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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Advances in Applied Sciences Bulletin of Electrical Engineering and Informatics
Srilakshmi, S. Sai
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Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Islanding detection of integrated DG system using rate of change of frequency over reactive power Kumari, B. V. Seshu; Prasad, Ambati Giri; Srilakshmi, S. Sai; Buchireddy, Karri Sairamakrishna; Reddy, Ch. Rami
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i3.pp1637-1644

Abstract

This paper offers a passive islanding detection method that is effective for distributed generation. When a distributed generator (DG) keeps a location powered even when access to the external electrical grid is lost, this circumstance is referred to as islanding. The power distribution system currently includes distributed generators (DGs), which provide inexpensive electricity and have fewer environmental impacts. Sometimes, these DGs continue to supply the nearby loads because of line outages and islands made by system separations. As a result, there are scenarios with unacceptable power quality. The islanding is identified if the result of the rate of change of frequency over reactive power exceeds the threshold value. The MATLAB test results from this study demonstrate the effectiveness of the suggested approach for different islanding and non-islanding scenarios.
Real-time vehicle detection and speed estimation system using Raspberry Pi and camera module Jyothi, B; Pabbuleti, Bhavana; Sanjeev, Gadi; Rao, Kambhampati Venkata Govardhan; Srilakshmi, S. Sai; Jee, Atul; Kumar, Malligunta Kiran; Bikku, Thulasi; Reddy, Ch. Rami
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9931

Abstract

In the era of intelligent transportation systems, real-time vehicle detection and distance estimation play a crucial role in enhancing road safety and traffic efficiency. This study proposes a low-cost, real-time system that integrates you only look once–version 8 (YOLOv8)-based deep learning for vehicle detection with monocular vision techniques for distance estimation, implemented on a Raspberry Pi embedded platform. The objective is to provide a scalable, affordable solution for traffic monitoring and collision avoidance in resource-constrained environments. The methodology involves using a camera module connected to Raspberry Pi for live video capture, YOLOv8 for object detection, and a calibrated monocular distance estimation algorithm based on bounding box dimensions and known vehicle sizes. Experimental results show that the system achieves over 90% detection accuracy under standard lighting conditions and maintains a distance estimation error below 10% for vehicles within 15 meters. The model processes video frames in real time (~0.17 seconds per frame), proving its effectiveness for embedded deployment. In conclusion, the proposed system offers a robust, power-efficient alternative to high-cost light detection and ranging (LiDAR) or stereo vision systems. Its modular design supports future enhancements such as speed estimation or multi-camera integration, making it highly relevant for smart city applications and low-cost vehicular safety systems.
Optimizing smart grids with blockchain-driven automation and demand response Jyothi, B.; Pabbuleti, Bhavana; Ponnala, Ravi; Rao, Kambhampati Venkata Govardhan; Srilakshmi, S. Sai; Narasimha, Putta Dhanush; Yadav, Mareboyina Karthik; Kumar, Malligunta Kiran; Reddy, Ch. Rami
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp985-998

Abstract

To increase resilience, efficiency, and engagement in the network, it shall develop and test its smart grid system integrating blockchain-based authentication and automated demand response management. Simulations are made on the dynamic behavior of the grid in energy generation, consumption, and management through demand responses through MATLAB/Simulink assessment of performance and stability. Ethereum is used in implementing and managing smart contracts that automate and secure events of demand response and consumer interactions for transparency in transactions. It uses Python with Pandas to process, analyze, and visualize simulation data that gives insight into the effectiveness of demand response strategies; PostgreSQL supports the structured storage and querying of data with comprehensive data management. Proper integration of such tools can result in the proper robust simulation of the smart grid system that is highly reliable, efficient usage of energy, and can empower consumers through secure, efficient demand response mechanisms. These immediate issues about managing the grid can thus solve the way toward the future development of such smart grid technologies and their possible integration with the blockchain.
Co-Authors Bikku, Thulasi Buchireddy, Karri Sairamakrishna Jee, Atul Jyothi, B Jyothi, B. Kumari, B. V. Seshu Malligunta Kiran Kumar Narasimha, Putta Dhanush Pabbuleti, Bhavana Ponnala, Ravi Prasad, Ambati Giri Rao, Kambhampati Venkata Govardhan Reddy, Ch. Rami Sanjeev, Gadi Yadav, Mareboyina Karthik