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Author: Ashutosh Kumar Dubey
Publisher: Elsevier
ISBN: 0443289484
Category : Technology & Engineering
Languages : en
Pages : 389
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Book Description
Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source
Author: Ashutosh Kumar Dubey
Publisher: Elsevier
ISBN: 0443289484
Category : Technology & Engineering
Languages : en
Pages : 389
Get Book Here
Book Description
Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source
Author: Ashutosh Kumar Dubey
Publisher: Elsevier
ISBN: 0443289476
Category : Technology & Engineering
Languages : en
Pages : 388
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Book Description
Computer Vision and Machine Intelligence in Renewable Energy Systems, the first release in Elsevier's cutting-edge new series, Advances in Intelligent Energy Systems, offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration. The book equips readers with a variety of essential tools and applications, outlining the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence and breaking down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Other sections offer case studies and applications to a wide range of renewable energy source and the future possibilities of the technology. This book provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids.
Author: Soteris Kalogirou
Publisher: Nova Publishers
ISBN: 9781600212611
Category : Computers
Languages : en
Pages : 488
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Book Description
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: Ashutosh Kumar Dubey
Publisher: Woodhead Publishing
ISBN: 0323906613
Category : Science
Languages : en
Pages : 408
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Book Description
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: Neeraj Priyadarshi
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110714043
Category : Computers
Languages : en
Pages : 320
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Book Description
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: Rabindra Nath Shaw
Publisher: Academic Press
ISBN: 0323984010
Category : Technology & Engineering
Languages : en
Pages : 248
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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
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: Mukhdeep Singh Manshahia
Publisher: Springer Nature
ISBN: 3031264967
Category : Technology & Engineering
Languages : en
Pages : 302
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Book Description
This book provides readers with emerging research that explores the theoretical and practical aspects of implementing new and innovative artificial intelligence (AI) techniques for renewable energy systems. The contributions offer broad coverage on economic and promotion policies of renewable energy and energy-efficiency technologies, the emerging fields of neuro-computational models and simulations under uncertainty (such as fuzzy-based computational models and fuzzy trace theory), evolutionary computation, metaheuristics, machine learning applications, advanced optimization, and stochastic models. This book is a pivotal reference for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in artificial intelligence, renewable energy systems, and energy autonomy.
Author: Pandey, Jay Kumar
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 506
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Book Description
As sustainable energy becomes the future, integrating solar power into existing systems presents critical challenges. Intelligent solutions are required to optimize energy production while maintaining transparency, reliability, and trust in decision-making processes. The growing complexity of these systems calls for advanced technologies that can ensure efficiency while addressing the unique demands of renewable energy sources. Explainable Artificial Intelligence and Solar Energy Integration explores how Explainable AI (XAI) enhances transparency in AI-driven solutions for solar energy integration. By showcasing XAI's role in improving energy efficiency and sustainability, the book bridges the gap between AI potential and real-world solar energy applications. It serves as a comprehensive resource for researchers, engineers, policymakers, and students, offering both technical insights and practical case studies.
Author: Tetyana Baydyk
Publisher: Springer
ISBN: 3030022366
Category : Computers
Languages : en
Pages : 292
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Book Description
After an introduction to renewable energy technologies, the authors present computational intelligence techniques for optimizing the manufacture of related technologies, including solar concentrators. In particular the authors present new applications for their neural classifiers for image and pattern recognition. The book will be of interest to researchers in computational intelligence, in particular in the domain of neural networks, and engineers engaged with renewable energy technologies.
