Electrical Grid Load Balancing using Real-Time Big Data Analytics

Main Article Content

ER. SIDDHARTH Agarwal

Abstract

The increasing demand for electricity, coupled with the necessity for efficient energy management, has necessitated innovative approaches to load balancing in electrical grids. This paper explores the application of real-time big data analytics to optimize load distribution across electrical grids. By leveraging data from various sources, including smart meters, weather forecasts, and historical consumption patterns, this study presents a framework for dynamic load balancing. A statistical analysis demonstrates the effectiveness of the proposed approach, showcasing significant improvements in efficiency and reliability. The findings highlight the potential for real-time analytics to enhance decision-making processes in electrical grid management, ultimately leading to a more sustainable and resilient energy infrastructure.

Article Details

How to Cite
Agarwal, E. S. (2024). Electrical Grid Load Balancing using Real-Time Big Data Analytics. Journal of Quantum Science and Technology (JQST), 1(3), July(76–85). Retrieved from https://jqst.org/index.php/j/article/view/49
Section
review article

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• Author : Harshita Cherukuri1, Villa 188, My Home Ankura, Sector B, Radial Road-7, Exit No 2, Tellapur, Cyberabad-sangareddy, 502032, Telangana, India , Dr. Bhawna Goel , Dr. Poornima Tyagi

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