Artificial Intelligence For Renewable Energy And Climate Change

Author : Pandian Vasant,Gerhard-Wilhelm Weber,J. Joshua Thomas,José Antonio Marmolejo-Saucedo,Roman Rodriguez-Aguilar
Publisher : John Wiley & Sons
Page : 500 pages
File Size : 43,7 Mb
Release : 2022-08-23
Category : Computers
ISBN : 9781119768999

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Artificial Intelligence for Renewable Energy and Climate Change by Pandian Vasant,Gerhard-Wilhelm Weber,J. Joshua Thomas,José Antonio Marmolejo-Saucedo,Roman Rodriguez-Aguilar Pdf

ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY AND CLIMATE CHANGE Written and edited by a global team of experts in the field, this groundbreaking new volume presents the concepts and fundamentals of using artificial intelligence in renewable energy and climate change, while also covering the practical applications that can be utilized across multiple disciplines and industries, for the engineer, the student, and other professionals and scientists. Renewable energy and climate change are two of the most important and difficult issues facing the world today. The state of the art in these areas is changing rapidly, with new techniques and theories coming online seemingly every day. It is important for scientists, engineers, and other professionals working in these areas to stay abreast of developments, advances, and practical applications, and this volume is an outstanding reference and tool for this purpose. The paradigm in renewable energy and climate change shifts constantly. In today’s international and competitive environment, lean and green practices are important determinants to increase performance. Corresponding production philosophies and techniques help companies diminish lead times and costs of manufacturing, improve delivery on time and quality, and at the same time become more ecological by reducing material use and waste, and by recycling and reusing. Those lean and green activities enhance productivity, lower carbon footprint and improve consumer satisfaction, which in reverse makes firms competitive and sustainable. This practical, new groundbreaking volume: Features coverage on a wide range of topics such as classical and nature-inspired optimization and optimal control, hybrid and stochastic systems Is ideally designed for engineers, scientists, industrialist, academicians, researchers, computer and information technologists, sustainable developers, managers, environmentalists, government leaders, research officers, policy makers, business leaders and students Is useful as a practical tool for practitioners in the fields of sustainable and renewable energy sustainability Includes wide coverage of how artificial intelligence can be used to impact the struggle against global warming and climate change

Author : Pandian Vasant,Valeriy Kharchenko,J. Joshua Thomas,Gerhard-Wilhelm Weber,Anirban Banik
Publisher : Wiley-Scrivener
Page : 350 pages
File Size : 47,5 Mb
Release : 2022-04-05
Category : Science
ISBN : 1119768985

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Introduction to Artificial Intelligence in Renewable Energy and Climate Change by Pandian Vasant,Valeriy Kharchenko,J. Joshua Thomas,Gerhard-Wilhelm Weber,Anirban Banik Pdf

Author : Gülgün Kayakutlu,M. Özgür Kayalica
Publisher : Springer Nature
Page : 307 pages
File Size : 54,5 Mb
Release : 2023-10-16
Category : Business & Economics
ISBN : 9783031383878

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Decision Making Using AI in Energy and Sustainability by Gülgün Kayakutlu,M. Özgür Kayalica Pdf

Artificial intelligence (AI) has a huge impact on science and technology, including energy, where access to resources has been a source of geopolitical conflicts. AI can predict the demand and supply of renewable energy, optimize efficiency in energy systems, and improve the management of natural energy resources, among other things. This book explores the use of AI tools for improving the management of energy systems and providing sustainability with smart cities, smart facilities, smart buildings, smart transportation, and smart houses. Featuring research from International Federation for Information Processing's (IFIP) “AI in Energy and Sustainability” working group, this book provides new models and algorithms for AI applications in energy and sustainability fields. Any short-term, mid-term and long-term forecasting, optimization models, trend foresights and prescriptions based on scenarios are studied in the energy world and the smart systems for sustainability. The contents of this book are valuable for energy researchers, academics, scholars, practitioners and policy makers.

Author : Sailesh Iyer,Anand Nayyar,Mohd Naved,Fadi Al-Turjman
Publisher : CRC Press
Page : 305 pages
File Size : 45,9 Mb
Release : 2023-07-17
Category : Business & Economics
ISBN : 9781000903409

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Renewable Energy and AI for Sustainable Development by Sailesh Iyer,Anand Nayyar,Mohd Naved,Fadi Al-Turjman Pdf

Electronic device usage has increased considerably in the past two decades. System configurations are continuously requiring upgrades; existing systems often become obsolete in a matter of 2–3 years. Green computing is the complete effective management of design, manufacture, use, and disposal, involving as little environmental impact as possible. This book intends to explore new and innovative ways of conserving energy, effective e-waste management, and renewable energy sources to harness and nurture a sustainable eco-friendly environment. This book: • Highlights innovative principles and practices using effective e-waste management and disposal • Explores artificial intelligence based sustainable models • Discovers alternative sources and mechanisms for minimizing environmental hazards • Highlights successful case studies in alternative sources of energy • Presents solid illustrations, mathematical equations, as well as practical in-the-field applications • Serves as a one-stop reference guide to stakeholders in the domain of green computing, e-waste management, renewable energy alternatives, green transformational leadership including theory concepts, practice and case studies • Explores cutting-edge technologies like internet of energy and artificial intelligence, especially the role of machine learning and deep learning in renewable energy and creating a sustainable ecosystem • Explores futuristic trends in renewable energy This book aims to address the increasing interest in reducing the environmental impact of energy as well as its further development and will act as a useful reference for engineers, architects, and technicians interested in and working with energy systems; scientists and engineers in developing countries; industries, manufacturers, inventors, universities, researchers, and interested consultants to explain the foundation to advanced concepts and research trends in the domain of renewable energy and sustainable computing. The content coverage of the book is organized in the form of 11 clear and thorough chapters providing a comprehensive view of the global renewable energy scenario, as well as how science and technology can play a vital role in renewable energy.

Author : Aboul Ella Hassanien,Ashraf Darwish
Publisher : Springer Nature
Page : 255 pages
File Size : 41,5 Mb
Release : 2023-03-11
Category : Computers
ISBN : 9783031224560

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The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations by Aboul Ella Hassanien,Ashraf Darwish Pdf

This book discusses the advances of artificial intelligence and data sciences in climate change and provides the power of the climate data that is used as inputs to artificial intelligence systems. It is a good resource for researchers and professionals who work in the field of data sciences, artificial intelligence, and climate change applications.

Author : Ajay Kumar Vyas,S. Balamurugan,Kamal Kant Hiran,Harsh S. Dhiman
Publisher : John Wiley & Sons
Page : 276 pages
File Size : 41,9 Mb
Release : 2022-03-02
Category : Computers
ISBN : 9781119761693

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Artificial Intelligence for Renewable Energy Systems by Ajay Kumar Vyas,S. Balamurugan,Kamal Kant Hiran,Harsh S. Dhiman Pdf

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.

Author : Suman Lata Tripathi,Mithilesh Kumar Dubey,Vinay Rishiwal,Sanjeevikumar Padmanaban
Publisher : CRC Press
Page : 423 pages
File Size : 44,8 Mb
Release : 2021-11-25
Category : Technology & Engineering
ISBN : 9781000392456

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Introduction to AI Techniques for Renewable Energy System by Suman Lata Tripathi,Mithilesh Kumar Dubey,Vinay Rishiwal,Sanjeevikumar Padmanaban Pdf

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.

Author : Pandian Vasant,Joshua Thomas,Elias Munapo,Gerhard-Wilhelm Weber
Publisher : Academic Press
Page : 416 pages
File Size : 43,8 Mb
Release : 2022-05-20
Category : Science
ISBN : 9780323885744

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Advances of Artificial Intelligence in a Green Energy Environment by Pandian Vasant,Joshua Thomas,Elias Munapo,Gerhard-Wilhelm Weber Pdf

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

Author : Krishna Kumar,Ram Shringar Rao,Omprakash Kaiwartya,Shamim Kaiser,Sanjeevikumar Padmanaban
Publisher : Academic Press
Page : 418 pages
File Size : 46,9 Mb
Release : 2022-03-18
Category : Science
ISBN : 9780323914284

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Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies by Krishna Kumar,Ram Shringar Rao,Omprakash Kaiwartya,Shamim Kaiser,Sanjeevikumar Padmanaban Pdf

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

Author : Dipankar Deb,Ambesh Dixit,Laltu Chandra
Publisher : Springer Nature
Page : 314 pages
File Size : 40,5 Mb
Release : 2019-09-03
Category : Science
ISBN : 9789813295780

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Renewable Energy and Climate Change by Dipankar Deb,Ambesh Dixit,Laltu Chandra Pdf

This book gathers selected papers presented at the First International Conference on Renewable Energy and Climate Change (REC 2019), which was held at the Institute of Infrastructure Technology Research and Management (IITRAM) from 1 to 2 February 2019. The topics covered include renewable (green) energy and sources including wind power, hydropower, solar energy, biomass, biofuel, geothermal energy, wave energy, tidal energy, hydrogen & fuel cells, energy storage, new trends and technologies for renewable energies, policies and strategies for renewable energies, smart grids, batteries, and e-mobility, control techniques for renewable energies, hybrid renewable energies, renewable energy research and applications for industries, applications of renewable energies in electrical vehicles and other allied areas, artificial intelligence and machine learning studies for renewable energies, renewable energy systems in smart cities, climate change mitigation, carbon trading, carbon capture and utilization, and carbon dioxide refrigeration systems.

Author : Mustapha Hatti
Publisher : Springer
Page : 569 pages
File Size : 49,7 Mb
Release : 2018-11-23
Category : Technology & Engineering
ISBN : 9783030047894

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Renewable Energy for Smart and Sustainable Cities by Mustapha Hatti Pdf

This book features cutting-edge research presented at the second international conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES2018, held on 24–26 November 2018, at the High School of Commerce, ESC-Koléa in Tipaza, Algeria. Today, the fundamental challenge of integrating renewable energies into the design of smart cities is more relevant than ever. While based on the advent of big data and the use of information and communication technologies, smart cities must now respond to cross-cutting issues involving urban development, energy and environmental constraints; further, these cities must also explore how they can integrate more sustainable energies. Sustainable energies are a major determinant of smart cities’ longevity. From an environmental and technological standpoint, these energies offer an optimal power supply to the electric network while creating significantly less pollution. This requires flexibility, i.e., the availability of supply and demand. The end goal of any smart city is to improve the quality of life for all citizens (both in the city and in the countryside) in a way that is sustainable and respectful of the environment. This book encourages the reader to engage in the preservation of our environment, every moment, every day, so as to help build a clean and healthy future, and to think of the future generations who will one day inherit our planet. Further, it equips those whose work involves energy systems and those engaged in modelling artificial intelligence to combine their expertise for the benefit of the scientific community and humanity as a whole.

Author : Soteris Kalogirou
Publisher : Nova Publishers
Page : 488 pages
File Size : 52,7 Mb
Release : 2007
Category : Computers
ISBN : 1600212611

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Artificial Intelligence in Energy and Renewable Energy Systems by Soteris Kalogirou Pdf

This book presents state of the art applications of artificial intelligence in energy and renewable energy systems design and modelling. It covers such topics as solar energy, wind energy, biomass and hydrogen as well as building services systems, power generation systems, combustion processes and refrigeration. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities dealing with modelling and performance prediction of energy and renewable energy systems.

Author : Neeraj Priyadarshi,Sanjeevikumar Padmanaban,Kamal Kant Hiran,Jens Bo Holm-Nielson,Ramesh C. Bansal
Publisher : Walter de Gruyter GmbH & Co KG
Page : 318 pages
File Size : 45,8 Mb
Release : 2021-11-22
Category : Computers
ISBN : 9783110714043

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Artificial Intelligence and Internet of Things for Renewable Energy Systems by Neeraj Priyadarshi,Sanjeevikumar Padmanaban,Kamal Kant Hiran,Jens Bo Holm-Nielson,Ramesh C. Bansal Pdf

This book explains the application of Artificial Intelligence and Internet of Things on green energy systems. The design of smart grids and intelligent networks enhances energy efficiency, while the collection of environmental data through sensors and their prediction through machine learning models improve the reliability of green energy systems.

Author : Ashutosh Kumar Dubey,Sushil Narang,Arun Lal Srivastav,Abhishek Kumar,Vicente García-Díaz
Publisher : Woodhead Publishing
Page : 408 pages
File Size : 44,5 Mb
Release : 2022-08-01
Category : Science
ISBN : 9780323906616

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Artificial Intelligence for Renewable Energy systems by Ashutosh Kumar Dubey,Sushil Narang,Arun Lal Srivastav,Abhishek Kumar,Vicente García-Díaz Pdf

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

Author : Kingsley Onyeagusi
Publisher : GRIN Verlag
Page : 19 pages
File Size : 50,7 Mb
Release : 2024-01-08
Category : Science
ISBN : 9783346990433

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The Global Impact of Renewable Energy and Data Analytics by Kingsley Onyeagusi Pdf

Academic Paper from the year 2023 in the subject Politics - Environmental Policy, , language: English, abstract: This article explores the critical role of renewable energy and intelligence systems in developing countries seeking to expand energy access and for developed nations working to decarbonise energy systems. The opportunities, challenges, and impacts of the renewable's revolution vary between poor nations with limited existing infrastructure and rich countries possessing advanced technical capabilities. However, data-driven solutions are invaluable in maximising clean energy potential everywhere while managing variability. By comparing and contrasting the nuances of integrating high shares of solar, wind, and other renewables onto grids in Asia, Africa, the Americas, and Europe, insights and best practices can be shared across borders. Artificial intelligence and machine learning are unlocking the promise of renewable energy worldwide through sophisticated forecasting of supply and demand, optimal location of projects, predictive maintenance of assets, and real-time management of complex systems. However, technology gaps and a lack of technical expertise hamper many developing nations. Targeted financing, capacity building, and knowledge transfer are critical to empowering these regions to benefit from data and renewables in providing affordable, reliable, and sustainable energy access. This article highlights significant trends, analyses case studies of success, and synthesises expert perspectives across the developed and developing world. By documenting the global impacts of renewables and analytics, stakeholders ranging from policymakers to investors can make informed decisions that steer all nations towards a decarbonised energy future that leaves no one behind. The insights can help guide an inclusive and just transition worldwide.