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Optimal detection and classification of grid connected system using MSVM-FSO technique

Environmental Science and Pollution Research 2024年第21期31卷 31064-31080页

作者： Stallon, Samuel Raj Daison Anand, Ramanpillai Kannan, Ramasamy Rajasekaran, Seenakesavan Department of Electrical and Electronics Engineering Nehru Institute of Engineering and Technology Tamil Nadu Coimbatore India Department of Electrical and Electronics Engineering KSR College of Engineering Tamil Nadu Thiruchengode India

This paper, a hybrid method, is proposed for protecting the hybrid photovoltaic (PV) and wind turbine (WT) system. The proposed protecting method is the hybrid wrapper of both the multiple support vector machine (MSVM) and firebug swarm optimization (FSO), commonly named as MSVM-FSO method. The proposed technique is diagnosing the appropriate fault occurring in the hybrid system. The main purpose of the proposed system is to assure the system with lower complexity for the fault diagnosis and detection (FDD) for improving the power quality (PQ) of hybrid method. Here, the MSVM approach is used to detect the fault conditions of grid-tied system. To evaluate the events of voltages, fault and the currents of hybrid systems are analyzed at the feeder of buses. The FSO categorizes the types of fault, which is occurred in grid-connected system. By then, the proposed method’s performance is done in the MATLAB software and it is contrasted with different existing methods. From this, the proposed method provides accuracy as 99.7% and efficiency as 98%, which is high compared to existing methods. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Support vector machines

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Innovative fuzzy logic type 3 controller for transient and maximum power point tracking in hydrogen fuel cells

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International Journal of Hydrogen Energy 2024年 143卷 833-845页

作者： Doğan, Serhat Haydaroğlu, Cem Gümüş, Bilal Mohammadzadeh, Ardashir Dicle University Faculty of Engineering Department of Electrical and Electronics Engineering Diyarbakır21280 Turkey Sakarya University Faculty of Engineering Department of Electrical and Electronics Engineering Sakarya54050 Turkey

This study introduces an advanced Fuzzy Logic Type 3 (FLT3) controller for Proton Exchange Membrane Fuel Cells (PEMFCs), aiming to optimize Maximum Power Point Tracking (MPPT) under dynamically varying temperature conditions. The FLT3 controller advances fuzzy logic control by incorporating an additional layer of uncertainty modelling, which enhances its ability to manage the inherent nonlinearities in PEMFC systems, such as temperature fluctuations and gas pressure variations. The controller is developed and validated through MATLAB/Simulink simulations, using a refined rule based on mechanism with finely tuned membership functions for precise adaptation to changing conditions. When compared to traditional Perturb and Observe (P&O) and Fuzzy Logic Type 2 (FLT2) controllers, the FLT3 controller demonstrates superior performance by achieving faster sitting times, minimizing power fluctuations, and maintaining operation closer to the nominal power point, particularly under transient conditions for hydrogen-based fuel cell. This innovative approach significantly improves the efficiency and stability of PEMFC systems, marking a substantial advancement in their operational management. © 2024 Hydrogen Energy Publications LLC

关键词： MATLAB

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Meta-heuristic-based power quality improvement in UPQC-based grid-connected hybrid renewable energy system

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Multimedia Tools and Applications 2025年第15期84卷 14553-14582页

作者： Ranjan, Ashish Choudhary, Jayanti Department of Electrical Engineering NIT Bihar Patna800005 India Department of Electrical & Electronics Engineering Nalanda College of Engineering Bihar Nalanda803108 India

The integration of renewable energy sources (RES) into the power grid has become an increasingly important aspect of modern power systems. However, the intermittent and variable nature of RES presents challenges for maintaining power quality (PQ) in the grid. One solution to address these challenges is the use of a Unified Power Quality Conditioner (UPQC) in a grid-connected hybrid renewable energy system (HY-RES). This paper proposes an approach to address power quality (PQ) issues in a hybrid renewable energy system (HY-RES) that incorporates a grid-connected load. The proposed approach utilizes a Unified Power Quality Conditioner (UPQC) device to minimize PQ disturbances and meet load demand in the system. To improve the performance of the UPQC, an optimized PI controller is introduced. To enhance the performance of the PI Controller, the gain parameters (Proportional gain kp and integral gain ki) are fine-tuned using the new hybrid optimization algorithm called Particle Updated Greywolf Optimizer (PUGO). The proposed Particle Updated Greywolf Optimizer (PUGO) model is the combination of the standard Particle Swarm optimization (PSO) and Grey wolf optimization (GWO), respectively. The proposed method is evaluated using MATLAB/Simulink, and its performance is compared to existing techniques such as GWO and PSO algorithms. The results show that the proposed approach outperforms existing techniques in mitigating PQ issues such as sag, swell, fluctuation, and Total Harmonic Distortion (THD). Overall, the proposed UPQC-based PC-GWO approach offers an effective solution for improving PQ in HY-RES systems with grid-connected loads. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Power quality

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Detailed Electromagnetic Analysis of Variable Flux Reluctance Machines: Unveiling Torque Production Harmonics Through Winding and Permeance Functions

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IEEE Transactions on Energy Conversion 2025年第2期40卷 959-969页

作者： Ayhan, Ufuk Gurleyen, Hilmi Meşe, Erkan Ege University Department of Electrical and Electronics Engineering Izmir35040 Turkey Uşak University Department of Electrical and Electronics Engineering Uşak64200 Turkey

This paper investigates the analytical modeling of variable flux reluctance machine (VFRM) using the harmonic spectrum of winding and magnetic permeance functions. Mutual inductance and back-electromotive force of 6/4 and 12/10 VFRM topologies are obtained using harmonic series expansion of the winding and permeance functions. The harmonic components of synchronous torque are derived by performing a comprehensive analysis of the sinusoidal series attributed to the winding and permeance functions. An investigation is conducted concerning the impact of rotor skewing on the back-EMF and synchronous electromagnetic torque output of a 12/10 VFRM. The validity of the proposed model is confirmed through results obtained from finite element analysis (FEA) and experimental measurements of back-electromotive force (back-EMF) and torque. © 1986-2012 IEEE.

关键词： Rotors (windings)

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Analysis of Solar Photovoltaic Integration and Plug-in Electric Vehicle Charging Systems with a Bidirectional Buck-Boost DC to DC Converter

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Journal of The Institution of Engineers (India): Series B 2024年 1-15页

作者： Rajalakshmi, J. Jeyanthi, S. Bhuvanesh, A. Arun Kumar, A. Department of Electrical and Electronics Engineering SRM Madurai College for Engineering and Technology Tamil Nadu Madurai India Department of Electrical and Electronics Engineering Ramco Institute of Technology Tamil Nadu Rajapalayam India Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli India

Renewable energy-powered plug-in electric vehicle (PEV) charging stations have gained popularity in recent years, especially in commercial and business-oriented environments. Several studies have investigated the use of solar photovoltaic (SPV) technology in a wide-spectrum bidirectional buck-boost DC-to-DC converter. Used in the grid-to-vehicle power export (VPE) and -ingestion (VPI) modes of operation, this combination system is designed for electric-powered vehicle packages like PEVs. In all operating modes, the converter achieves a satisfactory voltage switch ratio (VSR) with the suggested system setup, and there are no theoretical output voltage hurdles. In terms of flexibility, redundancy, and usability, it provides proof that it is suitable for PEV uses. In order to verify the theoretical assessment, an experimental model with 400 W was built and tested. The data shows that this improved method is successful and useful, with a peak efficiency of 97.4 percent when operating in VPE mode and 97.1 percent while operating in VPI mode. The results demonstrate the viability and practicality of the bidirectional buck-boost DC to DC converter, which enhances VPE-VPI operations in PEV charging structures and works well with the recommended combination of SPV and PEV charging systems. © The Institution of Engineers (India) 2024.

关键词： Charging stations

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From light sensing to adaptive learning:hafnium diselenide reconfigurable memcapacitive devices in neuromorphic computing

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Light(Science & Applications) 2025年第1期14卷 215-226页

作者： Bashayr Alqahtani Hanrui Li Abdul Momin Syed Nazek El-Atab Electrical and Computer Engineering Program Computer Electrical Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)ThuwalSaudi Arabia Electrical Engineering Department College of EngineeringPrincess Nourah Bint Abdulrahman University(PNU)RiyadhSaudi Arabia

Advancements in neuromorphic computing have given an impetus to the development of systems with adaptive behavior,dynamic responses,and energy efficiency *** charge-based or emerging memory technologies such as memristors have been developed to emulate synaptic plasticity,replicating the key functionality of neurons—integrating diverse presynaptic inputs to fire electrical impulses—has remained *** this study,we developed reconfigurable metal-oxide-semiconductor capacitors(MOSCaps)based on hafnium diselenide(HfSe2).The proposed devices exhibit(1)optoelectronic synaptic features and perform separate stimulus-associated learning,indicating considerable adaptive neuron emulation,(2)dual light-enabled charge-trapping and memcapacitive behavior within the same MOSCap device,whose threshold voltage and capacitance vary based on the light intensity across the visible spectrum,(3)memcapacitor volatility tuning based on the biasing conditions,enabling the transition from volatile light sensing to non-volatile optical data *** reconfigurability and multifunctionality of MOSCap were used to integrate the device into a leaky integrate-and-fire neuron model within a spiking neural network to dynamically adjust firing patterns based on light stimuli and detect exoplanets through variations in light intensity.

关键词： integrate volatile integrating

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An improved transfer learning model for detection of insulator defects in power transmission lines

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Neural Computing and Applications 2025年第9期37卷 6951-6976页

作者： Pradeep, V. Baskaran, K. Evangeline, S. Ida Department of Electrical and Electronics Engineering Alagappa Chettiar Government College of Engineering and Technology Tamilnadu Sivagangai District Karaikudi630003 India Department of Electrical and Electronics Engineering Government College of Engineering Tamilnadu Tirunelveli627808 India

Insulators are critical components of transmission lines but are prone to failures that can jeopardize the safe operation of electrical power systems. Accurate detection of insulator defects is essential for timely maintenance. With advancements in object detection algorithm and artificial intelligence, insulator defect detection has garnered significant attention. However, detection accuracy remains an issue. To address this, we propose an improved transfer learning model. Our approach incorporates the Mish activation function and a global context network module to enhance the model's performance. The improved YOLOv9 model is trained and tested using two public datasets: the insulator defect image dataset and the China power line insulator dataset. Experimental results demonstrate that our model achieves optimal detection precision and recall rates of 99.84 and 99.92%, respectively—improvements of 1.06 and 1.09% over the actual YOLOv9. Additionally, our model outperforms other algorithms, such as RTDETR and SSD, particularly in adapting to complex backgrounds and detecting small targets. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Power transmission lines

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An approach for commutation current ripple alleviation in BLDCM drive using novel DC-DC converter

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International Journal of Power electronics 2024年第1期19卷 24-52页

作者： Kumar, Dileep Choudhary, Surya Deo Tabrez, Md Department of Electrical and Electronics Engineering Motihari College of Engineering Motihari845401 India

Brushless direct current motors (BLDCMs) have gained widespread favour in several applications, including residential, business, and industrial settings. In comparison to other drives, such as induction motor, DC, and synchronous motor drives, the BLDCM drives offer better performance. However, the BLDCM drive's use is constrained by the significant problem of commutation current ripples (CCRs). These ripples are mostly caused by phase winding inductance. Unnecessary speed variations, oscillation, noise, and vibration are introduced by the CCR. To alleviate the CCR, a novel BLDCM drive based on DC-DC converters has been designed in this paper. Wide voltage gain is offered by the suggested DC-DC converter, along with minimal conduction losses. The regulated DC-bus voltage is drawn in the suggested topology configuration using a DC-DC converter, which creates an equal slope (slew rate) of the incoming and departing phase currents. Within the MATLAB/Simulink software environment, the suggested model is tested. Additionally, an experimental prototype has developed to confirm the viability of the suggested technique. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： DC-DC converters

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When to Reach for the Skies? A DRL-Based Routing Framework for Non-Terrestrial Networks

IEEE Networking Letters

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IEEE Networking Letters 2025年第1期7卷 16-20页

作者： Sharma, Akanksha Tripathi, Sharda Joshi, Sandeep Department of Electrical and Electronics Engineering Pilani333031 India

Non-terrestrial networks are envisioned to be an integral component of the beyond-fifth-generation wireless communication networks, catering to both conventional and emerging communication applications. In particular, a plethora of use cases are emerging for ultra-reliable low-latency communication, which require dynamic and quality of service compliant frameworks. In this letter, we formulate a binary integer non-linear programming problem to route time-critical traffic through non-terrestrial nodes. As the problem is NP-hard, we propose the solution using a deep reinforcement learning framework, taking into account the interactions between the terrestrial and various non-terrestrial nodes with an end-to-end latency target while maximizing the coverage probability. We perform simulations for multiple latency deadlines and outage thresholds and the results corroborate the efficiency of the proposed framework. Furthermore, we benchmark the proposed framework and show an improvement of 96.31% in coverage while incurring only 3.2% latency violations compared to the state-of-the-art. © 2019 IEEE.

关键词： Deep reinforcement learning

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An Adaptive Secondary Control Based on Recursive Neural Networks for Isolated Microgrids

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2024年第4期22卷 137-142页

作者： Rodríguez, L. Pantoja, A. Revelo, J. Barco-Jiménez, J. Department of Electronics University of Nariño Colombia Program of Electronic Engineering University CESMAG Colombia Postgraduate Programs in Electrical and Electronic Engineering-PPIEE University of Valle Colombia Electrical Engineering Department University of Malaga Spain

This work proposes a model reference adaptive control based on recursive neural networks. This secondary-level controller corrects the deviations on the voltage and frequency setpoints of a simple primary control in an isolated microgrid (MG) with multiple distributed generators (DGs). The controller has two nonlinear autoregressive with external input neural networks to emulate the microgrid and guide the whole system according to an appropriate reference model. The networks are trained with synthetic data from a simulation MG and the order of the networks are obtained with a deterministic method. The method is tested with a three-units MG in a Matlab simulation under different working conditions. Results show the proper performance of the proposed controllers in comparison to a PI strategy. © 2024, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Microgrids

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