Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern. Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy. Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry.

The application of contemporary and emerging operational research optimization methods in renewable energy is vital to creating and maintaining sustainable environments across the planet. More research is needed to understand how modern and innovative technological solutions can enhance accessible global energy. Operational Research for Renewable Energy and Sustainable Environments is a critical scholarly resource that examines the efficient use of modern electrical technology and renewable energy sources that have a positive impact on sustainable development. Highlighting topics such as cogeneration thermal modules, photovoltaic (PV) solar, and renewable energy systems (RES) application practices, this publication is geared towards academics, advocates, government officials, policymakers, humanized managers, practitioners, professionals, and students interested in the latest research on renewable energy and clean technology for sustainable rural development.

This book presents the state-of-the-art methods in Linear Integer Programming, including some new algorithms and heuristic methods developed by the authors in recent years. Topics as Characteristic equation (CE), application of CE to bi-objective and multi-objective problems, Binary integer problems, Mixed-integer models, Knapsack models, Complexity reduction, Feasible-space reduction, Random search, Connected graph are also treated.