Scalable Internet of Things Enabled Intelligent Solutions for Proactive Energy Engagement in Smart Grids Predictive Load Balancing and Sustainable Power Distribution
- DOI
- 10.2991/978-94-6463-718-2_85How to use a DOI?
- Keywords
- IoT; smart grids; predictive load balancing; sustainable power distribution; scalability; real-time deployment; hybrid AI
- Abstract
IoT technologies enable smart grids to be more proactive than ever in energy engagement, allowing for predictive load balancing systems to optimize energy across the spectrum. By being implemented in a full-scale approach, being tested in real scenarios, and, having secure communication protocols running, this research overcomes the scalability issues and improves the resilience of the entire system. While existing studies are primarily focused on technical feasibility without assessing economic viability or environmental effects, this work provides an extended cost-benefit analysis for different stakeholders, explores hybrid AI techniques including performance mapping for real-time system optimization, and devises a new mechanism for real-time demand response pricing. Additionally, it also enables novel battery degradation mitigation strategies, user behavior analysis and edge AI for real-time grid management. This work will help lay the groundwork for wider adoption of scalable and secure Internet-of-Things (IoT) enabled smart grids to ensure longterm and sustainable energy dispatch by overcoming regulatory barriers for vehicle-to-grid (V2G) systems, as well as discussing cybersecurity and environmentally sustainable solutions.
- Copyright
- © 2025 The Author(s)
- 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
TY - CONF AU - M. SilpaRaj AU - R. Senthil Kumar AU - K. Jayakumar AU - M. Gopila AU - S. Senthil Kumar AU - Kazi Kutubuddin Sayyad Liyakat PY - 2025 DA - 2025/05/23 TI - Scalable Internet of Things Enabled Intelligent Solutions for Proactive Energy Engagement in Smart Grids Predictive Load Balancing and Sustainable Power Distribution BT - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024) PB - Atlantis Press SP - 1004 EP - 1016 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-718-2_85 DO - 10.2991/978-94-6463-718-2_85 ID - SilpaRaj2025 ER -