Big Data Application in Power Systems. Second Edition, presents a thorough update of the previous volume, providing readers with step-by-step guidance in big data analytics utilization for power system diagnostics, operation, and control. Bringing back a team of global experts and drawing on fresh, emerging perspectives, this book provides cutting-edge advice for meeting today's challenges in this rapidly accelerating area of power engineering. The book is divided into two parts. The first part introduces the big picture of machine learning and big data analytics for electric utilities, explaining the benefits, challenges, and opportunities of this emerging technology. The second part delves into the theoretical and practical aspects of applied machine learning for big data analytics, presenting case studies and applications from various power system domains. Readers will develop new strategies and techniques for leveraging data toward real-world outcomes. Including five brand new chapters on emerging technological solutions, this book remains an essential resource for the reader aiming to utilize the potential of big data in the power systems of the future. Key Features, Provides a total refresh to include the most up-to-date research, developments, and challenges, Focuses on practical techniques, including rapidly modernizing monitoring systems, measurement data availability, big data handling, and machine learning approaches for processing high-dimensional, heterogeneous, and spatiotemporal data, Engages with cross-disciplinary lessons drawing on the impact of applied machine learning from various disciplines, including statistics, computer science, and bioinformatics, Includes five brand new chapters on hot topics, ranging from uncertainty decision-making to features selection methods and the opportunities provided by social network data