Machine Learning Model used Efficiently to Manage the Smart Grid and Renewable Energy

A new technology, a Smart Grid Management System (SGMS), explains how it uses machine learning algorithms to distribute power more effectively. This article overviews intelligent grid management systems, including their design, advantages, and problems. Machine learning methods, including decision trees, neural networks, and Support Vector Machines (SVM), are also discussed in this study as they are employed in intelligent grid management systems. Increased efficiency, less waste, enhanced dependability, and decreased expenses are a few benefits of using deep learning techniques in intelligent energy systems for management. Protection of data, Security, and capacity are only some issues that arise when applying machine learning techniques to innovativegrid management systems. The report finishes with a discussion of potentialnext steps for machine research learning-based intelligent control systems for grids.