Applications of AI and IOT in Renewable Energy
Applications of AI and IOT in Renewable Energy

Author: Rabindra Nath Shaw

Publisher: Academic Press

Published: 2022-02-09

Total Pages: 248

ISBN-13: 0323984010

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 The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles.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

AI Applications for Clean Energy and Sustainability
AI Applications for Clean Energy and Sustainability

Author: Riswandi, Budi Agus

Publisher: IGI Global

Published: 2024-08-16

Total Pages: 485

ISBN-13:

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The global demand for clean energy solutions the urgency of addressing climate change continue to intensify, and as such, the need for innovative approaches becomes increasingly paramount. However, navigating the complex landscape of clean energy production and sustainability presents significant challenges. Traditional methods often fall short in efficiently optimizing renewable energy systems and mitigating environmental impacts. Moreover, the integration of artificial intelligence (AI) into the energy sector remains underexplored, despite its potential to revolutionize operations and drive sustainable development. AI Applications for Clean Energy and Sustainability emerges, working to tackle these pressing issues. This comprehensive volume delves into the transformative power of AI in revolutionizing clean energy production, distribution, and management. By harnessing machine learning algorithms, data analytics, and optimization techniques, the book offers innovative solutions to enhance the efficiency, reliability, and scalability of renewable energy systems. Through real-world case studies and practical examples, it illustrates AI's potential to optimize energy infrastructure, monitor marine ecosystems, and predict climate change impacts, thereby paving the way for a more sustainable future.

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies

Author: Krishna Kumar

Publisher: Academic Press

Published: 2022-03-18

Total Pages: 418

ISBN-13: 0323914284

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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

AI in Manufacturing and Green Technology
AI in Manufacturing and Green Technology

Author: Sambit Kumar Mishra

Publisher: CRC Press

Published: 2020-10-20

Total Pages: 168

ISBN-13: 1000171892

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This book focuses on environmental sustainability by employing elements of engineering and green computing through modern educational concepts and solutions. It visualizes the potential of artificial intelligence, enhanced by business activities and strategies for rapid implementation, in manufacturing and green technology. This book covers utilization of renewable resources and implementation of the latest energy-generation technologies. It discusses how to save natural resources from depletion and illustrates facilitation of green technology in industry through usage of advanced materials. The book also covers environmental sustainability and current trends in manufacturing. The book provides the basic concepts of green technology, along with the technology aspects, for researchers, faculty, and students.

Introduction to AI Techniques for Renewable Energy System
Introduction to AI Techniques for Renewable Energy System

Author: Suman Lata Tripathi

Publisher: CRC Press

Published: 2021-11-25

Total Pages: 423

ISBN-13: 1000392457

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Introduction to AI techniques for Renewable Energy System Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems. Features Focuses on a significant area of concern to develop a foundation for the implementation of renewable energy system with intelligent techniques Showcases how researchers working on renewable energy systems can correlate their work with intelligent and machine learning approaches Highlights international standards for intelligent renewable energy systems design, reliability, and maintenance Provides insights on solar cell, biofuels, wind, and other renewable energy systems design and characterization, including the equipment for smart energy systems This book, which includes real-life examples, is aimed at undergraduate and graduate students and academicians studying AI techniques used in renewal energy systems.

Clean Energy for Sustainable Development
Clean Energy for Sustainable Development

Author: Kalam Abul Azad

Publisher: Academic Press

Published: 2016-11-12

Total Pages: 632

ISBN-13: 0128054247

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Clean Energy for Sustainable Development: Comparisons and Contrasts of New Approaches presents information on the fundamental challenge that the energy sector faces with regard to meeting the ever growing demand for sustainable, efficient, and cleaner energy. The book compares recent developments in the field of energy technology, clean and low emission energy, and energy efficiency and environmental sustainability for industry and academia. Rasul, Azad and Sharma, along with their team of expert contributors, provide high-end research findings on relevant industry themes, including clean and sustainable energy sources and technologies, renewable energy technologies and their applications, biomass and biofuels for sustainable environment, energy system and efficiency improvement, solar thermal applications, and the environmental impacts of sustainable energy systems. This book uses global institutes and case studies to explore and analyze technological advancements alongside practical applications. This approach helps readers to develop and affirm a better understanding of the relevant concepts and solutions necessary to achieve clean energy and sustainable development in both medium and large-scale industries. - Compares in-depth research on a wide range of clean technologies, from global institutes in Australia, Europe, and India - Evaluates the recent developments in clean technologies against the efficiency of tried and tested applications - Considers case studies on the advancements of sustainable energy into industry from around the world

Artificial Intelligence for Renewable Energy systems
Artificial Intelligence for Renewable Energy systems

Author: Ashutosh Kumar Dubey

Publisher: Woodhead Publishing

Published: 2022-08-01

Total Pages: 408

ISBN-13: 0323906613

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Artificial Intelligence for Renewable Energy Systems addresses the energy industries remarkable move from traditional power generation to a cost-effective renewable energy system, and most importantly, the paradigm shift from a market-based cost of the commodity to market-based technological advancements. Featuring recent developments and state-of-the-art applications of artificial intelligence in renewable energy systems design, the book emphasizes how AI supports effective prediction for energy generation, electric grid related line loss prediction, load forecasting, and for predicting equipment failure prevention. Looking at approaches in system modeling and performance prediction of renewable energy systems, this volume covers power generation systems, building service systems and combustion processes, exploring advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms and hybrid mechanisms. - Includes real-time applications that illustrates artificial intelligence and machine learning for various renewable systems - Features a templated approach that can be used to explore results, with scientific implications followed by detailed case studies - Covers computational capabilities and varieties for renewable system design

Data Science Applied to Sustainability Analysis
Data Science Applied to Sustainability Analysis

Author: Jennifer Dunn

Publisher: Elsevier

Published: 2021-05-11

Total Pages: 312

ISBN-13: 0128179775

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Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. - Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery - Includes considerations sustainability analysts must evaluate when applying big data - Features case studies illustrating the application of data science in sustainability analyses

Green Illusions
Green Illusions

Author: Ozzie Zehner

Publisher: U of Nebraska Press

Published: 2012

Total Pages: 462

ISBN-13: 0803243367

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We don’t have an energy crisis. We have a consumption crisis. And this book, which takes aim at cherished assumptions regarding energy, offers refreshingly straight talk about what’s wrong with the way we think and talk about the problem. Though we generally believe we can solve environmental problems with more energy—more solar cells, wind turbines, and biofuels—alternative technologies come with their own side effects and limitations. How, for instance, do solar cells cause harm? Why can’t engineers solve wind power’s biggest obstacle? Why won’t contraception solve the problem of overpopulation lying at the heart of our concerns about energy, and what will? This practical, environmentally informed, and lucid book persuasively argues for a change of perspective. If consumption is the problem, as Ozzie Zehner suggests, then we need to shift our focus from suspect alternative energies to improving social and political fundamentals: walkable communities, improved consumption, enlightened governance, and, most notably, women’s rights. The dozens of first steps he offers are surprisingly straightforward. For instance, he introduces a simple sticker that promises a greater impact than all of the nation’s solar cells. He uncovers why carbon taxes won’t solve our energy challenges (and presents two taxes that could). Finally, he explores how future environmentalists will focus on similarly fresh alternatives that are affordable, clean, and can actually improve our well-being. Watch a book trailer.

Artificial Intelligence Methods in the Environmental Sciences
Artificial Intelligence Methods in the Environmental Sciences

Author: Sue Ellen Haupt

Publisher: Springer Science & Business Media

Published: 2008-11-28

Total Pages: 418

ISBN-13: 1402091192

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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.