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measurement and Analysis of Voltage sag and swell in Large Penetrated Grid-Connected Wind Farm

Journal of The Institution of Engineers (India): series B 2024年第3期105卷 713-732页

作者： Bhadane, Kishor V. Thakre, mohan Devikar, Rohit Electrical Engineering Amrutvahini College of Engineering M.S. Sangamner Dist Ahmednagar India Electrical Engineering Shri Vithal Education and Research Institute College of Engineering M.S. Pandharpur India Information Technology Amrutvahini College of Engineering M.S. Sangamner Dist Ahmednagar India

Due to the increase in the grid-connected WE penetration and its huge integration to grid system, technical challenges are faced in the form of power quality (PQ). The injection of huge wind power in to weak grid system causes power quality issues such as voltage sag and voltage swell as per technical standard of IEC 614000-4-30 and IEEE 1668. The main objective of this review paper is to provide the causes, effect of voltage sag, swell in grid-connected wind energy system and its proper detection, protections to the unexpected voltage variations-based power quality issues such as voltage sag and swell condition during grid-connected mode of wind energy system by using custom power devices (CPD). Due to inadequate drawing of reactive power from grid system during voltage variation condition such as sag, swell condition, the voltage profile and voltage stability as PQ issues are affected the wind power operation. Hence, CPD is interfaced in to wind energy system to supplied necessary required reactive power so that to control the voltage fluctuations to within the constraint limit. During sag condition of WT, the active power of wind turbine without CPD is 29 mW and with CPD is 36.9., i.e., additional 8% active power is injected by WT in to the grid, and the reactive power is controlled up to 2.2% by CPD. During swell condition of WT, the active power of wind turbine without CPD is 38mW and with CPD is 39mW, i.e., additional 1% active power is injected by WT in to the grid, and the reactive power is controlled up to 1% by CPD. © The Institution of Engineers (India) 2024.

关键词： Power quality

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Enhancing EV Performance: Critical Review of ITC and DTC for Torque Ripple mitigation in sRms 1

Enhancing EV Performance: Critical Review of ITC and DTC for...

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1st International Conference on AImL-Applications for engineering and Technology, ICAET 2025

作者： sawant, Jitendra shahakar, Deepak Pandit, Pankaj Darda Institute of Engineering and Technology Dept. of Electrical Engineering Jawaharlal M.S. Yavatmal India College of Engineering and management Dept. of Electrical Engineering P.R.Pote M.S. Amravati India Jawaharlal Darda Institute of Engineering and Technology Dept. of Electronics & Telecommunication Engineering M.S. Yavatmal India

ISBN: (纸本)9798350355611

switched Reluctance motors are viable substitutes for electric vehicle propulsion due to their features which include affordable cost, robust construction and ease of use. However, excessive torque ripple is a significant challenge in sRm applications as it can cause greater acoustic noise and mechanical vibrations there by lowering EV performance and comfort. This critical evaluation focuses on two popular torque control strategies- ITC and DTC that aim to reduce torque ripple in sRms. Indirect Torque Control uses an intermediary control variable such as current or flux linkage to govern torque indirectly. This technique improves torque production by optimizing current profiles are reducing torque ripples. ITC approaches frequently use advanced control technique and exact current profiling to produce the necessary torque characteristics. Direct Torque Control directly alters motor torque by adjusting the power converter's switching states in real-time in response to torque and flux inputs. DTC is noted for its rapid dynamic response and ease of application, as it eliminates the need for sophisticated modulation procedures. However, the of problem precisely measuring torque and flux, which is crucial for avoiding torque ripple is a challenging issue in sRm drive. This paper critically review and examines the control approaches torque ripple analysis, benefits and drawbacks of both ITC and DTC strategies for torque ripple minimization in sRms for specially EV application EV applications. Here comparative study is carried out to illustrate the efficiency of each strategy in several operational scenarios. In addition, recent breakthroughs and hybrid approaches that integrate components of both ITC and DTC are investigated to provide insights into future trends and prospective opportunities for improvements in torque control strategies for sRms. This study is definitely expected to the researchers in making prudent choice for selection of an acceptable and effective con

关键词： Reluctance motors

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Development of an Autonomous Electric Vehicle with solar Tracker 1

Development of an Autonomous Electric Vehicle with Solar Tra...

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1st IEEE International Conference on smart Power Control and Renewable Energy, ICsPCRE 2024

作者： Punith Raj, J.s. Varanasi, Praveen Kumar Gowda, Nesar G Ravichandran, shama Dhanraj, m. M.S. Ramaiah University of Applied Sciences Dept of Electrical Engineering Bengaluru India

ISBN: (纸本)9798350377002

This paper presents a solar powered autonomous electric vehicle with a solar tracker to maximize the solar power harvested. The solar tracker tracks the sun's rays and modifies the panel's reflecting surface according to the intensity. Real-time image processing technique is used for road sign recognition, obstacle recognition and avoidance. Experimental results show that the autonomous electric vehicle can navigate to various destinations without human intervention and can detect objects up to a given threshold cm accurately. Traffic signal detection test results shows that the vehicle stops exactly at the pre-defined position. In obstacle recognition and avoidance test obstacles like potholes, pedestrians and vehicles were detected and avoided successfully. The proposed method of harvesting solar energy using a solar tracker for an autonomous electric vehicle leads to notable gains in energy efficiency, increasing the vehicle's range and decreasing its dependency on outside power sources. This strategy contributes to a cleaner and greener transportation ecosystem by increasing solar power capture and lowering the vehicle's carbon footprint. © 2024 IEEE.

关键词： Traffic signals

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KNN for Exploratory Drug Risk Analysis and Patient Well-Being: Enhanced Healthcare 5th

KNN for Exploratory Drug Risk Analysis and Patient Well-Bein...

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5th Doctoral symposium on Computational Intelligence, DosCI 2024

作者： Raj, V. Aditya Raman, V. R. monish shidaganti, Ganeshayya Department of Computer Science and Engineering M.S. Ramaiah Institute of Technology Karnataka Bangalore India

ISBN: (纸本)9789819771776

The importance of drug risk analysis is very evident in the ever-evolving landscape of pharmaceuticals and healthcare due to the introduction of innovative technologies. With the development of novel therapies and pharmaceutical innovations at an unprecedented rate, the challenges associated with ensuring the drug’s efficacy and safety have also increased. Prom.s.ng advancement in drug risk analysis has been achieved with the integration of advanced technologies including machine learning and sophisticated data analytics. making accurate predictions on the safety concerns of newly developed drugs by scrutinizing vast datasets has been made easy due to these advancements. Our research paper provides a versatile solution to analyse the risks of a particular drug that may have negative effects on individuals based on their individual medical histories and conditions. Using a handcrafted dataset containing health records of each patient’s medical history, we have trained a K-Nearest Neighbours (KNN) model using clustering methods that identify which patients may safely use this medication and who cannot with an accuracy of 84%. This sophisticated solution can help doctors determine the safety of a particular drug without causing any health complications with the existing medical conditions of the patient. © The Author(s), under exclusive license to springer Nature singapore Pte Ltd. 2025.

关键词： Electronic health record

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Quantum illumination with high-dimensional Bell states

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Physical Review A 2024年第5期110卷 L050603-L050603页

作者： Armanpreet Pannu Amr s. Helmy Hesham El Gamal The Edward S. Rogers Department of Electrical and Computer Engineering University of Toronto Toronto Canada M5S 3G4 School of Electrical and Information Engineering Faculty of Engineering The University of Sydney Sydney 2008 Australia

We propose a protocol in quantum illumination (QI) leveraging entanglement in discrete-variable states. Our investigation shows that, as m→∞, the m-mode Bell state matches the 6 dB advantage of the two-mode squeezed vacuum in high noise. It also excels in low- and mid-noise conditions, demonstrating that QI's benefits are not restricted to high background noise. moreover, the protocol benefits from a sequential decision rule, increasing the advantage beyond 6 dB. These findings present an intriguing alternative to continuous-variable states and open different applications for QI using discrete-variable states.

关键词： Quantum.s.nsing

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Building a hybridised meta-heuristic optim.s.tion algorithm for efficient cluster analysis

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International Journal of Business Intelligence and Data mining 2022年第1-2期22卷 170-222页

作者： Kumar, D. Pradeep sowmya, B.J. Kanavalli, Anita Cornelio, Varun Dsouza, Jaison Pravith memon, Wasim Prashanth, P. Department of Computer Science and Engineering M.S. Ramaiah Institute of Technology Bangalore India

Nature-inspired algorithms are a relatively recent field of meta-heuristics introduced to optim.s. the process of clustering unlabelled data. In recent years, hybridisation of these algorithms has been pursued to combine the best of multiple algorithms for more efficient clustering and overcoming their drawbacks. In this paper, we discuss a novel hybridisation concept where we combine the exploration and exploitation processes of the vanilla bat and vanilla whale algorithm to develop a hybrid meta-heuristic algorithm. We test this algorithm against the existing vanilla meta-heuristic algorithms, including the vanilla bat and whale algorithm. These tests are performed on several single objective CEC functions to compare convergence speed to the minima coordinates. Additional tests are performed on several real-life and artificial clustering datasets to compare convergence speeds and clustering quality. Finally, we test the hybrid on real-world cases with unlabelled clustering data, namely a credit card fraud detection dataset, and a COVID-19 diagnosis dataset, and end with a discussion on the significance of the work, its limitations and future scope. © 2023 Inderscience Enterprises Ltd.

关键词： Cluster analysis

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Exploratory Data Analytics of COVID-19 Vaccination Drive in India: Insights and Lessons Learnt

Exploratory Data Analytics of COVID-19 Vaccination Drive in ...

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2024 IEEE International Conference on Innovation and Novelty in engineering and Technology, INNOVA 2024

作者： Joshi, Akhilesh Doddmani, seeba Akkasaligar, Prema T. Pattar, santosh Department of Computer Science and Engineering KLE Technological University’s Dr. M.S. Sheshgiri College of Engineering and Technology Belagavi India

ISBN: (纸本)9798331505134

This study examines COVID-19 vaccination drive in India, highlighting disparities by age, gender, and region. Challenges include addressing gaps in second-dose uptake and regional inequities. Our analysis of vaccination data ties into sustainable Development Goal 3 (sDG 3), revealed that older age groups were prioritized, Covishield was the m.s. prevalent vaccine, and significant gaps existed in second-dose administration.A survey on how vaccination affects population immunity is also conducted, revealing similar patterns of disparity. Regional disparities were also observed, with uneven vaccine distribution across states. The findings suggest that improvements are necessary to enhance second-dose coverage and ensure equitable vaccine access across all the regions. © 2024 IEEE.

关键词： COVID-19

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Intelligent Control of Double Boost Converter Interfaced with multilevel Inverter for electrical Vehicle Applications

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Journal of The Institution of Engineers (India): series B 2022年 1-9页

作者： Varanasi, Praveen Kumar Nagaraja Rao, s. Duraiswamy, Punithavathi Department of Electrical Engineering M.S. Ramaiah University of Applied Sciences Banglore560054 India Department of Electronics and Communication Engineering M.S. Ramaiah University of Applied Sciences Banglore560054 India

This work presents a double boost converter (DBC) integrated with three-level diode clamped multilevel inverter (TLDCI). The proposed converter can be used for renewable energy, grid or electric vehicle applications. The double boost converter provides twice the output voltage in comparison with convention boost converter. The DBC is modelled and simulated under open loop and closed loop operating conditions. Proportional integral (PI) and fuzzy logic controllers (FLCs) are used in closed loop operation. The DBC further integrated with three-level diode clamped inverter. sine and third harmonic pulse width modulation (sPWm and TH-PWm) is used to generate pulses for TLDCI. The proposed converter simulated in mATLAB/simulink. Comparison results in open and closed loop such as output voltage error for double boost converter and line, phase voltages and total harmonic distortion for inverter output voltage and current are presented. © 2022, The Institution of Engineers (India).

关键词： Pulse width modulation

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Necessary and sufficient Condition for Triggering ECN before PFC in shared memory switches

IEEE Networking Letters

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IEEE Networking Letters 2024年第2期6卷 119-123页

作者： Luangsomboon, Natchanon Liebeherr, Jörg University of Toronto Department of Electrical and Computer Engineering TorontoONM5S 1A1 Canada

Flow control in a data center network (DCN) prevents packet losses by pausing transm.s.ions from upstream.s.itches, whereas congestion control prevents network overload by regulating traffic sources. For two widely deployed flow and congestion control algorithms, namely PFC and DCQCN, we derive a necessary and sufficient condition that ensures that congestion control mechanisms in a shared-memory switch are triggered before flow control. The condition creates an imbalance of buffer requirements at the ingress and egress of a switch. For fair queuing and priority scheduling at the egress, we present traffic scenarios that saturate the condition. The lack of such traffic scenarios for FIFO scheduling suggests that choosing appropriate schedulers may help reducing minimal buffer requirements. © 2019 IEEE.

关键词： Flow control

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m22: A Communication-Efficient Algorithm for Federated Learning Inspired by Rate-Distortion

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IEEE Transactions on Communications 2024年第2期72卷 845-860页

作者： Liu, Yangyi Rini, stefano salehkalaibar, sadaf Chen, Jun McMaster University Department of Electrical and Computer Engineering HamiltonONL8S 4L8 Canada Department of Electrical and Computer Engineering Hsinchu30010 Taiwan University of Toronto Department of Electrical and Computer Engineering TorontoONM5A 4T4 Canada

In federated learning (FL), the communication constraint between the remote clients and the Parameter server (Ps) is a crucial bottleneck. For this reason, model updates m.s. be compressed so as to minimize the loss in accuracy resulting from the communication constraint. This paper proposes 'm-magnitude weighted L2 distortion + 2 degrees of freedom' (m22) algorithm, a rate-distortion inspired approach to gradient compression for federated training of deep neural networks (DNNs). In particular, we propose a family of distortion measures between the original gradient and the reconstruction we referred to as ' m-magnitude weighted Lm ' distortion, and we assume that gradient updates follow an i.i.d. distribution-generalized normal or Weibull, which have two degrees of freedom. In both the distortion measure and the gradient distribution, there is one free parameter for each that can be fitted as a function of the iteration number. Given a choice of gradient distribution and distortion measure, we design the quantizer to minimize the expected distortion in gradient reconstruction. To measure the gradient compression performance under a communication constraint, we define the per-bit accuracy as the optimal improvement in accuracy that one bit of communication brings to the centralized model over the training period. Using this performance measure, we systematically benchmark the choice of gradient distribution and distortion measure. We provide substantial insights on the role of these choices and argue that significant performance improvements can be attained using such a rate-distortion inspired compressor. © 1972-2012 IEEE.

关键词： Deep neural networks

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