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 c oncerns. 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.
