Nagpal N., Alhelou H.H., Siano P., Padmanaban S. (eds.) Applications of Big Data and Artificial Intelligence in Smart Energy Systems: Volume 2

River Publishers, 2023. — 250 p. — (River Publishers Series in Computing and Information Science and Technology). — ISBN 9788770228275.In the era of propelling traditional energy systems to evolve towards smart energy systems, including power generation, energy storage systems, and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles, and domestic & industrial loads. Similarly, with the integration of solid state devices, renewable sources, and distributed generation, power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting, including load distribution automation, energy regulation and control, and energy trading.This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. The book delves into the new technologies such as the Internet of Things, blockchain, etc. for smart home solutions, and smart city solutions in depth in the context of the modern power systems.Innovation, Opportunities, and Ongoing Challenges of AI and IOE in the Power and Energy Sector
Applications of Artificial Intelligence in Intelligent Combustion and Energy Storage Technologies
Sustainable Smart Energy Systems and Energy Preservation Strategies in Intelligent Transportation Sectors
Application of ANN Techniques to Mitigation of Power Quality Problems
Application of the LMS Algorithm for Mitigation of Voltage Sag as a Power Quality Problem
Blockchain-based Solutions for Electricity Supply Chain in Smart Grids
Virtual Power Plant
AI Business Models in Emerging Energy Markets: Smart Grid
Artificial Neural Networks and Forecasting Major Energy Markets