Artificial Intelligence and Machine Learning for Sustainable Power Systems

This book provides an in-depth exploration of how smart technologies such as artificial intelligence and machine learning are revolutionizing power systems, addressing critical challenges such as operational efficiency, renewable energy integration, and decarbonization. It emphasizes the role of explainable artificial intelligence in fostering trust and transparency and shows real-world examples of renewable energy forecasting.Features:Highlights the transformative role of artificial intelligence and machine learning in modern power systems, focusing on critical advancements like predictive maintenance for minimizing downtime, and energy distribution optimization to reduce losses.Addresses the integration of renewable energy through advanced artificial intelligence models for solar and wind forecasting, ensuring grid stability while meeting decarbonization goals.Showcases how explainable artificial intelligence techniques, such as decision trees, feature importance analysis, and interpretable neural networks, make artificial intelligence decisions understandable and reliable for safety-critical applications.Discusses the role of artificial intelligence in facilitating the seamless integration of renewable energy sources into traditional power networks, addressing key challenges in the transition to sustainable energy.Focuses on machine learning techniques to optimize energy storage systems, improve battery management, and maximize renewable energy utilization.It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, energy engineering, renewable energy, computer science, and engineering.