Artificial Intelligence for Enhancing Greed Stability: A Review

Abstract

Integrating renewable energy sources (RES) such as wind and solar power into conventional power grids presents significant challenges due to their intermittent and unpredictable nature. Traditional network management techniques are increasingly inadequate to deal with these complexities. This overview paper explores the key role of artificial intelligence (AI) in enhancing grid stability by providing advanced solutions for distributed energy resource management, load forecasting, smart grid automation and predictive maintenance. AI-driven models enable accurate demand forecasting, fault detection and efficient management of energy flows, thereby preventing outages and improving overall grid resilience. Key applications discussed include artificial intelligence in load balancing, demand response, renewable energy integration and smart microgrid development. In addition, the document highlights future trends such as the use of digital twins and the integration of electric vehicles into the grid. Through real-world case studies and comprehensive analysis, this paper shows how AI technologies are revolutionizing energy management and ensuring stable and reliable energy system in the face of increasing use of renewable energy sources.