Next-Generation Smart Grid Optimization: Integrating Edge AI for Real-Time and Decentralized Energy Management

Surya Narayan Sahu, K. Ruth Isabels, R. Gayathiri, A. Nagamani, V. Sriga, Elumalai P.

2025

Abstract

Nowadays, the development of smart grid systems require intelligent and real-time solutions in scalable fashion. This paper presents a new approach that combines edge computing and AI for decentralized and adaptable energy management in the context of distributed grid settings. Contrary to the typical cloud-based models, the proposed model utilizes edge AI enabling local data processing, shortened latency and quick decision-making. The approach is built based on federated learning and lightweight deep learning models, as well as considerations on privacy preserving and grid resilience against dynamic load demands and system failures. The performance of the system is additionally evaluated through simulation and benchmarked against centralized approaches, with results showing that the proposed framework achieves higher efficiency, scalability, and reliability in resource-limited edge environments. This research adds to the cornerstone of future smart grids that can accommodate sustainable and self-sufficient energy ecosystems.

Paper Citation

in Harvard Style

Sahu S., Isabels K., Gayathiri R., Nagamani A., Sriga V. and P. E. (2025). Next-Generation Smart Grid Optimization: Integrating Edge AI for Real-Time and Decentralized Energy Management. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 316-322. DOI: 10.5220/0013863300004919

in Bibtex Style

@conference{icrdicct`2525,
author={Surya Sahu and K. Isabels and R. Gayathiri and A. Nagamani and V. Sriga and Elumalai P.},
title={Next-Generation Smart Grid Optimization: Integrating Edge AI for Real-Time and Decentralized Energy Management},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25},
year={2025},
pages={316-322},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013863300004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 1: ICRDICCT`25
TI - Next-Generation Smart Grid Optimization: Integrating Edge AI for Real-Time and Decentralized Energy Management
SN - 978-989-758-777-1
AU - Sahu S.
AU - Isabels K.
AU - Gayathiri R.
AU - Nagamani A.
AU - Sriga V.
AU - P. E.
PY - 2025
SP - 316
EP - 322
DO - 10.5220/0013863300004919
PB - SciTePress