Advances of Artificial Intelligence in a Green Energy Environment


Book Description

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. - Looks at new techniques in artificial intelligence (AI) reducing the dimension of data coverage worldwide - Chapters include AI methodologies using enhanced hybrid swarm-based optimization algorithms - Includes flowchart diagrams for exampling optimizing techniques




Applications of AI and IOT in Renewable Energy


Book Description

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 The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles.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




Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies


Book Description

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation. - Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment - Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum - Addresses the advanced field of renewable generation, from research, impact and idea development of new applications




Green Energy, Environment and Sustainable Development


Book Description

The subjects of green energy and sustainability have never been more important, as governments around the world wrestle with the problem of how to protect the planet from the damage being caused to the environment by climate change. This book presents the proceedings of GEESD2023, the 4th International Conference on Green Energy, Environment and Sustainable Development, held in Mianyang, China from 15-17 June 2023 and online via Zoom. The conference aims to gather innovative academicians and industry experts in the fields of green energy, environment, and sustainable development in a common forum, providing a platform for the exchange of the latest research developments in related fields. This year, the call for papers attracted more than 280 submissions, 138 of which were accepted for inclusion in this collection. The process of evaluation and peer-review took place over six months and involved more than 100 TPC members and reviewers. The book is divided into 7 sections: green energy and systems; computer methods in the environment; chemistry and the environment; ecology and the rural environment; energy, environment and economy; environment and pollution; and water and mineral resources. Papers deal with the most up-to-date findings and technologies. The book provides a valuable overview of the latest research and developments and will be of interest to all those working in the fields of green energy and sustainable development.




Artificial Intelligence Methods in the Environmental Sciences


Book Description

How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.




Intelligent Renewable Energy Systems


Book Description

INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.




Artificial Intelligence for Renewable Energy Systems


Book Description

ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.




Human Agro-Energy Optimization for Business and Industry


Book Description

In the current era, there are many environmental and energy challenges facing the agricultural sector, which negatively impact the climate, business, industry, and society. Through modern technologies and engineering, however, these challenges are now able to be met with solutions. There is a need for research in this area so that the industry can continue to be sustainable. Human Agro-Energy Optimization for Business and Industry presents research on humanized optimization approaches for smart energy and the agro-business industry. It is a critical scholarly resource that examines the efficient use of modern smart farming and renewable energy sources, which have a positive impact on sustainable development. Covering topics such as biomass characterization, energy efficiency, and sustainable development, this premier reference source is an essential resource for agricultural scientists, engineers, government officials, software developers, managers, business leaders, executive officers, students and educators of higher education, librarians, researchers, and academicians.




The Economics of Artificial Intelligence


Book Description

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.




Proceedings of the 2nd International Conference on Green Energy, Environment and Sustainable Development (GEESD2021)


Book Description

The need for green technologies and solutions which will deliver the energy requirements of both the developed and developing world to support sustainability and protect the environment worldwide has never been more urgent.This book contains the proceedings of the 2nd International Conference on Green Energy, Environment and Sustainable Development (GEESD2021) which, due to the COVID-19 pandemic around the world and with the strict travel restrictions in China, was held as a hybrid conference (both physically and online via Zoom) in Shanghai, China on 26 and 27 June 2021. It provided an opportunity to bring together an international community of leading scientists, researchers, engineers and academics, as well as industrial professionals, to exchange and share their experiences and research results in the energy, environment and sustainable development sector. In total, 80 participants were able to exchange knowledge and discuss the latest developments in the field. GEESD2021 attracted more than 250 submissions, 88 of which were accepted after an extensive period of peer review by more than 100 reviewers and members of the program committee. These are included here, grouped into 3 sections, with 28 papers on sustainable energy; 34 on ecology; and 26 papers covering environmental pollution and protection.Offering an overview of the most up-to-date findings and technologies in the field of sustainable energy and environmental protection, the book will be of interest to all those working in this field.