Internet of Things and AI in Smart Grid Applications

Abstract

The shrewd matrix, otherwise called the mix of sensors and correspondence innovation into power organizations, is a new improvement in science and innovation. The shrewd network's uplifted weakness to cyberthreats is one of its primary issues. Consequently, the writing suggests a number of safeguards and risks. This article provides a bibliographic overview of the security implications of IoT-backed smart grids. To the best of the authors' knowledge, this is without a doubt the first bibliometric survey article on this subject. All journal passages are given a bibliometric examination, and the outcomes are coordinated by dates, first sentences, and primary contemplations. Moreover, this piece verifiably sums up the few cyberthreats that the astute organization experiences, the different security moves toward that have been recommended in the composition, and the exploration holes in the field of smart structure security. The smart grid, a modernized form of energy infrastructure that makes use of cutting-edge communication and information technology, is taking the place of traditional power grids. Through improved management of informational flows that occur alongside inherent energy flows during transmission, distribution, or generation procedures, this integration of IoT technology—known within the energy sector as the Power internet of things (PIoT)—provides improved efficiency. This article supports adding value streams to existing smart grids, focusing on the untapped potential of innovative services and market mechanisms and enhancing efficiency through the exchange of valuable information to supplement scarce sources and the latest 5G developments. Energy production and distribution to all electrical grid users are changing. The goal of the Savvy Network (SG) concept was to change how the capabilities and electrical matrix base were managed by the flow framework. One of these undertakings — estimating customers' energy utilization — has proactively been changed over in a few countries from unpredictable, manual readings to additional successive, programmed readings, leading to brilliant meters (SM). Technology could help SM systems by making it easier to distribute energy more evenly throughout the infrastructure and by making it easier to get information about how much energy each user uses.