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Enhancing Grid-Connected Hybrid Renewable Energy System with Super Lift Luo Converter for Improved Power Management and Reduced THD

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Journal of The Institution of Engineers (India): Series B 2025年第1期106卷 129-143页

作者： Ganga Bhavani, Chaladi S. Bhanu Prasad, N. Ravi Kishore, D. Department of Electrical and Electronics Engineering GIET University Odisha Gunupur India Department of Electrical and Electronics Engineering Godavari Institute of Engineering and Technology Rajahmundry India

In recent decades, use of renewable energy sources (RES) has become increasingly popular due to its reliable and clean source of electricity. Utilizing RES like solar and wind helps in ensuring energy sustainably. Furthermore, it is admirable to employ renewable resources popularly in order to generate energy that is both affordable and dependable. Solar and wind energy sources are intermittent, and their energy output can vary due to weather conditions. Combining them helps to mitigate the variability in power generation. In the proposed work in combination of solar and wind turbine source is implemented for increased system reliability with minimized cost. The proposed approach uses Super Lift Luo Converter to boost up the voltage generated from PV system. The employed Proportional Integral (PI) controller regulates the converter operation and aids in the generation of a stable voltage at the DC link. A similar process ensues in the Doubly Fed Induction Generator based Wind Energy Conversion System, which produces AC voltage that is converted into DC by a PWM rectifier to supply the DC Link with input power. In case of excess generation of energy from the hybrid systems, a battery is utilized for storing energy. For the conversion of DC electricity to AC, a three-phase voltage source inverter is supplied the DC link voltage. Grid synchronization is accomplished utilizing a PI controller, while the LC filter decreases harmonics. Grid synchronization is accomplished with help of a PI controller, and harmonics are reduced by an LC filter. The performance of suggested concept is appraised using the experimental setup and the corresponding results are verified utilizing MATLAB simulation. The proposed system operates at the efficiency of 96%, with reduced Total Harmonic Distortion (THD) of 0.93%. © The Institution of Engineers (India) 2024.

关键词： Pulse width modulation

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Comparative analysis and statistical performance evaluation of fractional PID controllers in fuel cell choppers optimized with metaheuristic algorithms

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Neural Computing and Applications 2025年第6期37卷 4585-4615页

作者： Güven, Aykut Fatih Mengi, Onur Özdal Department of Electrical and Electronics Engineering Yalova University Yalova Turkey Department of Electrical and Electronics Engineering Giresun University Giresun Turkey

Fuel cells (FCs) are significant renewable energy sources that produce electrical energy, similar to photovoltaic solar panels and wind turbines. These cells use hydrogen as a fuel and produce pure water as waste, making them potential alternatives to batteries. This paper compares the parameters of a buck-type converter designed for use in fuel cell (FC) energy production systems. These parameters were optimized using five optimization algorithms. To ensure high quality, the converters that adjust the desired current and voltage values on the load must be controlled optimally. In this context, fractional-order PID (FOPID) controllers, which are advanced versions of standard PID controllers, were used to adjust the voltage of a load to its desired reference value. Five parameters (KP, KI, KD, μ, and λ) of this controller were adjusted using various algorithms: artificial bee colony (ABC) optimization, atom search optimization (ASO), Henry gas solubility optimization (HGSO), the JAYA algorithm, and the sine cosine algorithm (SCA) optimization. Among these algorithms, the HGSO algorithm demonstrated the best results. However, after a comprehensive statistical analysis, different insights emerged. The findings are then presented in a comparative analysis. Simulation studies were performed in the MATLAB/Simulink environment and the coding sections of MATLAB. The system under study comprises an FC, a converter, and loads. The responsiveness of the controller to variables and disturbances was examined by continuously adjusting both the reference value and load. The results derived from these calculations provide a detailed analysis of the controller’s ability to ensure that the voltage on the load aligns with the reference values. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Three term control systems

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Efficient Fault Classification in Distributed Generation Systems using M-KNN and Grid Search Techniques

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International Energy Journal 2025年 25卷 195-202页

作者： Bisht, Kamlesh S. Ahamad, Nafees Awasthi, Saurabh Department of Electrical and Electronics and Communication Engineering India

To meet the growing demand for electricity and ensure a sustainable future, there is a significant shift towards distributed generation (DG), including non-renewable energy sources. The stability and reliable operation of DGs, which involve non-uniform power generation, present challenging problems. Proper fault diagnosis and mitigation are crucial in these systems. Consequently, reliable fault identification and mitigation are essential to ensure the trustworthiness and functionality of DGs. Established mathematical models for fault identification, location, and system isolation can be time-consuming and inaccurate. With advancements in machine learning (ML) and artificial intelligence (AI), these technologies have found applications in distributed generation systems (DGS). Therefore, this article investigates the use of Mutual K-Nearest Neighbors (M-KNN) for fault identification. This study considers a 100 km grid-connected distributed generation system comprising two distributed generators (DGs), simulated using MATLAB® to obtain data for ten different faults at various locations spaced at 2 km intervals. Subsequently, M-KNN in Python is employed for fault classification to accurately determine the nature of faults. To enhance the robustness of the model, a grid search approach with and without cross-validation (CV) is utilized. The achieved training and testing accuracies approach 99%, surpassing the performance of Basic KNN (B-KNN) models. © 2025 Regional Energy Resources Information Center (RERIC), Asian Institute of Technology. All rights reserved.

关键词： k-nearest neighbors

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Invariant Feature Extraction Functions for UME-Based Point Cloud Detection and Registration

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IEEE Transactions on Image Processing 2025年 34卷 3209-3224页

作者： Efraim, Amit Haitman, Yuval Francos, Joseph M. Shamoon College of Engineering Department of Electronics and Electrical Engineering Israel Ben Gurion University Department of Electrical and Computer Engineering Israel

Point clouds are unordered sets of coordinates in 3-D with no functional relation imposed on them. The Rigid Transformation Universal Manifold Embedding (RTUME) [1] is a mapping of volumetric or surface measurements on a 3-D object to matrices, such that when two observations on the same object are related by a rigid transformation, this relation is preserved between their corresponding RTUME matrices, thus providing linear and robust solution to the registration and detection problems. To make the RTUME framework of 3D object detection and registration applicable for processing point cloud observations, there is a need to define a function that assigns each point in the cloud with a value (feature vector), invariant to the action of the transformation group. Since existing feature extraction functions do not achieve the desired level of invariance to rigid transformations, to the variability of sampling patterns, and to model mismatches, we present a novel approach for designing dense feature extraction functions, compatible with the requirements of the RTUME framework. One possible implementation of the approach is to adapt existing feature extracting functions, whether learned or analytic, designed for the estimation of point correspondences, to the RTUME framework. The novel feature-extracting function design employs integration over SO(3) to marginalize the pose dependency of extracted features, followed by projecting features between point clouds using nearest neighbor projection to overcome other sources of model mismatch. In addition, the non-linear functions that define the RTUME mapping are optimized using an MLP model, trained to minimize the RTUME registration errors. The overall RTUME registration performance is evaluated using standard registration benchmarks, and is shown to outperform existing SOTA methods. © 1992-2012 IEEE.

关键词： Linear transformations

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Dual-stage Model Predictive Control Based Reduced Model Framework for Voltage Control in Active Distribution Networks

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Journal of Modern Power Systems and Clean Energy 2024年第6期12卷 1880-1892页

作者： Mudaser Rahman Dar Sanjib Ganguly Department of Electronics and Electrical Engineering Indian Institute of TechnologyGuwahatiIndia

The large-scale penetration of photovoltaic(PV)units and controllable loads such as electric vehicles(EVs)ren-der the distribution networks prone to frequent,uncertain,and simultaneous over/under *** coordinated control of devices such as on-load tap changer(OLTC),PV inverters,and EV chargers seem efficient in regulating the distribution net-work voltage within normal operation ***,the need for measuring infrastructure throughout the distribution net-work and communication setup to all control devices makes it practically and economically ***,for large-scale networks,the large measurement dataset of the network and distributed control resources increase the computational complexity and the response *** paper proposes a volt-age control strategy based on dual-stage model predictive con-trol by coordinating devices such as OLTC and controllable PVs and EV charging stations.A minimum set of available con-trol resources is identified to establish the voltage control in the network with reduced communication and minimum measuring infrastructure,using a reduced model *** are performed on 33-bus distribution network and the modified IEEE 123-bus distribution network to validate the efficacy of the proposed control strategy.

关键词： Active distribution network voltage control distributed generation photovoltaic(PV) model predictive con-trol(MPC)

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Extension of Distribution Transformer Life in the Presence of Smart Inverter-based Distributed Solar Photovoltaic Systems

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 88-95页

作者： Kanhaiya Kumar Saran Satsangi Ganesh Balu Kumbhar Department of Electrical and Electronics Engineering Motihari College of EngineeringMotihariBiharIndia Department of Electrical Engineering National Institute of Technology(NIT)PatnaPatnaBiharIndia Department of Electrical Engineering Indian Institute of Technology(IIT)RoorkeeRoorkeeUttarakhandIndia

A transformer is an essential but expensive power delivery equipment for a distribution *** many distribution utilities worldwide,a sizable percentage of transformers are near the end of their designed *** the same time,distribution utilities are adopting smart inverter-based distributed solar photovoltaic(SPV)systems to maximize renewable *** central objective of this paper is to propose a methodology to quantify the effect of smart inverter-based distributed SPV systems on the aging of distribution *** proposed method is first tested on a modified IEEE-123 node distribution *** that,the procedure is applied to a practical distribution system,i.e.,the Indian Institute of Technology(IIT)Roorkee campus,*** transformer aging models,alongside advanced control functionalities of grid-tied smart inverter-based SPV systems,are implemented in *** open-source simulation tool(OpenDSS)is used to model distribution *** analyze effectiveness of various inverter functionalities,time-series simulations are performed using exponential load models,considering daily load curves from multiple seasons,load types,current harmonics,*** show replacing a traditional inverter with a smart inverter-based SPV system can enable local reactive power generation and may extend the life of a distribution *** results demonstrate,simply by incorporating smart inverter-based SPV systems,transformer aging is reduced by 15%to 22%in comparison to SPV systems operating with traditional inverters.

关键词： Distribution transformer loss of life smart inverter functions solar photovoltaic systems thermal models Volt-VAr control

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Analysis of the Performances of Dissimilar PV array Topologies Under Realistic Partial Shading Condition

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Journal of The Institution of Engineers (India): Series B 2024年第5期105卷 1169-1181页

作者： Jha, Vandana Department of Electrical and Electronics Engineering RV College of Engineering Bangalore India

This paper analyses the performances of dissimilar PV array topologies—(i) classical topologies: Series, Parallel, Series–Parallel, Total-Cross-Tied, Bridge-Linked, andHoney-Comb and (ii) modern topologies: SeriesParallel-TotalCrossTied, BridgeLinked-TotalCrossTied, HoneyComb-TotalCrossTied, and BridgeLinked-HoneyComb under realistic partialshadingcondition. In this work, MATLAB tool has been used for the simulation of the models of dissimilar PV array topologies. The performances of dissimilar PV array topologies have been weighed against each other on the basis of their maximumpower, fill-factor, thermalvoltage, and relativepowerloss under realistic partialshadingcondition analogous to two shading patterns at various instants for respectively 2 complete days 6 months apart. The MATLAB simulated outcomes of dissimilar PV array topologies for all the examined shading patterns have been processed employing probabilitydensityfunction which validates the superiority of the modern topologies over their respective classical topologies. © The Institution of Engineers (India) 2024.

关键词： Topology

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An intelligent control approach for resonance damping in a grid-connected inverter system

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International Journal of electrical engineering and Education 2024年第2期61卷 161-179页

作者： Hemakesavulu, O. Dash, Subhransu S Chellammal, Nallaperumal Department of Electrical and Electronics Engineering SRM Institute of Science and Technology India Department of Electrical and Electronics Engineering GCE Odisha keonjhar India

Photovoltaic power generation has transformed into the most reassuring strategy for power generation among the renewable sources in view of its intrinsic favorable circumstances. The significant snag that photovoltaic system poses like other inexhaustible sources is the power intermittency in regard to atmospheric conditions like irradiation and temperature. These photovoltaic systems are interfaced to the grid through filters via inverters to prevent harmonics getting in to the grid. Generally, inductor–capacitor–inductor filters are employed in grid-connected system, as they provide better harmonic attenuation than inductor and inductor-capacitor filters. However, they bring resonance as well as oscillations into the grid-connected system. So, in order to suppress the resonance that brings instability problems in the system, active damping control strategies are adopted. But these conventional active damping methods increase the complexity of the system as they need extra sensors. This article proposes a fuzzy logic control-based active damping method to ease the control activity. The proposed controller is contrasted with the injected grid current feedback controller to investigate the resonance damping and the stability of grid interfaced multilevel inverter with inductor–capacitor–inductor filter. When compared with the injected grid current feedback controller, the fuzzy logic control approach promises satisfactory performance based on harmonic content, resonance peak, and stability analysis. The compliance according to the industrial standard in terms of harmonics is met in this article and is duly documented within the manuscript. Simulation results verify the design strategies and the effectiveness of the proposed fuzzy logic control strategy. © The Author(s) 2019.

关键词： Resonance

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Fault classification and identification through machine learning approaches for a solar PV – battery based water pumping system

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Multimedia Tools and Applications 2025年第14期84卷 13843-13864页

作者： Sowmmiya, U. Abinaya, K. Jhunjhunwala, Rishik Satpathy, Prateek Arul, R. Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Kattankulathur India Department of Electrical and Electronics Engineering Vellore Institute of Technology Chennai India

The world progresses towards enabling renewable sources into the mainstream supply of energy and it is imperative to develop systems that can handle new challenges and disturbances. This paper aims at machine learning model-based fault identification and classification of an islanded Solar PV – battery integrated system feeding a water pumping system. The system is powered through solar PV and battery (discharge mode) which are controlled through Semi Pilot Cell based Fractional Open Circuit Voltage (SFOCV) method and conventional voltage control method respectively. The water pumping system is simulated using MATLAB which is interfaced with RT-LAB software for extracting the real-time data from the OPAL – RT Controller (OP4510) through Software-in-Loop (SiL) approach. All possible faults associated with a stand-alone solar PV-battery system are aggregated to execute the machine learning model. This data is pre-processed and the distribution plots are observed to describe the statistical nature of the data. The processed data is then used to train a Logistic Regression (LR) Model and Artificial Neural Network (ANN) Model to identify whether there is a fault or non-fault condition (Binary Classification) and then classify which fault case has occurred (Multi-class Classification). The models are trained and validated in the controller. The resulting comparative parameters such as accuracy and kappa values indicate that ANN model proves to be a better solution for fault identification and classification. Also, the cost functions (error) seem to be less in ANN model and the comparative results are discussed in this work. The proposed intelligent, fault identification and classification model being implemented with real-time data ensures reliability and immediate indication to the stakeholders on the status of the fault in the system. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： MATLAB

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PV-Based Grid Integrated EV with GWO Optimized PI Controller for Boost Integrated Luo Converter

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Journal of The Institution of Engineers (India): Series B 2024年第2期105卷 309-321页

作者： Kancherla, Ananda Babu Prasad, N. Bhanu Kishore, D. Ravi Department of Electrical and Electronics Engineering Gandhi Institute of Engineering and Technology Odisha Gunpur India Department of Electrical and Electronics Engineering Godavari Institute of Engineering and Technology A.P. Rajahmundry India

The superfluous carbon emissions from automobiles and fossil-fuelled power plants are major contributors of global warming and air pollution. It is high time that both these sectors are steadily decarbonized in order to prevent the earth from becoming completely uninhabitable for human life. Thereby, in this work, focus is towards combining photovoltaic (PV) system and grid with an electric vehicle (EV) such as electric train, which successfully satisfies the requirement of both decarbonized energy generation and transportation. For enhancing the voltage level of the PV, a Boost integrated Luo converter is introduced, since it offers wide conversion range along with reduced voltage stress. Moreover, a constant output without fluctuations is obtained from the converter with the employment of Grey Wolf Optimized proportional–integral controller. On the EV side, its speed is controlled by the implementation of PI controller. The PV power is sufficient to run the BLDC motor of EV during daylight hours owing to the presence of sunlight;however, in night time, the BLDC motor is powered by the energy from the single-phase grid. The proposed grid integrated PV-based EV charging system is tested for its effective working in a MATLAB platform. © The Institution of Engineers (India) 2023.

关键词： Global warming

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