This paper investigates support vector machine based fault type and distance estimation scheme in a long transmission line. The planned technique uses post single cycle current waveform pre-processing of the samples is done by wavelet packet transform. Energy entropy are obtained from decomposed coefficients feature matrix prepared. Then redundant features taken out forward selection method normalized. Test train data developed taking into consideration variables simulation situation like...

Abstract The increasing use of power electronics devices as well the integration renewable source-based microgrids (MG) has seriously affects quality (PQ) three-phase system. Therefore, for improvement PQ, it is required to reduce total harmonics distortion (THD) in utility network. In this work, PQ discussed a photovoltaic (PV) based MG integrated system using three-level H-bridge (3LHB) multilevel inverter (MI). MI used compensating source current and reducing THD by meeting IEEE standard...

<span lang="EN-US">Solar photovoltaic (PV) power, for its multiple benefits, has adhered to prominent consideration in the electrical energy generation region. The double-stage triple-phase grid-connected solar PV (SPV) system is utilized enhance power quality by employing a lymphoblastoid cell lines LCL filter. In this method, DC-DC converter and DC-AC make feasible juncture of systems interface. For converting boosted DC into AC, A 3-phase used, which supplied grid. voltage employed...

<span lang="EN-US">With the increase in demand for solar power, a power forecasting model is of maximum importance to allow higher level integration non-conventional energy into existing electricity grid. With advancement data availability, there’s good time use data-driven algorithms enhanced prediction generation. Gathering and analyzing can predict generation mitigate impact intermittency. During this research, we explore automatically creating models that are site-specific...

In the evolving landscape of subscription-based services, effective data deletion mechanisms are critical for safeguarding user privacy and ensuring regulatory compliance. This paper examines technical operational frameworks that underpin secure removal, addressing both immediate active profiles challenges associated with eradicating residual from backups distributed storage systems. By exploring encryption-based deletion, anonymization techniques, automated erasure protocols, study...

Artificial Intelligence (AI) is revolutionizing modern accounting by automating complex financial processes and enhancing accuracy in data management. This research explores the development of an AI integrated bank statement classifier paired with a ledger automation system to transform traditional practices. The proposed leverages advanced machine learning algorithms analyze categorize transactions from statements, enabling seamless reconciliation entries. A comprehensive preprocessing...

This research explores cost optimization and efficiency improvement in enterprise BI reporting through the implementation of strong audit governance strategies. Through formal auditing processes, organizations are able to detect redundancies, remove inefficiencies, optimize workflows. At same time, a clear-cut framework helps ensure data quality, enforces compliance with standards, aligns initiatives general business goals. Incorporating results into practices not only minimizes operations...

Electrical power load forecasting has at all times been an major issue in energy trade. Load is generally made through developing models on relative knowledge, reminiscent of local weather and previous demand knowledge. Such forecast almost always aimed towards brief-time period prediction like one-day forward prediction, the ground that longer interval (mid-term or long term) will not be reliant as a result error propagation. The accurateness predicting needs massive effect electricity...

The emission of greenhouse gasses from transportation vehicles is one the most alarming environmental threats and these gases mounting at a distressing pace. Limited fossil fuel resources are also threat to automobile industry. This work aims describe solar-powered electric vehicle (SPEV) as key solving downside pollution. A battery used in an (EV) which charged both external power supply photovoltaic (PV) panels absorb radiation sunlight generate electrical power. maximum point tracker...

Forecasting heart disease is an imperative endeavor in healthcare, and accurate models are essential for early detection intervention. In this proposed work, we have created a one-dimensional Convolutional artificial neural network model. with gridsearchCV hyperparameter tuning compared the accuracy Utilizing Support Vector Machine (SVM) Neural Network (1D CNN) Cleveland dataset. The SVM model widely used machine learning algorithm known its effectiveness classification tasks. We train on...

This paper is based on the improvement of power quality (PQ) using fuel cell and fuzzy controller. By proposed controller, in grid system especially micro connected with non- linear unbalanced load enhanced. The configuration combined hybrid arrangement photovoltaic ([PV) wind energy conversion (WECS), (FC) including compressed air storage (CAES) where management controlled by distributed sharing technique. In this distortions voltage at point common coupling (PCC) decreased FC which acts as...

This paper covers the comparison between four different DC-DC converters for solar power conversion. The are buck converter, buck-boost boost and noninverting converter. An MPPT algorithm is designed to calculate battery voltage, current of PV array, voltage output power. It observed that non-inverting converter finest final circuit design has results 12.2V 0.31A 34V 23mW panel, 21.8mW efficiency this system nearly 95%. All circuits simulated in MATLAB/Simulink R2020b.

This paper gives an analyzing study on fault detection and classification in a long transmission line which is series compensated using artificial neural network wavelet transform. The proposed scheme makes use of one cycle pre post samples the three phase current signals to find ground signal. Daubechies used as mother while discrete transform technique.The differential energy, based applied feed system, designed for all eleven types. Finally, optimal features are energies obtained from...

This paper presents an accurate hybrid fault location technique, combining s-transform and extreme learning machine for underground power cable in distribution system. In the proposed method, one cycle sending end post current voltage signal are taken determining cable. Using s-transform, useful features extracted, further applying feature selection redundant removed from total set. this paper, forward selection/particle swarm optimization-based method is used. Thereafter used to estimate...

This paper develops a maximum power point tracking (MPPT) approach for microgrid-linked solar photovoltaic (PV) system based on the concept of perturb and observe (P&O) approach. It is an iterative algorithm that requires starting to trace tracking. study proposes P&O MPPT 3-ɸ grid-connected PV system. In this work, modeled as DC system, applied model. An application used in proposal amplify effectiveness array face any unsteady climatic circumstances. Hence, highest energy...

One of the biggest challenges electric vehicle (EV) users has been predicting amount driving time their vehicles will have on one battery charge. Planning a trip and reducing range anxiety depends an accurate estimate. This study aims to anticipate EV using machine learning methods. In this research, several regression models for be developed compared. A real-world dataset comprising various factors affecting range, such as power, distance, energy consumption, style, environmental factors,...

A hybrid technique for fault distance estimation in a distribution line with wind farm is presented this paper. Here, one cycle of post current samples are taken location from the distributed generation end. The collected then decomposed by wavelet transform and thereafter six statistical features extracted reconstructed detail coefficients signal. Further best selected total feature set forward selection method. These fed as input to artificial neural network location. In proposed method,...