Method And Process of Energy Cloud Clustering Mechanism Using Cloud Computing Models

Authors

  • Sonam Chikara, Dr. Nishant Kumar Pathak

Keywords:

Energy Cloud, Cloud Computing Models, Clustering Mechanism, Energy Efficiency, Resource Optimization, Renewable Energy Integration, Smart Grids, Data Analytics, Green Computing.

Abstract

The increasing global demand for energy and the urgent need for sustainable resource management have prompted the development of innovative solutions. This research introduces an Energy Cloud Clustering Mechanism (ECCM) that leverages cloud computing models to optimize energy resource management. ECCM employs advanced data analytics and machine learning techniques to categorize diverse energy resources, including renewables (e.g., solar, wind, and hydroelectric), fossil fuels, and energy storage systems. By creating intelligent clusters based on resource characteristics and geographical distribution, ECCM enhances the efficiency of energy allocation and distribution. The scalability and adaptability offered by cloud computing ensure ECCM's responsiveness to changing energy supply and demand patterns, enhancing the resilience and sustainability of the energy ecosystem. This paper details ECCM's architecture, components, and practical applications, accompanied by case studies and simulation results, demonstrating its potential to revolutionize energy management for a greener and more sustainable future.

Published

2023-10-16

How to Cite

Sonam Chikara, Dr. Nishant Kumar Pathak. (2023). Method And Process of Energy Cloud Clustering Mechanism Using Cloud Computing Models. SJIS-P, 35(3), 463–468. Retrieved from http://sjisscandinavian-iris.com/index.php/sjis/article/view/698

Issue

Section

Articles