Edge Computing and Internet of Things (IoT) for Real-time Energy Analytics in Smart Grids

Edi Leksono, Justin Pradipta, Bastian Z Nur

Abstract


Real-time energy analytics in smart grids require timely data processing and decision-making. This paper explores the integration of edge computing and the Internet of Things (IoT) for real-time energy analytics in smart grids. We propose an architecture that leverages edge devices and IoT sensors for data collection, localized data processing, and real-time insights. By distributing computational tasks to edge devices, we reduce communication latency, improve scalability, and enable near real-time decision-making. Through extensive simulations and case studies, we demonstrate the effectiveness of our approach in load balancing, fault detection, and grid stability. We discuss the integration challenges, resource management, and scalability considerations associated with deploying edge-enabled IoT solutions for real-time energy analytics in smart grids.

References


Kitagami, Shinji, et al. ‘Proposal of a Multi-Agent Based Flexible IoT Edge Computing Architecture Harmonizing Its Control with Cloud Computing’. 2017 Fifth International Symposium on Computing and Networking (CANDAR), IEEE, 2017, pp. 223–229.

Liu, Yi, et al. ‘Intelligent Edge Computing for IoT-Based Energy Management in Smart Cities’. IEEE Network, vol. 33, no. 2, IEEE, 2019, pp. 111–117.

Singh, Shailendra, and Abdulsalam Yassine. ‘IoT Big Data Analytics with Fog Computing for Household Energy Management in Smart Grids’. Smart Grid and Internet of Things: Second EAI International Conference, SGIoT 2018, Niagara Falls, ON, Canada, July 11, 2018, Proceedings 2, Springer, 2019, pp. 13–22.

Yu, Wei, et al. ‘A Survey on the Edge Computing for the Internet of Things’. IEEE Access, vol. 6, IEEE, 2017, pp. 6900–6919.


Refbacks

  • There are currently no refbacks.




Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.