ARTIFICIAL INTELLIGENCE IN SMART GRIDS: APPLICATIONS, CHALLENGES, AND FUTURE DIRECTIONS

Abstract

With the development of modern energy systems, there is a need to operate increasingly intelligent electricity systems. Smart grids are advanced electricity networks that allow for integrating new technologies, increasing the reliability and performance of the power system, addressing the issues of renewable energy sources, growing electricity consumption, and real-time monitoring of the operating processes. Artificial Intelligence (AI) can be applied in different areas of smart grid to make the electricity system more reliable and competitive. The methods include Machine Learning, Deep Learning, Artificial Neural Networks, Reinforcement Learning, Fuzzy Logic, and Expert Systems. They are used to perform demand side management, predict electricity consumption, forecast renewable energy production, detect and diagnose grid failures, optimize maintenance, enhance protection and security, and manage energy consumption. However, there are challenges for implementing AI in the smart grid, such as data privacy, security, complexity, lack of transparency, and legislation. The current research explores the different aspects of applying AI technologies to smart grids. The paper provides some of the most common applications of AI and discusses the challenges and future outlook for AI-driven smart grids. The study emphasizes the significance of artificial intelligence for developing the next-generation smart grid.