The vulnerability of distribution systems to frequent fault occurrences creates considerable issues, particularly when distributed generators (DG) are used. The standard relaying method struggles to adequately manage ...
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The vulnerability of distribution systems to frequent fault occurrences creates considerable issues, particularly when distributed generators (DG) are used. The standard relaying method struggles to adequately manage these complications, which are exacerbated by the radial system’s change owing to the existence of various sources. These deficiencies erode the existing protection framework, making the system vulnerable to a variety of faults that, if left untreated, might cause serious damage and significant disruptions. Prompt fault clearing and system restoration are critical for maintaining distribution network reliability and price stability. Delays in detecting and localizing faults have a direct impact on a country’s overall development. As a result, classifying the fault and predicting its exact location as soon as possible is crucial. Researchers have investigated many fault categorization and localization methods, which are broadly classed as traditional and artificial intelligence (AI) methodologies. Existing approaches, on the other hand, frequently ignore variations in source impedance during faults, resulting in less accurate fault type identification. Although fault localization accuracy has been sufficient in most circumstances, there is still room for significant improvement in fault type classification. As a result, this study suggests using a K-nearest neighbor (KNN) approach to improve fault categorization in distribution networks with several DGs. The suggested method is based on extensive fault data gathered from various locations and derived through short-circuit and steady-state analysis. To evaluate the efficiency of the proposed strategy, modeling and simulations were carried out using MATLAB Simulink. Finally, we give a thorough comparison of the outcomes of our suggested strategy and previously used data classifying approaches. The findings demonstrate the superiority and efficacy of the KNN-based method, emphasizing its potential to greatl
The primary motivation behind this study is the aspiration to design a prosthetic foot that demonstrates enhanced functionality, enabling more active and prompt responses, particularly tailored for individuals with be...
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We investigate sequential time series data through ensemble learning. Conventional ensemble algorithms and the recently introduced ones have provided significant performance improvements in widely publicized time seri...
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This study presents a robust path-tracking controller for vehicles with parameter uncertainties using a Takagi-Sugeno (T-S) fuzzy observer-based control scheme. First, the path-tracking system and the observer are rep...
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This paper evaluates the need for corrugated boxes in the industry & the need for fast and efficient manufacturing of such boxes, even at a small scale. Nowadays, online shopping is increasing at a tremendous rate...
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A distributed power system holds distinct advantages over its traditional centralized counterpart. However, when considering protection aspects, the inclusion of distributed generators warrants heightened attention du...
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A distributed power system holds distinct advantages over its traditional centralized counterpart. However, when considering protection aspects, the inclusion of distributed generators warrants heightened attention due to potential challenges such as stability loss, re-closure failures, voltage deviations, and related factors. The complication is further exacerbated in the presence of short circuit occurrences. Therefore, the precise identification of the fault’s location and nature becomes paramount, particularly when situated within a compact and dispersed generation setup. Swift and accurate fault identification assumes heightened significance, given its potential to adversely impact the entire system’s functionality and performance. Numerous methodologies have been formulated in the past to ascertain both the location and type of faults within distributed generation systems. While several of these approaches have yielded commendable outcomes in pinpointing fault locations, their reliability in accurately identifying the specific fault type remains an area that necessitates substantial enhancement. This research introduces a shallow artificial neural network (sANN) model designed to identify specific types of failures that may occur in a basic distribution network when integrated with a distributed generation system. The study commences by modeling a distribution system consisting of multiple distributed generators, a grid, and a distribution line. Various fault scenarios at different locations are simulated to collect voltage and current data, resulting in a 500 × 18 dataset matrix. Subsequent to this, the shallow Artificial Neural Network (sANN) is meticulously formulated to discern and categorize distinct fault types present within the system. The accumulated data is harnessed to meticulously train, validate, and assess the neural network’s performance. The comprehensive outcomes exhibit an exemplary error rate of almost 0%, showcasing the remarkable precision
This article presents an open-loop fractional output divider (FOD) that employs a replica-digital-to-time converter (DTC)-free background calibration. To support fractional division operation, the divider is modulated...
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In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies ...
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In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.
Integration of hydrogen into the existing natural gas infrastructure is considered a potential pathway that can accelerate the incorporation of hydrogen into the energy sector. While blending renewable hydrogen with n...
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The introduction of several small and large-scale industries,malls,shopping complexes,and domestic applications has significantly increased energy *** aim of the work is to simulate a technically viable and economical...
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The introduction of several small and large-scale industries,malls,shopping complexes,and domestic applications has significantly increased energy *** aim of the work is to simulate a technically viable and economically optimum hybrid power system for residential *** proposed micro-grid model includes four power generators:solar power,wind power,Electricity Board(EB)source,and a Diesel Generator(DG)set,with solar and wind power performing as major sources and the EB supply and DG set serving as backup *** core issue in direct current to alternate current conversion is harmonics distortion,a five-stage multilevel inverter is employed with the assistance of an intelligent control system is simulated and the optimum system configuration is estimated to reduce harmonics and improve the power *** monthly demand for residential buildings is 13-15 ***,almost 433 Kilo-Watts(KW)of electricity is required every day,and if it is used for 8 h per day,50-60 KW of electricity is needed per *** overall micro-grid model’s operation and performance are established using MATLAB/SIMULINK software,and simulation results are *** simulation results show that the developed system is both cost-effective and environment friendly resulting in yearly cost reductions.
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