Smart Science最新文献

{"title":"MFCDFT and impedance characteristic-based adaptive technique for fault and power swing discrimination","authors":"Pankaj H. Vasava, Dharmesh D. Patel, Nilesh G. Chothani, Sanjay Joshi","doi":"10.1080/23080477.2023.2298538","DOIUrl":"https://doi.org/10.1080/23080477.2023.2298538","url":null,"abstract":"","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"14 23","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139388891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Frequency and voltage stability of multi microgrid system using 2-DOF TIDF FUZZY controller","authors":"Gyana Ranjan Biswal, B. Mohanty","doi":"10.1080/23080477.2023.2297550","DOIUrl":"https://doi.org/10.1080/23080477.2023.2297550","url":null,"abstract":"","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"6 16","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-based fault recognition and classification in the IEEE 9-bus system interconnected to PV systems","authors":"Hinal Shah, Nilesh G. Chothani, Jaydeep Chakravorty","doi":"10.1080/23080477.2023.2285275","DOIUrl":"https://doi.org/10.1080/23080477.2023.2285275","url":null,"abstract":"","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"268 ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139242885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cost-emission based scheme for residential energy hub management considering comfortable lifestyle and responsible demand","authors":"Zohre Salmani, Mahyar Lasemi Imeni, M. Ghazizadeh, Mohammad Ali Lasemi","doi":"10.1080/23080477.2023.2285420","DOIUrl":"https://doi.org/10.1080/23080477.2023.2285420","url":null,"abstract":"","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"70 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139257164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent faults diagnostics of turbine vibration’s via Fourier transform and neuro-fuzzy systems with wavelets exploitation","authors":"Nadji Hadroug, Abdelhamid Iratni, Ahmed Hafaifa, Ilhami Colak","doi":"10.1080/23080477.2023.2281734","DOIUrl":"https://doi.org/10.1080/23080477.2023.2281734","url":null,"abstract":"ABSTRACTGas turbines play a vital role in gas transportation and power generation, but they are prone to instability phenomena that can lead to vibrations, shorten equipment lifespan, and result in catastrophic failures. To tackle these challenges, a paper introduces an integrated approach that leverages advanced techniques like Fourier transform, Neuro-Fuzzy systems, and wavelet analysis for continuous monitoring of the MS5002C turbine’s condition. The proposed method begins by collecting operational data and utilizing the Fourier transform to measure vibratory quantities, accurately representing their evolution through spectral data obtained from the analyzed signals. Adaptive inference-based algorithms of neuro-fuzzy systems are then employed to generate turbine failure indicators. This approach enables the development of a model-based fault detection method that compares the actual turbine operation with the estimated operation derived from a pre-established model, enabling the classification of detected faults. To enhance decision-making quality, evaluation, and validation of the diagnostic strategy’s performance, a multi-resolution analysis based on the wavelet transform is applied. The presented results from various implementation and validation tests demonstrate the effectiveness of this intelligent diagnostic approach in detecting and analyzing gas turbine vibrations. The paper exhibits promising outcomes in real-time monitoring, ensuring the operational safety of the turbine.KEYWORDS: fault diagnosticsgas turbinevibrations instabilitiesFourier transformneuro-fuzzy systemswavelets Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"53 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135036768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal energy mix with renewable penetration for Masirah Island, Oman","authors":"Abdullah Al Badi, Arif S. Malik","doi":"10.1080/23080477.2023.2278365","DOIUrl":"https://doi.org/10.1080/23080477.2023.2278365","url":null,"abstract":"ABSTRACTElectrical power generation in Oman depends mainly on natural gas, while in rural areas it is based mainly on diesel fuel. Oman has committed to net-zero emissions by 2050, in line with the Paris Agreement’s goal of limiting global warming to 1.5°C. The objective of this paper is to propose an optimal energy mix model for electricity generation from various energy sources, such as gas, diesel, wind, and photovoltaic, that considers more renewable sources in the energy mix. The optimization model minimizes various costs such as construction cost, operation cost, fuel cost, and carbon emissions, while satisfying the load demand. In this paper, Masirah Island is selected to perform our analysis. Several scenarios are contemplated, including grid extension to the island. The results found that gas-powered generators with 20% PV and storage are the best option in terms of the levelized cost of electricity. The grid extension is an economically feasible option if the existing load is more than doubled.KEYWORDS: OmanMasirah Islandrural areasrenewable sourcesenergy mixgrid extension Disclosure statementNo potential conflict of interest was reported by the author(s).Authors’ contributions Al Badi wrote the paper and did Homer AnalysisMalik wrote the optimization part and did the grid analysisBoth of them reviewed the paperAvailability of data and materialsThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":" 47","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135290619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiverse optimized ANFIS scheduled fractional ordered proportional-integral-derivative controller for mitigation of frequency excursions in AC microgrid coupled with electric vehicles","authors":"Amandeep Singh, Sathans Suhag","doi":"10.1080/23080477.2023.2273666","DOIUrl":"https://doi.org/10.1080/23080477.2023.2273666","url":null,"abstract":"ABSTRACTOwing to the current environmental concerns, the RESs have become popular as the microgrid structures for power generation. However, due to capricious weather and loading conditions, the generated power and thereby the microgrid frequency get adversely affected. This instant study puts forth the control strategy for the mitigation of frequency excursions, arising out of step load disturbance, in AC microgrid through adaptive network fuzzy inference system (ANFIS) scheduled fractional ordered proportional-integral-derivative (PID) control optimally tuned with a multiverse optimizer. The control strategy proposition is compared against multi-verse optimized PID and fractional order PI controls. Furthermore, the study investigates as to how EV affects in stabilizing the system frequency in the backdrop of a load disturbance. For a more realistic assessment, the proposition is assessed in the face of system nonlinearities and random load perturbations also to establish its robust and stable behavior. The results prove the efficacy of the multi-verse optimized ANFIS scheduled fractional ordered PID controller. Simulations are executed using MATLAB® software. The results are also validated by experimental studies employing a hardware-in-loop configuration on the OPAL-RT real-time simulator.KEYWORDS: Microgridrenewable energy systemenergy storage systemfrequency excursionsfractional-ordered controller Disclosure statementNo potential conflict of interest was reported by the author(s).Nomenclature Abbreviation=ANFIS=Adaptive Network Fuzzy Inference SystemFOPID=Fractional-Ordered Proportional-Integral-DerivativeEV=Electric VehicleICA=Imperialist Competition AlgorithmBESS=Battery Energy Storage SystemMC=Microsource ControllerMVO=Multiverse OptimizerRES=Renewable Energy SourcesV2G=Vehicle to GridDER=Distributed Energy ResourcesAGC=Automatic Generation ControlFESS=Flywheel Energy Storage SystemCES=Capacitive Energy StoragePSO=Particle Swarm OptimizationLFC=Load Frequency ControlCOA=Coyote Optimization AlgorithmESS=Energy Storage SystemsGOA=Grasshopper Optimization AlgorithmDG=Distributed GenerationMPC=Model Predictive ControlPV=PhotovoltaicWTG=Wind Turbine GeneratorMGCC=Microgrid Central ControllerLC=Load ControllerITAE=Integral of Time multiplied Absolute ErrorFC=Fuel CellPEV=Plug-in EVLCC=Local Control CentreISE=Integral of Squared ErrorMF=Membership FunctionsLSE=Least Squares ErrorDEG=Diesel Engine GeneratorBP=BackPropagationALO=Ant Lion OptimizationFIS=Fuzzy Inference SystemSMES=Superconducting Magnetic Energy StoragePCC=Point of Common CouplingDE=Differential EvolutionIAE=Integral of Absolute ErrorTLBO=Teaching–Learning-Based OptimizationSSA=Salp Swarm AlgorithmSubscripts=Tg=Generator Time ConstantTI/c=Interconnection Device Time ConstantTIN=Inverter Time ConstantTt=Turbine ConstantKP=Proportional GainD=Damping CoefficientKI=Integral GainR=Droop ConstantKD=Derivative GainH=Inertia ConstantΛ=Order of IntegratorTBESS=BESS Time Constantµ=Order of D","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"16 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135813312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Face manipulated deepfake generation and recognition approaches: a survey","authors":"Mansi Rehaan, Nirmal Kaur, Staffy Kingra","doi":"10.1080/23080477.2023.2268380","DOIUrl":"https://doi.org/10.1080/23080477.2023.2268380","url":null,"abstract":"ABSTRACTWith the progression of deep-learning techniques, digital media recording and synthesis media generation have become exceptionally easy. Due to open access of user-friendly deepfaking applications generated using Artificial Intelligence methods especially Generative Adversarial Networks (GANs) and Variational Auto-encoders (VAEs), synthesis of recorded media has been made more effortless. Digital media synthesized using such applications is termed as deepfake. Generation of realistic fake audio/video content poses critical threats to an individual and society at large. To curb the threat of deepfaking, numerous deepfake detection algorithms have been proposed. This paper presents a survey on state-of-the-art deepfake generation techniques, categorized into face swap, attribute manipulation, and lip-sync manipulation. An analysis of some recently developed techniques that can generate images from text is also presented in the proposed paper. In addition, state-of-art image and video datasets released in the domain of deepfake detection are also discussed. The analysis provided in this survey reveals that every new deepfake generation technique calls for the development of novel deepfake detection techniques. Among deepfake detection techniques proposed so far, MobileNet-CNN model, multi-scale temporal CNN model, and GAN-based technique outperform good for face swap, lip-syncing, and attribute manipulation detection with an accuracy of 99.28%, 97.1% ,and 100%, respectively. This survey would help researchers to understand the literature on deepfake generation and detection which is required for future development in this field.KEYWORDS: Face swapattribute manipulationlip-syncingdeepfake Datasets Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"5 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136067603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discrete-time state delayed systems with saturation arithmetic: overflow oscillation-free realization","authors":"Satya Krishna Murthy Kanithi, Kalpana Singh, V. Krishna Rao Kandanvli, Haranath Kar","doi":"10.1080/23080477.2023.2264569","DOIUrl":"https://doi.org/10.1080/23080477.2023.2264569","url":null,"abstract":"ABSTRACTIn many smart systems, such as cloud computing, networked control, manufacturing, and telecommunication, the effects of time delays are unavoidable. Saturation nonlinearity is common in many smart systems (e.g. electric systems with limited actuator power supplies, mechanical systems with position and speed constraints, fixed-point digital filters, etc.). Therefore, the study of stability of discrete-time systems (DTSs) with time delay and saturation is of high importance in practice. The global asymptotic stability (GAS) problem of such systems is investigated in this paper. The saturation nonlinearity is constrained by a convex hull with a free matrix whose infinity norm is smaller than or equal to unity. A new Lyapunov-based GAS criterion for DTSs with time-varying delay and state saturation is established. The GAS problem for DTSs with constant delay and saturation is also discussed. The obtained results can be used to ensure the absence of overflow oscillations in the considered system. In comparison to several existing criteria, the approach yields improved stability results. An example is provided to demonstrate the importance of the presented results.KEYWORDS: Asymptotic stabilitydelayed systemdiscrete-time systemstate saturation AcknowledgmentsThe authors would like to thank the Editor-in-Chief and anonymous reviewers for their constructive comments on the manuscript.Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135166597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GWO- and SSA-Tuned PID Control for Frequency Regulation in Multi-Area PowerNetwork Integrated with Plug-in Electric Vehicle","authors":"Gunjan Chorasiya, Vinod Kumar, Sathans Suhag","doi":"10.1080/23080477.2023.2270668","DOIUrl":"https://doi.org/10.1080/23080477.2023.2270668","url":null,"abstract":"ABSTRACTThe Plug-in Electric Vehicles (PEVs) can be influential in containing power system frequency fluctuations. This study, therefore, investigates the efficacy of frequency regulation for PEV-integrated multi-area power network using Grey Wolf Optimizer (GWO) and Salp Swarm Algorithm (SSA) optimized Proportional-Integral-Derivative (PID) control. Instant investigation not only brings out the relative competence of GWO and SSA but also examines the impact of PEV in improving the system performance. The varying operating conditions are realized by subjecting the system to step and random load variations in either or both of the areas. With the proposed control scheme and involvement of PEV, system frequency and tie-line power excursions settle quicker with their peak swings also getting restricted to a lower value, while the oscillations are arrested as well to a great extent. Further, it’s the SSA that shows its superiority over GWO as per the simulation results executed in MATLAB.KEYWORDS: Multi-area power systemSalp Swarm Algorithm (SSA)frequency excursionsGrey Wolf Optimizer (GWO)Plug-in Electric Vehicles (PEVs) Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":"40 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135273220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}