• Patel Jay Hasmukhbhai.
• Binal Modi
• Krunal Dattesh

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 systems in the face of increasing use of renewable energy sources.

Artificial Intelligence (AI), Grid Stability, Smart Grids, Fault Detection

"LEVERAGING ARTIFICIAL INTELLIGENCE FOR ENHANCING GRID STABILITY: A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.c408-c415, October-2024, Available :http://www.jetir.org/papers/JETIR2410341.pdf

"LEVERAGING ARTIFICIAL INTELLIGENCE FOR ENHANCING GRID STABILITY: A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. ppc408-c415, October-2024, Available at : http://www.jetir.org/papers/JETIR2410341.pdf