IJSDIP | International Journal of System Design & Info Processing

Edge Computing for Real-Time Data Processing in Smart Grids: Reducing latency and improving the reliability of energy distribution systems

Paper ID:

IJSDIP_2025_VOLUME 13_ISSUE 4_126-133

Author's Name:

Dr.D.Jayahar, Prof. Atul B Pawar, Prof. Chandrakant Kakasaheb Shejwal, Prof. Sanghamitra T Kamble

Volume:

Issue:

Issue 4

Year:

2025

Pages:

126-133

Abstract

The complexity of the modern energy system is such that smart grids need high operational reliability, low-latency communication, and fast data processing. Conventional cloud-based systems have difficulties with latency and bandwidth constraints, particularly, when subjected to variability of loads in real time, to intermittent renewable production, and grid faults. In this paper, the author aims to explore how edge computing can be integrated to process real-time data on smart grids to minimize latency and improve the reliability of energy distributions. Through the decentralization of the computational functions to edge nodes that are much near to sensors, meters, and intelligent electronic devices (IEDs), data can be processed in milliseconds as opposed to utilizing remote cloud networks. The suggested model shows that edge-enabled smart grids are much more efficient than traditional solutions in regard to response duration, accuracy of fault detection and resistance to communication failures. Optimal results of experimental simulations depict a latency of up to 35 60 percent less and a 40 percent enhancement in system reliability under peak load perturbation. Evidence-based constraints are cost of deploying edge-nodes, interoperability, data synchronization, and cybersecurity. Future studies can consider federated learning in distributed grid intelligence, sophisticated prediction models of faults, and standardized edge models to enable the next-generation energy system.

Keywords

Edge computing, smart grids, latency reduction, energy distribution reliability, real-time processing, intelligent edge nodes, distributed energy systems

References

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DOI: https://doi.org/10.64971/j.cph.ijsdip.v13.i4.18.2025