Applications Of Deep Machine Learning In Future Energy Systems
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Applications of Deep Machine Learning in Future Energy Systems
Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and operation, before laying out the current AI approaches and our outstanding limitations. Later chapters provide in-depth accounts of specific challenges and the use of innovative third-generation machine learning, including neuromorphic computing, to resolve issues from security to power supply. An essential tool for the management, control, and modelling of future energy systems, Applications of Deep Machine Learning maps a practical path towards AI capable of supporting sustainable energy. - Clarifies the current state and future trends of energy system machine learning and the pitfalls facing our transitioning systems - Provides guidance on 3rd-generation AI tools for meeting the challenges of modeling and control in modern energy systems - Includes case studies and practical examples of potential applications to inspire and inform researchers and industry developers
Application of Machine Learning and Deep Learning Methods to Power System Problems
Author: Morteza Nazari-Heris
language: en
Publisher: Springer Nature
Release Date: 2021-10-20
This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.
Applications of AI and IOT in Renewable Energy
Applications of AI and IOT in Renewable Energy provides a future vision of unexplored areas and applications for Artificial Intelligence and Internet of Things in sustainable energy systems. The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles. In all these areas and more, applications of artificial intelligence methods, including artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above in hybrid systems are included. This book is designed to assist with developing low cost, smart and efficient solutions for renewable energy systems and is intended for researchers, academics and industrial communities engaged in the study and performance prediction of renewable energy systems. Includes future applications of AI and IOT in renewable energy Based on case studies to give each chapter real-life context Provides advances in renewable energy using AI and IOT with technical detail and data