IoT, Machine Learning and Blockchain Technologies for Renewable Energy and Modern Hybrid Power Systems PDF Download
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Author: C. Sharmeela
Publisher: CRC Press
ISBN: 1000824403
Category : Computers
Languages : en
Pages : 305
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Book Description
This edited book comprises chapters that describe the IoT, machine learning, and blockchain technologies for renewable energy and modern hybrid power systems with simulation examples and case studies. After reading this book, users will understand recent technologies such as IoT, machine learning techniques, and blockchain technologies and the application of these technologies to renewable energy resources and modern hybrid power systems through simulation examples and case studies.
Author: C. Sharmeela
Publisher: CRC Press
ISBN: 1000824403
Category : Computers
Languages : en
Pages : 305
Get Book Here
Book Description
This edited book comprises chapters that describe the IoT, machine learning, and blockchain technologies for renewable energy and modern hybrid power systems with simulation examples and case studies. After reading this book, users will understand recent technologies such as IoT, machine learning techniques, and blockchain technologies and the application of these technologies to renewable energy resources and modern hybrid power systems through simulation examples and case studies.
Author: C. Sharmeela
Publisher:
ISBN: 9788770227117
Category : Artificial intelligence
Languages : en
Pages : 0
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Book Description
This edited book comprises chapters that describe the IoT, machine learning, and blockchain technologies for renewable energy and modern hybrid power systems with simulation examples and case studies. After reading this book, users will understand recent technologies such as IoT, machine learning techniques, and blockchain technologies and the application of these technologies to renewable energy resources and modern hybrid power systems through simulation examples and case studies.
Author: Acharjya, Pinaki Pratim
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 351
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Book Description
As the world grapples with the urgent need for sustainable energy solutions, the limitations of traditional approaches to renewable energy forecasting become increasingly evident. The demand for more accurate predictions in net load forecasting, line loss predictions, and the seamless integration of hybrid solar and battery storage systems is more critical than ever. In response to this challenge, advanced Artificial Intelligence (AI) techniques are emerging as a solution, promising to revolutionize the renewable energy landscape. Machine Learning and Computer Vision for Renewable Energy presents a deep exploration of AI modeling, analysis, performance prediction, and control approaches dedicated to overcoming the pressing issues in renewable energy systems. Transitioning from the complexities of energy prediction to the promise of advanced technology, the book sets its sights on the game-changing potential of computer vision (CV) in the realm of renewable energy. Amidst the struggle to enhance sustainability across industries, CV technology emerges as a powerful ally, collecting invaluable data from digital photos and videos. This data proves instrumental in achieving better energy management, predicting factors affecting renewable energy, and optimizing overall sustainability. Readers, including researchers, academicians, and students, will find themselves immersed in a comprehensive understanding of the AI approaches and CV methodologies that hold the key to resolving the challenges faced by renewable energy systems.
Author: Riswandi, Budi Agus
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 485
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Book Description
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.
Author: Derbali, Abdelkader Mohamed Sghaier
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 389
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Book Description
The crucial challenge of integrating sustainability into business and investment decisions is compounded by the complexity of analyzing vast and intricate datasets to make informed choices. Traditional approaches often fail to provide timely and accurate insights into environmental, social, and governance (ESG) factors, hindering progress toward a greener future. Additionally, the rapid evolution of AI and machine learning in finance has left many professionals needing help to grasp their full potential in advancing sustainability goals. With a comprehensive understanding and practical guidance, organizations can stay caught up in adopting sustainable practices and leveraging AI for financial and environmental benefits. Social and Ethical Implications of AI in Finance for Sustainability offers a timely and comprehensive solution to these challenges by thoroughly examining how AI can safely enhance sustainability in finance. The book bridges the gap between theory and practice, offering practical insights and real-world applications to empower academics, practitioners, policymakers, and students. Through a series of expertly curated chapters, readers will gain a deep understanding of the role AI plays in reshaping finance for a sustainable future. The book's instructional elements, including case studies and expert analysis, provide a roadmap for incorporating AI into sustainability strategies, enabling organizations to make informed decisions and drive positive change.
Author: Edghiem, Farag
Publisher: IGI Global
ISBN: 1668474182
Category : Business & Economics
Languages : en
Pages : 331
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Book Description
Digital technologies have enabled certain opportunities for industries, societies, and companies to change for the better. The service sector has essentially evolved through significant developments in recent decades, such as the increasing adoption of artificial intelligence (AI) applications and automated technologies, including service robots, chatbots, and virtual assistants. Both digital transformation and digital entrepreneurship are multifaceted areas that relate to varied emerging technologies that have recently dominated the current service industry. These technologies serve to enhance various sociotechnical areas, including communication and collaboration, as well as co-creating business value and promoting service automation. Digital Entrepreneurship and Co-Creating Value Through Digital Encounters contributes to the services’ digital transformation and digital entrepreneurship domain by uncovering contemporary innovations used in the modern service industry. It supports modern applications of Industry 4.0, digital transformation, and entrepreneurship to facilitate value co-creation for contemporary businesses. Covering topics such as big data management, industrial relations, and tourist destination selection, this premier reference source is an ideal resource for entrepreneurs, business owners and managers, government officials, policymakers, students and educators of higher education, librarians, researchers, and academicians.
Author: Abhishek, Kumar
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 442
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Book Description
The convergence of Internet of Things (IoT) technology and blockchain offers transformative potential for the development of smart cities, enhancing industry operations and healthcare systems. IoT devices generate vast amounts of data to optimize urban infrastructure and improve service delivery, while blockchain provides a secure, transparent framework for managing data. Across industries, this collaboration leads to smarter manufacturing processes and efficient logistics. In healthcare, it enhances patient care through secure data sharing and streamlined administrative processes. A concerted effort to address these technical, regulatory, and ethical challenges is crucial for effective and responsible integration of IoT and blockchain in smart cities for improved urban living and healthcare services. Applying Internet of Things and Blockchain in Smart Cities: Industry and Healthcare Perspectives explores the application of IoT and blockchain technology for smart city integration in healthcare industries and business processes. It offers solutions for this effective convergence, through aspects like cloud and digital technology, or security and privacy practices. This book covers topics such as machine learning, energy management, and wearable devices, and is a useful resource for business owners, computer engineers, agriculturalists, security professionals, healthcare workers, academicians, researchers, and scientists.
Author: Mohammadreza Daneshvar
Publisher: Elsevier
ISBN: 0323957803
Category : Technology & Engineering
Languages : en
Pages : 191
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Book Description
IoT-Enabled Multi-Energy Systems: From Isolated Energy Grids to Modern Interconnected Networks proposes practical solutions for the management and control of energy interactions throughout the interconnected energy infrastructures of the future multi-energy grid. The book discusses a panorama of modeling, planning and optimization considerations for IoT technologies, their applications across grid modernization, and the coordinated operation of multi-vector energy grids. The work is suitable for energy, power, mechanical, chemical, process and environmental engineers, and highly relevant for researchers and postgraduate students who work on energy systems. Sections address core theoretical underpinnings, significant challenges and opportunities, how to support IoT-based developed expert systems, and how AI can empower IoT technologies to sustainably develop fully renewable modern multi-carrier energy networks. Contributors address artificial intelligence technology and its applications in developing IoT-based technologies, cloud-based intelligent energy management schemes, data science and multi-energy big data analysis, machine learning and deep learning techniques in multi-energy systems, and much more. - Reviews core applications of IoT technologies in grid modernization of multi-energy networks - Develops practical solutions for optimal integration of renewable energy resources in modern multi-vector energy networks - Analyzes the reliable integration, sustainable operation and accurate planning of multi-carrier energy grids in highly penetrated stochastic energy resources
Author: Hazra, Sunanda
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 520
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Book Description
Optimization Techniques for Hybrid Power Systems: Renewable Energy, Electric Vehicles, and Smart Grid is a comprehensive guide that delves into the intricate world of renewable energy integration and its impact on electrical systems. With the current global energy crisis and the urgent need to address climate change, this book explores the latest advancements and research surrounding optimization techniques in the realm of renewable energy. This book has a focus on nature-inspired and meta-heuristic optimization methods, and it demonstrates how these techniques have revolutionized renewable energy problem-solving and their application in real-world scenarios. It examines the challenges and opportunities in achieving a larger utilization of renewable energy sources to reduce carbon emissions and air pollutants while meeting renewable portfolio standards and enhancing energy efficiency. This book serves as a valuable resource for researchers, academicians, industry delegates, scientists, and final-year master's degree students. It covers a wide range of topics, including novel power generation technology, advanced energy conversion systems, low-carbon technology in power generation and smart grids, AI-based control strategies, data analytics, electrified transportation infrastructure, and grid-interactive building infrastructure.
Author: Denis Sidorov
Publisher: MDPI
ISBN: 3039433822
Category : Technology & Engineering
Languages : en
Pages : 272
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Book Description
This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.
