Integration of Artificial Intelligence and Machine Learning for Smart Grid Optimization

Abstract

This study examines how machine learning (ML) and artificial intelligence (AI) approaches can be joined to further develop smart grid enhancement. This study explains the smart grid the executive’s framework, a state of the art development that disseminates energy proficiently by utilizing machine learning calculations. An outline of smart grid the board frameworks' design, benefits, and hardships is given in this review. The concentrate likewise covers various machine learning techniques, including Support Vector Machines (SVM), Brain Organizations, and Choice Trees, that are used in smart grid the executive’s frameworks. Utilizing machine learning calculations in smart grid the executive’s frameworks has a few advantages, including lower costs, better constancy, diminished energy squander, and upgraded energy productivity. Executing machine learning calculations in smart grid the board frameworks presents versatility, protection, and information security issues. Future directions for machine learning-based smart grid management system research are covered in the paper's conclusion. The results open the door for the creation of intelligent systems that have the potential to completely transform power grid management and operation, leading to the construction of a more robust and sustainable energy infrastructure.