Artificial Intelligence in Power System Operations: Applications, Challenges, and Future Directions

Abstract

This review provides a comprehensive exploration of the transformative role of Artificial Intelligence (AI) in power system operations. The paper delves into the historical evolution of AI applications in energy management, highlighting its impact on load forecasting, demand-side management, fault detection, grid stability, and renewable energy integration. It addresses the key challenges faced during implementation, including data quality, computational complexity, legacy system integration, cybersecurity, and ethical considerations.

Future directions are discussed, emphasizing predictive maintenance, decentralized grids, hybrid AI models, and real-time decision-making. The review also presents case studies demonstrating successful AI applications in power systems, such as those by Siemens and General Electric, showcasing performance improvements and cost savings. Finally, practical recommendations are provided for seamless AI integration, underscoring the importance of industry-academia partnerships and training programs for engineers to leverage AI effectively.

AI's potential in revolutionizing the energy sector is undeniable, paving the way for more efficient, reliable, and sustainable power systems to meet future energy demands.