Edge Intelligence in Smart Grids: A Survey on Architectures, Offloading Models, Cyber Security Measures, and Challenges

Author:

Molokomme Daisy NkeleORCID,Onumanyi Adeiza JamesORCID,Abu-Mahfouz Adnan M.ORCID

Abstract

The rapid development of new information and communication technologies (ICTs) and the deployment of advanced Internet of Things (IoT)-based devices has led to the study and implementation of edge computing technologies in smart grid (SG) systems. In addition, substantial work has been expended in the literature to incorporate artificial intelligence (AI) techniques into edge computing, resulting in the promising concept of edge intelligence (EI). Consequently, in this article, we provide an overview of the current state-of-the-art in terms of EI-based SG adoption from a range of angles, including architectures, computation offloading, and cybersecurity concerns. The basic objectives of this article are fourfold. To begin, we discuss EI and SGs separately. Then we highlight contemporary concepts closely related to edge computing, fundamental characteristics, and essential enabling technologies from an EI perspective. Additionally, we discuss how the use of AI has aided in optimizing the performance of edge computing. We have emphasized the important enabling technologies and applications of SGs from the perspective of EI-based SGs. Second, we explore both general edge computing and architectures based on EI from the perspective of SGs. Thirdly, two basic questions about computation offloading are discussed: what is computation offloading and why do we need it? Additionally, we divided the primary articles into two categories based on the number of users included in the model, either a single user or a multiple user instance. Finally, we review the cybersecurity threats with edge computing and the methods used to mitigate them in SGs. Therefore, this survey comes to the conclusion that most of the viable architectures for EI in smart grids often consist of three layers: device, edge, and cloud. In addition, it is crucial that computation offloading techniques must be framed as optimization problems and addressed effectively in order to increase system performance. This article typically intends to serve as a primer for emerging and interested scholars concerned with the study of EI in SGs.

Funder

Council for Scientific and Industrial Research

Publisher

MDPI AG

Subject

Control and Optimization,Computer Networks and Communications,Instrumentation

Reference239 articles.

1. A novel edge-supported cost-efficient resource management approach for smart grid system;Mishra,2018

2. Cost-efficient tasks scheduling for smart grid communication network with edge computing system;Yao;Proceedings of the 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC),2019

3. A Review of Cognitive Radio Smart Grid Communication Infrastructure Systems

4. Smart Grids and Their Communication Systems;Kabalci,2019

5. Prosumer in smart grids based on intelligent edge computing: A review on Artificial Intelligence Scheduling Techniques;Slama;Ain Shams Eng. J.,2021

Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Artificial Intelligence of Things (AIoT) for smart agriculture: A review of architectures, technologies and solutions;Journal of Network and Computer Applications;2024-08

2. Intelligent data-driven condition monitoring of power electronics systems using smart edge–cloud framework;Internet of Things;2024-07

3. Detecting Aberrations in Renewable Energy With the One-Class Support Vector Machine Model;Advances in Environmental Engineering and Green Technologies;2024-05-17

4. Edge Offloading in Smart Grid;Smart Cities;2024-02-19

5. TinyML for 5G networks;TinyML for Edge Intelligence in IoT and LPWAN Networks;2024

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3