losses of an IEEE-33 bussystem has been examined via two scenarios.It is important to mention that the effect of EVs on the rate of air pollution,produced by fossil fuel electricity generators,has been investigated throughout the study.Also,the key role of demand response programs in the reduction of EVs’negative effects on the grid has also been discussed in the last scenario.Generally,the simulation of this paper provides a novel and wider perspective on EVs and their effect on grids and environmental pollution.
文摘With penetration growing of renewable energy sources which integrated into power system have caused problems on grid stability. Electric Vehicles (EV) are one of the renewable energy sources that can bring significant impacts to power system during their charging and discharging operations. This article established a model of single machine infinite bus (SMIB) power system considering EV as a case study of load disturbance for power system oscillation. The objective of this research is to enhance stability and overcome the drawbacks of traditional control algorithms such as power system stabilizer (PSS), PID controller and fuzzy logic controller (FLC). The implementation’s effect of FLC parallel with PID controller (Fuzzy-PID) has been shown in this paper. The speed deviation (?ω) and electrical power (Pe) are the important factors to be taken into consideration without EV (only change in mechanical torque), EV with change in the mechanical torque and sudden plug-in EV. The obtained result by nonlinear simulation using Matlab/Simulink of a SMIB power system with EV has shown the effectiveness of using (Fuzzy-PID) against all disturbances.
基金funded by Universiti Malaya research grant from Malaysia under the project name‘Intelligent Price Forecasting System for Optimal Energy Market’with grant number ST005-2021.
文摘Electricity price forecasting(EPF)is important for energy system operations and management which include strategic bidding,generation scheduling,optimum storage reserves scheduling and systems analysis.Moreover,accurate EPF is crucial for the purpose of bidding strategies and minimizing the risk for market participants in the competitive electricity market.Nevertheless,accurate time-series prediction of electricity price is very challenging due to complex nonlinearity in the trend of electricity price.This work proposes a mid-term forecasting model based on the demand and price data,renewable and non-renewable energy supplies,the seasonality and peak and off-peak hours of working and nonworking days.An optimized Gated Recurrent Unit(GRU)which incorporates Bagged Regression Tree(BTE)is developed in the Recurrent Neural Network(RNN)architecture for the mid-term EPF.Tanh layer is employed to optimize the hyperparameters of the heterogeneous GRU with the aim to improve the model’s performance,error reduction and predict the spikes.In this work,the proposed framework is assessed using electricity market data of five major economical states in Australia by using electricity market data from August 2020 to May 2021.The results showed significant improvement when adopting the proposed prediction framework compared to previous works in forecasting the electricity price.
文摘The growing need for renewable energy and zero carbon dioxide emissions has fueled the development of thermoelectric generators with improved power generating capability.Along with the endeavor to develop thermoelectric materials with greater figures of merit,the geometrical and structural optimization of thermoelectric generators is equally critical for maximum power output and efficiency.Green energy strategies that are constantly updated are a viable option for addressing the global energy issue while also protecting the environment.There have been significant focuses on the development of thermoelectric modules for a range of solar,automotive,military,and aerospace applications in recent years due to various advantages including as low vibration,great reliability and durability,and the absence of moving components.In order to enhance the system performance of the thermoelectric generator,an artificial neural network(ANN)based algorithm is proposed.Furthermore,to achieve high efficiency and system stability,a buck converter is designed and deployed.Simulation and experimental findings demonstrate that the suggested method is viable and available,and that it is almost similar to the real value in the steady state with the least power losses,making it ideal for vehicle exhaust thermoelectric generator applications.Furthermore,the proposed hybrid algorithm has a high reference value for the development of a dependable and efficient car exhaust thermoelectric generating system.
基金funded by the Deanship of Scientific Research,Taif University,KSA(Research project number 1-441-99).
文摘With the increasing development of EVs, the energy demand from theconventional utility grid increases in proportion. On the other hand, photovoltaic(PV) energy sources can overcome several problems when charging EVs from theutility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PV array, a lithium-ion battery representing the EV battery, and alead-acid battery representing the energy storage system (ESS). A bidirectionalDC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging the EV battery. The proposed controllers achieve maximum power extraction from the PV and regulate the DC-linkvoltage. It also controls the voltage and current levels of both the ESS and the EVduring the charging/discharging process. The study has been applied to two caseswith different power levels. Analysis, simulation, and implementation of the proposed system are presented. A 120 W laboratory prototype is carried out to verifythe system performance, experimentally. Design guides for higher power levelsare proposed to help in choosing the proper parameters of the converters. Boththe simulation and experimental results are matched and verify the highperformance of the proposed system.
文摘The research aimed to propose a non-destructive technology to control subterranean termites Coptotermes curvignathus Holmgren infestation based on electromagnetic waves. A portable apparatus for this technology has been built and its experiment is presented in this paper. Some electrical parameters were measured and analyzed along with their effects to the termites. The experiment using frequency range between 30 Hz - 600 kHz has been done. The average error of the apparatus by comparing the result with the direct measurement using oscilloscope was also measured. The highest error value appeared at 600 kHz with frequency error 6.05 kHz. The highest error of voltage (i.e. 0.186 Volt) appeared at 100 kHz. For safetiness, the highest magnetic field at 300 kHz was 0.1815 μT and at 500 kHz was 0.00725 μT which were safe for human. The average value of termites mortality was higher on irradiation time 120 minutes than 60 minutes respectively in all test frequency: 300 kHz, 400 kHz, 500 kHz and 600 kHz. This paper presents an important information of the electromagnatic-based technology for environmental friendly termites control in spite of using the insecticides.
文摘The classical minimization of power losses in transmission lines is dominated by artificial intelligence techniques, which do not guarantee global optimum amidst local minima. Revolutionary and evolutionary techniques are encumbered with sophisticated transformations, which weaken the techniques. Power loss minimization is crucial to the efficient design and operation of power transmission lines. Minimization of losses is one way to meet steady grid supply, especially at peak demand. Thus, this paper has presented a gradient technique to obtain optimal variables and values from the power loss model, which efficiently minimizes power losses by modifying the traditional power loss model that combines Ohm and Corona losses. Optimality tests showed that the unmodified model does not support the minimization of power losses on transmission lines as the Hessian matrix portrayed the maximization of power losses. However, the modified model is consistent with the gradient method of optimization, which yielded optimum variables and values from the power loss model developed in this study. The unmodified (modified) models for Bujagali-Kawanda 220 kV and Masaka West-Mbarara North 132 kV transmission lines in Uganda showed maximum power losses of 0.406 (0.391) and 0.452 (0.446) kW/km/phase respectively. These results indicate that the modified model is superior to the unmodified model in minimizing power losses in the transmission lines and should be implemented for the efficient design and operation of power transmission lines within and outside Uganda for the same transmission voltages.
文摘The FREEDM （future renewable electric energy delivery and management） system is a smart distribution system that facilitates seamless integration of high-penetration DRER （distributed renewable energy resources） and DESD （distributed energy storage devices） with the existing distribution system. Protection schemes have been proposed to detect the overcurrent faults throughout the FREEDM system, according to its requirements. In this paper the time inverse directional over current protection coordination scheme is developed as a backup protection when the primary protection communication failed. The proposed scheme is applied to FREEDM network using conventional mathematical model. To speed up the fault clearing time without coordination loss, the settings of the proposed relays in the two directions are minimized using genetic algorithm. The developed methods are validated using ETAP software. The results ensure that the faults throughout the FREEDM system sections are detected and the relays tripping time are minimized.
文摘This paper presented the simulation results of the three phase electrical systems supplied by four wires with power quality problems, to which the parallel 3-leg APF （active power filters） are connected. The purpose of this study is to analyze the results obtained in these conditions in order to observe the limits of the 3-leg active power filters and to form a foundation for the future studies of the 4-leg active power filters. For a complete analysis, the APF will be controlled by four control methods： synchronous reference system control, indirect control, instantaneous p-q theory control, and positive sequence control. The analysis will watch the power quality indicators： THD （total harmonic distortion factor）, PF （power factor）, Iunb （unbalance factor）.
基金funded by Maranatha Christian University,Bandung,Indonesia for Productive Lecturer Research under grant number:011/SK/ADD/UKM/IV/2024.
文摘Objective:To assess the effects of turmeric extract and its compounds on oxidative stress,inflammation,and apoptosis in acetaminophen-induced liver injury.Methods:HepG2 cells were administered with acetaminophen(40 mM)to induce hepatotoxicity,followed by treatment with turmeric extract and its isolated compounds including curcumin,demethoxycurcumin,bis-demethoxycurcumin and ar-turmerone at 5,25,and 125μg/mL.IL-1β,IL-6,and IL-10 levels were quantified with ELISA kits.Further,qRT-PCR was used to analyze the mRNA expression of JNK,Casp-9,and Casp-3.Meanwhile,the levels of nitric oxide and lactate dehydrogenase were analyzed using colorimetric assay.Results:Acetaminophen administration caused an increase in the levels of lactate dehydrogenase,nitric oxide,IL-1β,IL-6,and the mRNA expression of JNK,Casp-9,and Casp-3 in HepG2 cells while reducing IL-10 levels.Treatment with turmeric extract,curcumin,demethoxycurcumin,bis-demethoxycurcumin,and ar-turmerone lowered IL-1β,IL-6,nitric oxide,and lactate dehydrogenase levels,downregulated the mRNA expression of JNK,Casp-9,and Casp-3,and increased IL-10 levels.Conclusions:Turmeric extract and its compounds have significant hepatoprotective activity and could be further explored for the treatment of liver damage.
基金extend their appreciation to the King Salman Center for Disability Research for funding this work through Research Group No.KSRG-2024-223.
文摘Epilepsy is a long-term neurological condition marked by recurrent seizures,which result from abnormal electrical activity in the brain that disrupts its normal functioning.Traditional methods for detecting epilepsy through machine learning typically utilize discrete-time models,which inadequately represent the continuous dynamics of electroencephalogram(EEG)signals.To overcome this limitation,we introduce an innovative approach that employs Neural Ordinary Differential Equations(NODEs)to model EEG signals as continuous-time systems.This allows for effective management of irregular sampling and intricate temporal patterns.In contrast to conventional techniques,such as Convolutional Neural Networks(CNNs)and Recurrent Neural Networks(RNNs),which necessitate fixedlength inputs and often struggle with long-term dependencies,our framework incorporates:(1)a NODE block to capture continuous-time EEG dynamics,(2)a feature extraction module tailored for seizure-specific patterns,and(3)an attention-based fusion mechanism to enhance interpretability in classification.When evaluated on three publicly accessible EEG datasets,including those from Boston Children’s Hospital and the Massachusetts Institute of Technology(CHB-MIT)and the Temple University Hospital(TUH)EEG Corpus,the model demonstrated an average accuracy of 98.2%,a sensitivity of 97.8%,a specificity of 98.3%,and an F1-score of 97.9%.Additionally,the inference latency was reduced by approximately 30%compared to standard CNN and Long Short-Term Memory(LSTM)architectures,making it well-suited for real-time applications.The method’s resilience to noise and its adaptability to irregular sampling enhance its potential for clinical use in real-time settings.
文摘We demonstrated a new type of MAX phase material,chromium titanium aluminum carbide(Cr_(2)TiAlC_(2)) polymer film,to generate a passively Q-switched erbium-doped fiber laser(EDFL).The film thickness was measured to be around 45 μm,which was fabricated using the embedding method with polyvinyl alcohol(PVA) polymer as hoster.The saturable absorber(SA) film demonstrates a dual-wavelength passively Q-switched EDFL which operates at 1 531 nm and 1 560.19 nm,respectively.The Q-switching pulse duration could be varied from 2.46 μs to 770 ns,while the repetition rate varied from 92.76 kHz to 106.6 kHz with an increasing input pumping range from 154 mW to 300 mW.The maximum output power and pulse energy of 15.05 mW and 141.18 nJ were obtained at the maximum input power of 300 mW,respectively.
基金supported in part by an International Research Partnership“Electrical Engineering-Thai French Research Center(EE-TFRC)”under the project framework of the Lorraine Universite´d’Excellence(LUE)in cooperation between Universite´de Lorraine(France)and King Mongkut’s University of Technology North Bangkok(year 2021-2024/2025-28)by the National Research Council of Thailand(NRCT)under Research Team Promotion Grant(Senior Research Scholar Program)under Grant No.N42A 680561by the NSRF via the Program Management Unit for Human Resources&Institutional Development,Research and Innovation under Research project Grant No.B41G680025.
文摘Permanent Magnet Synchronous Motors(PMSMs)are widely employed in high-performance drive applications due to their superior efficiency and dynamic capabilities.However,their control remains challenging owing to nonlinear dynamics,parameter variations,and unmeasurable external disturbances,particularly load torquefluctuations.This study proposes an enhanced Interconnection and Damp-ing Assignment Passivity-Based Control(IDA-PBC)scheme,formulated within the port-controlled Hamiltonian(PCH)framework,to address these limitations.A nonlinear disturbance observer is embedded to estimate and compensate,in real time,for lumped mis-matched disturbances arising from parameter uncertainties and external loads.Additionally,aflatness-based control strategy is employed to generate the desired current references within the nonlinear drive system,ensuring accurate tracking of time-varying speed commands.This integrated approach preserves the system’s energy-based structure,enabling systematic stability analysis while enhancing robustness.The proposed control architecture also maintains low complexity with a limited number of tunable parameters,facilitating practical implementation.Simulation and experimental results under various operating conditions demonstrate the effectiveness and robustness of the proposed method.Comparative analysis with conventional proportional-integral(PI)control and standard IDA-PBC strategies confirms its capability to handle disturbances and maintain dynamic performance.
