Enabling Methodologies for Renewable and Sustainable Energy

This book aims to provide practical aspects of, and an introduction to, the applications of various technological advancement tools, such as AI, machine learning to design, big data, cloud computing, and IoT, to model, characterize, optimize, forecast, and do performance prediction of renewable energy exploitation. It further discusses new avenues for energy sources such as hydrogen energy generation and energy storage technologies including existing policies and case studies for a better understanding of renewable energy generation.
Features:
Covers technologies considered to explore, predict, and perform operation and maintenance of renewable energy sources.
Aids in the design and use of renewable energy sources, including the application of artificial intelligence in a real-time environment.
Includes IoT, cloud computing, big data, smart grid, and different optimization techniques for resource forecasting, installation, operation, and optimization of energy.
Discusses the principle of integration/hybridization of renewable energy sources along with their optimization based on energy requirements.
Reviews the concepts and challenges involved in the implementation of smart grids.
This book is aimed at researchers and graduate students in renewable energy engineering, computer and mechanical engineering, novel technologies, and intelligent systems.


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