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Decentralized and Distributed Control Strategies for Microgrids: A Review of Key Techniques and Applications

Decentralized and Distributed Control Strategies for Microgr...

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2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Sarathkumar, D. Maheswari, P. Manivel, Murugesan Jayakumar, T. Sivakumar, R. Parrthipan, B.K. Kongu Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638060 India Excel Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638052 India Karpagam Institute of Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore641021 India Nandha Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638052 India V.S.B Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 639111 India Kamaraj College of Engineering and Technology Department of Mechanical Engineering Tamil Nadu Vellakulam625701 India

ISBN: (纸本)9798331529833

Microgrids have emerged as a key solution for enhancing the flexibility, reliability, and sustainability of power systems. As the penetration of renewable energy sources and distributed generation increases, effective control strategies are essential for ensuring stable and efficient microgrid operation. This paper presents a comprehensive review of decentralized and distributed control strategies for microgrids, highlighting their significance in enabling scalability, robustness, and resilience. Key techniques, such as primary, secondary, and tertiary control layers, are discussed, with a focus on the transition from centralized to decentralized paradigms. The review explores the application of advanced algorithms like multi-agent systems (MAS), consensus-based control, and artificial intelligence (AI) for optimizing power sharing, voltage regulation, frequency stability, and energy management in islanded and grid-connected modes. Additionally, the paper analyzes the challenges and opportunities in implementing decentralized and distributed control, with real-world case studies and simulation-based insights to demonstrate their effectiveness in various microgrid configurations. Finally, potential future research directions are suggested to address emerging trends such as peer-to-peer energy trading, blockchain-based energy systems, and the integration of electric vehicles (EVs) into microgrid networks. © 2025 IEEE.

关键词： Decentralized control

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An Innovative Method to Detect Cyberbullying on Social Media 3

An Innovative Method to Detect Cyberbullying on Social Media

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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Pandiaraja, P. Muthumanickam, K. Geetha, M. Mahesh, P.C. Senthil Vedhashree, S.K. Selvarathi, C. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai600062 India Kongunadu College of Engineering and Technology Department of Information Technology Tholurpatti Tamil Nadu Trichy621215 India M.Kumarasamy College of Engineering Department of Computer Science and Engineering Karur639113 India Excel Engineering College Department of Computer Science and Engineering Tamilnadu Komarapalayam637303 India Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore641021 India

ISBN: (纸本)9798331509675

Today social media has fundamentally altered global communication and information exchange. However, as these platforms have become more widely used, so has cyber-hatred which is a significant problem that has caught academics' attention. This article has been addressed by a variety of methods from deep learning and machine learning, including recurrent neural networks, convolutional neural networks, logistic regression, and Naive Bayes. These techniques distinguish between various classes using mathematical concepts. However, sentiment-oriented data offers an accurate picture of how the public reads communications online, accurate classification necessitates a more "critical thinking"perspective. Two machine learning classifiers were employed in this study, one of which was built on a review of the literature to look at efficient classification techniques. Four online hatred datasets using logistic regression and multinomial naive Bayes. To better grasp the text in the datasets, the classifier results were enhanced by using XG-Boost algorithm. © 2025 IEEE.

关键词： Adversarial machine learning

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Analysis of Performance Characteristics on TiO2 and ZrO2 Nano Fillers Coated Single Phase Transformers Through Sumpner or Regenerative Test 1

Analysis of Performance Characteristics on TiO2 and ZrO2 Nan...

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1st IEEE International Conference on Smart Power Control and Renewable Energy, ICSPCRE 2024

作者： Deepak, M. Santhakumar, C. Vasantharaj, A. Dineshkumar, P. Mohamedyaseen, A. Manokaran, J. KIT-Kalaignarkarunanidhi Institute of Technology Department of Eee Coimbatore641402 India Ksr College of Engineering Department of Eee Tiruchengode637215 India Annamachariya Institute of Technology and Science Department of Eee Tirupathi India Excel Engineering College Department of Ece Pallakkapalayam637303 India Srm Institute of Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798350377002

Nano filler materials consist of different combinations of nano dimensions with distinct and unique differences in structure, chemistry, electrical and mechanical properties. Nanoparticles improve the electrical, thermal and mechanical properties of high-voltage electrical equipment. It plays an important role in improving the functions of electrical machines. Sumpner's test or back-to-back test on the transformer is used for determining transformer efficiency and heating under loaded conditions. Short circuit and open circuit tests on the transformer can give us parameters of an equivalent circuit of the transformer, but they are not helpful in finding the heating information. Thus, Sumpner's test gives more accurate results on efficiency than O.C. and S.C. tests. In this paper special focus has been given on two identical single-phase transformers connected in back-to-back connection. In order to reduce the variable copper loss, TiO2 and ZrO2 Nanofillers have been tested and evaluated with different proportions of concentration with the base coating solution. It has been experimentally proved that the addition of a 15% concentration of TiO2 and ZrO2 Nano filler has significant improvement in the reduction of variable copper loss in the transformers as compared to uncoated normal transformers. © 2024 IEEE.

关键词： Titanium dioxide

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An extensive critique of various modern optimization techniques for electric vehicles and their applications

An extensive critique of various modern optimization techniq...

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2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Sarathkumar, D. Arun Shunmugam, D. Maheswari, P. Sajin, J.B. Jayakumar, T. Manivel, Murugesan Bashkaran, K. Kongu Engineering College Department of Electrical and Electronics Engineering Tamil Nadu India Psr Engineering College Department of Electronics and Communication Engineering Tamil Nadu Sivakasi626140 India Excel Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638052 India Sree Buddha College of Engineering Department of Mechanical Engineering Kerala Pattoor690 529 India Nandha Engineering College Department of Electrical and Electronics Engineering Tamil Nadu 638052 India Karpagam Institute of Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore641021 India Kongunadu College of Engineering and Technology Department of Biomedical Engineering Tamil Nadu Thottiam621215 India

ISBN: (纸本)9798331529833

The rapid advancement of electric vehicles (EVs) has prompted significant research into optimizing their performance, efficiency, and integration into smart grid systems. This paper provides an extensive critique of modern optimization techniques applied to EVs, covering areas such as battery management, energy consumption, routing, and charging infrastructure. We analyze both traditional and emerging optimization methods, including heuristic algorithms, machine learning approaches, and hybrid techniques. The paper evaluates these methods in terms of computational efficiency, scalability, adaptability, and real-world applicability. Furthermore, we discuss the challenges and future directions for optimizing EVs in the context of evolving technologies and infrastructures. By synthesizing the latest research findings, this critique aims to offer a comprehensive understanding of the strengths and limitations of various optimization strategies, providing valuable insights for researchers, engineers, and policymakers involved in the development and deployment of electric vehicles. © 2025 IEEE.

关键词： Heuristic algorithms

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Influence of nano additive blended watermelon seed biodiesel on the performance and exhaust emissions of a VCR compression ignition engine 5

Influence of nano additive blended watermelon seed biodiesel...

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5th International eConference on Frontiers in Materials engineering and nanotechnology, ICFMET 2023

作者： Sachuthananthan, B. Vinoth, R. Padmaja, N. Sachidananda, K.B. Kanna Kumar, J. Sree Vidyanikethan Engineering College Andhra Pradesh Tirupathi517102 India Excel Engineering College Tamilnadu Namakkal637303 India K v Subba Reddy Institute of Technology Andhra Pradesh Kurnool India

An innovative idea have been proposed in this work, to increase fuel efficiency and minimize emission from Diesel engine. This research mainly focuses on the systhesis of two nano materials namely MgO, TiO2. The synthesized nano additives was blended in equal proportion with Biodiesel prepared from Watermelon seed oil through the process of trans-esterification. Then 20% Biodiesel was mixed with 80% diesel and now the fuel is called as B20. Equal proportion of MgO and TiO2 mixture was prepared which is called as Nano Additive Mix(NAM) and added with B20 blend. A 5HP mono Barrel Diesel engine was powered with B20 and with various proportion of NAM in the range of 50ppm, 100ppm, 150ppm and 200ppm. The results obtained revealed that B20 blended with NAM150 minimized CO, HC and Smoke emission considerably when equated to other mixtures. The BTE at peak load for Diesel was 28.4% and for the same load it was 28.2% for B20 @ NAM150 blend. The B20 with 150NAM blend become the best alternative fuel combination to operate the engine with less emission and best fuel consumption and power output. © Published under licence by IOP Publishing Ltd.

关键词： Diesel engines

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Detecting Evolving Fake News in Social Media by Leveraging Heterogeneous Deep Learning Model

Detecting Evolving Fake News in Social Media by Leveraging H...

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International Conference on Advances in Information technology (ICAIT)

作者： B.M. Brinda C. Rajan K. Geetha Computer Science and Engineering Paavai College of Engineering Namakkal Information Technology KSR College of Technology Thiruchengode Computer Science and Engineering Excel Engineering College Komarapalayam

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

A recent study revealed that fake articles spread considerably faster than factual content on Twitter, specifically at a 70% higher rate of retweets and reaching the first 1,500 users six times faster. This highlights the urgent need for scalable automated detection solutions to combat the pervasive threat of fake news online. While machine learning methods often rely solely on semantic text analysis, evolving fake news campaigns mimic genuine news, employing tactics like bot networks and sophisticated language imitation. This renders text-based meth- ods increasingly vulnerable. To address this challenge,we propose a heterogeneous deep learning model that incorporates richer information beyond text, specifically dissemination structure features from social networks. These features capture aspects like user interactions, sharing patterns, and network topology, providing valuable insights into the spread of information. Our model leverages the sentiment and affects the enriched Alt dataset for text analysis. Instead of using a popular language model called BERT, we explore alternative pre-trained language models like the Sentence Transformer, which focuses on capturing con- textual sentence embeddings, or the Universal Language Model (ULMFiT), which excels at understanding semantic relationships within text. Additionally, we consider spaCy, a versatile NLP library offering similar functionalities for text processing and feature extraction. While The Quint Dataset Challenge Dataset lacks sentiment annotations, it could be a potential alternative to Alt depending on research goals. This network-aware approach achieves an impressive 95.27% accuracy on The Boom Live dataset and demonstrates generalizability to The Quint dataset with 92.1% accuracy, highlighting its effectiveness in combatting evolving fake news tactics.

关键词： Deep learning Analytical models Accuracy Text analysis Social networking (online) Text recognition Semantics

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Design and Fabrication of Aluminium Nitride Based Micro Cantilever Sensor for the Detection of Carbon Dioxide

Design and Fabrication of Aluminium Nitride Based Micro Cant...

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2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Rao, Arjun Sunil Guru Prasad, B. Sannakashappanavar, Basavaraj S. Rashmi, K.R. Manipal Academy of Higher Education Department of Electronics and Communication Engineering Karnataka Manipal India Alva's Institue of Engineering and Technology Department of Electronics and Communication Engineering Moodbidri India Dayananda Sagar College of Engineering Department of Electronics and Communication Engineering Bangalore India Excel Pre-University College Department of Physics Guruvayankere India

ISBN: (纸本)9798331540821

In this work, we describe the design and fabrication of the microcantilever for CO2 detection employing a new aluminum nitrate. The microcantilever was designed using COMSOL Multiphysics, and it was then fabricated using a combination of bulk and surface micromachining techniques. A Laser Doppler Vibrometer (LDV) was used to test the devices and determine their resonant frequency, while a Field Emission Scanning Electron Microscope (FESEM) was used to analyze the device's dimensions. The fabricated device displays first harmonics at 729 Hz, second harmonics at 845 Hz, and third harmonics at 2191 Hz. Subsequently, the developed device was utilized with a gas sensor setup to detect CO2, and it responded well to the gas. In conclusion, there is a strong correlation between the synthesized device properties and the simulated outcomes obtained from the resonant frequency calculation. © 2024 IEEE.

关键词： Aluminum nitride

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Whale Optimization Algorithm Based Improved Convolutional Neural Network for Breast Cancer Detection and Diagnosis 2

Whale Optimization Algorithm Based Improved Convolutional Ne...

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2nd International Conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Alzubaidi, Laith H. Soundariya, R.S. Madhavan, Sowmya Selvaraju, P. Aarati, K. The Islamic University Najaf Iraq Bannari Amman Institute of Technology Department of Computer Technology Sathyamangalam India Nitte Meenakshi Institute of Technology Dept of Ece Bengaluru India Excel Engineering College Department of Ai and Ds Namakkal Komarapalayam India Malla Reddy Engineering College for Women Dept of Cse Maisamma guda Hyderabad India

ISBN: (纸本)9798350382952

The breast cancer is a hazardous disease through the huge mortality and morbidity rate and its detection id identified as important health issues in nowadays. Numerous studies have conducted to categorize the patients into benign and malignant but the significance of the issues and efforts are continuing. This paper proposed a Whale Optimization Algorithm based Improved Convolutional Neural Network (WOA-ICNN) for breast cancer detection and diagnosis. The BCWD dataset is utilized and preprocessed through data normalization. Then, the features are extracted by Grey Level Cooccurrence Matrix (GLCM) and selected by WOA. The selected features are given to ICNN for early detection and diagnosis of breast cancer. The accuracy, precision, recall and f1-score are utilized for estimating WOA-ICNN performance. The WOA-ICNN obtains 99.16% accuracy, 98.75% precision, 98.87% recall and 98.66% f1-score which is better than existing algorithms like Fast-Learning Network (FLN), optimized Deep Recurrent Neural Network (RNN), Multi-Layer Perceptron (MLP) based homogeneous ensemble. © 2024 IEEE.

关键词： Convolutional neural networks

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Fruits Freshness Recognition System by Manipulating Versatile Neural Networks

Fruits Freshness Recognition System by Manipulating Versatil...

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2023 International Conference on Circuit Power and Computing Technologies, ICCPCT 2023

作者： Sharmila, A. Tamilselvan, K.S. Dhivya Priya, E.L. Yuvaraj, D. Soundarya, B. Ambika, K.S. Bannari Amman Institute of Technology Dept of ECE Erode India KPR Institute of Engineering and Technology Dept of ECE Coimbatore India Erode Sengunthar Engineering College Dept of ECE Erode India Kongu Engineering College Dept of CSD Erode India Excel Engineering College Dept of EEE Namakkal India

ISBN: (纸本)9798350333244

Fruits are the prerequisite authority of nutrition. Consuming fresh fruits on a daily basis is good for health. Fruits are the consequential provenance of income for farmers. Harvesting of fruits takes place after it acquires its matured state. The farmers has to separate the harvested fruit as fresh fruit or rotted or raw fruits before selling them. Predicting the fresh fruits for selling and purchasing for regular use by customers is still an intricate endeavor. The traditional methods of determining the ripeness and rottenness of fruits takes time. It requires a huge man power for detection. Sorting of fruits, peculiarly the ripened fruit first to sold them in market prior to the raw fruits is vital. As the maturated fruit are highly prone to decay than the others. Employing recent techniques in agriculture immensely assists farmers. In some instances, the fresh fruits and rottenness fruits looks similar in texture and color. Disparate fruits upon freshness is an exigent venture. The proposed work makes use of DenseNet architecture so as to concede and grade the freshness of fruits. The initiated work incorporates layers of CNN comprising convolutional layers, maximum pooling layers, flattening and fully interconnected neural nets incorporating numerous layers for detecting and sorting the fresh fruits. The proposed work gains an accuracy of 98 % in recognition of freshness of fruits. © 2023 IEEE.

关键词： Fruits

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Farmoline - The New Age Agro Drone in Modern Embedded Agriculture to Spray Healthy Organic Pesticides 15

Farmoline - The New Age Agro Drone in Modern Embedded Agricu...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sathesh, S. Maheswaran, S. Navanithi, K. Dhivakar, R.S. Dhushyanth, R. Ajay, K. Mohanaprasath, K.V. Giri, K. Kongu Engineering College Perundurai Department of Electronics and Communication Engineering Tamil Nadu Erode638060 India KGiSL Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Kongu Engineering College Perundurai Department of ECE Tamil Nadu Erode638060 India Excel Engineering College Department of Electronics and Communication Engineering Tamil Nadu Komarapalayam637303 India Velalar College of Engineering & Technology Thindal Department of Bio Medical Engineering Tamil Nadu Erode638012 India

ISBN: (纸本)9798350370249

The utilization of unmanned aerial vehicles (UAVs), popularly known as drones, in the agricultural sector has garnered notable attention as a possible means of enhancing efficiency and productivity in crop care and management. Therefore, this research project proposes the creation of an atmospherically regulated automotive spraying mechanism utilizing drones for agricultural applications. The principal objective of this study is to replace manual labour with an automated and eco-friendly solution that promotes sustainable farming practices. To tackle the challenge of accurately and precisely spraying the required quantity of enzymes to crops, this research project has implemented a wired configuration, which comprises poles and pulleys to create a stable spraying system. This approach guarantees meticulous and controlled movements of the drones while simultaneously reducing the payload by providing wired supplies in place of heavy batteries. By utilizing tethered drones with a remarkable payload capacity of 5-liters, the research project aims to extend flight time and coverage area, thereby enabling efficient spraying over vast agricultural land. Furthermore, the replacement of chemical fertilizers and pesticides with enzymes and natural agents minimizes environmental pollution and reduces chemical dependency, thereby creating a cleaner and greener farming ecosystem. The proposed drone-based spraying system offers a practical and sustainable solution for small-scale farming, thereby enabling farmers to automate crop care operations and decrease reliance on harmful chemicals. With autonomous operation and minimal human intervention, farmers can allocate their time and resources more effectively while ensuring efficient and effective crop management. This research project contributes to the advancement of agricultural practices by integrating the capabilities of drone technology and considering environmental factors into crop care operations. The following sections de

关键词： Drones

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