Abstract
Smart Grid technology has been considered an attractive research issue due to its efficiency in solving energy demand, storage, and power transmission. The integration of IoT technology in the Smart Grids is a critical way to accelerate the digitization of the power grid and is useful for the efficient performance of the energy grid infrastructure. For efficient real-time data analysis and decision-making, the Internet of Things will incorporate various communication systems seamlessly. To achieve efficient communication between all Internet of Things, devices are expected to use multiple means, including smart sensors, cable and wireless communication. Improved Internet of Things sensor technologies and connectivity could theoretically prevent or minimize the potential to natural disaster transmission lines, improve transmission power capacity and reduce economic losses. A smart grid is a variety of sensors, devices, and data sets that continuously capture high-resolution data equal to individual IoT conditions. A vast amount of data is one of the biggest challenges on the Internet of Things. Edge Computing is trying to process data close to linked sensors to address this problem, where the data is gathered and processed. This paper aims to investigate the edge computing solutions for the smart grid. A comprehensive review of both emerging issues and edge computing in the Smart Grid environment is discussed and explained. There are two primary components to the energy sharing process among Prosumers: information/digital technologies and Artificial Intelligence Scheduling Techniques. Each of them is mentioned in detail to discuss the Prosumer smart Grid. Furthermore, Edge Computing and classifications (cloudlet, Fog computing and Multi-Access) are among the suitable network methods mentioned in this paper. Some techniques and methodologies have been extensively covered to improve reader awareness of the Prosumer smart grid system.