Artificial Intelligence Enabled Smart Energy Conservation Systems for Intelligent Resource Management and Sustainable Future Power Grids

Xma R. Pote; Avinash Pamisetty; G. Karthikeyan; Deepak Gupta; R. Senthil Kumar; D. Beula

doi:10.2991/978-94-6463-718-2_18

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Artificial Intelligence Enabled Smart Energy Conservation Systems for Intelligent Resource Management and Sustainable Future Power Grids

Authors

Xma R. Pote¹^{, *}, Avinash Pamisetty², G. Karthikeyan³, Deepak Gupta⁴, R. Senthil Kumar⁵, D. Beula⁶

¹Assistant Professor, Department of Electrical Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, Maharashtra, India

²Integration Specialist, Millsboro, DE, USA

³Associate Professor, Department of EEE, Sona College of Technology, Salem, Tamil Nadu, India

⁴Department of Mechanical Engineering, Graphic Era Hill University, Dehradun, Uttarakhand, India

⁵Assistant Professor, Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu District, Chennai, Tamil Nadu, India

⁶Assistant Professor, Department of Physics, New Prince Shri Bhavani College of Engineering and Technology, Chennai, Tamil Nadu, India

^*Corresponding author. Email: potexma@gmail.com

Corresponding Author

Xma R. Pote

Available Online 23 May 2025.

DOI: 10.2991/978-94-6463-718-2_18 How to use a DOI?
Keywords: Artificial Intelligence; Smart Energy Conservation; Sustainable Power Grids; Energy Optimization; Edge Computing; Real-Time Processing; Cybersecurity; Resource Management; Renewable Energy; Economic Feasibility
Abstract: Incorporation of Artificial Intelligence (AI) into Energy Management Systems for resource optimization and smart power grid development. While previously, research literature has set a foundation of AI for developing energy solutions, implemented and scale capabilities of practical efforts, like networks, real-time issues and resilience to environmental perturbations to scales, are found with lots of gaps which are yet to be covered. To alleviate these challenges, this work proposes an AI-based energy saving system with real-time data analytics, edge computing, and improved cyber security. The model is designed to maximize energy milestones, enhance resilience to extreme weather and make the plan economically viable on a total cost basis. This paper proposes an intelligent power grid resource management solution with high practical applicability and flexibility. Results show more effective, more reliable and more secure way forward towards a modern sustainable energy infrastructure.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series: Advances in Computer Science Research
Publication Date: 23 May 2025
ISBN: 978-94-6463-718-2
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-718-2_18 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Xma R. Pote
AU  - Avinash Pamisetty
AU  - G. Karthikeyan
AU  - Deepak Gupta
AU  - R. Senthil Kumar
AU  - D. Beula
PY  - 2025
DA  - 2025/05/23
TI  - Artificial Intelligence Enabled Smart Energy Conservation Systems for Intelligent Resource Management and Sustainable Future Power Grids
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 196
EP  - 207
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_18
DO  - 10.2991/978-94-6463-718-2_18
ID  - Pote2025
ER  -

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