Data Analytics Challenges and Needs in Smart Grid for Smart Energy Management

The power industry's future is strongly reliant on the utilization of new electric networks combined with information and communication technologies (ICT), These grids are usually referred to as smart grids. The benefit of employing smart grids is that, they give a higher quality of service by improving resource and asset management, identifying system problems, lowering the gap of demand and supply, and Minimizing peak load. In the past, the electrical sector has made extensive use of data analytics to provide a range of services, including demand forecasts, revenue protection, and data visualization. There are still many circumstances, nonetheless, in which data analytical procedures may be useful. Demand response management in the smart grid setting is one such area where data analytics can be useful in managing the total load on the grid. This article aims to use different machine learning technologies to evaluate the requirements for data analytics in smart grids, demand response management in smart grids, and potential future demand areas for smart energy management using different machine learning technologies.