Application of Artificial Intelligence in Power Systems

The application of Artificial Intelligence (AI) in power systems would bring a groundbreaking way to optimize grid operations, improve system reliability, and more efficiently integrate renewable energy sources. This paper outlines the areas in which AI is being applied in contemporary power systems, more specifically, load predictions, fault detection, optimal power flow, voltage stability, and integration of renewable energy. AI is leveraged through machine learning, deep learning, and reinforcement learning take advantage of the principles of uncertainty, efficiency, and resilience to improve decision making, operational efficiency, and system resilience, respectively. Although the benefit of AI in power systems is significant, several challenges prevent AI from larger-scale use including data quality, computational complexity, cybersecurity, and interpretability. The paper also details future research themes including Explainable AI (XAI) development, IoT and Edge computing integration, and digital twins working with on-line characterizations for real-time simulation and control. The study and supporting paper conclude AI has potential to fundamentally change the way power systems operate, but the existing and perpetuating challenges must first be addressed correctly and comprehensively in order for it to enabled at a large-scale.