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Author: Pinaki Pratim Acharjya
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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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. Machine Learning and Computer Vision for Renewable Energy positions itself as a catalyst for this change. The book not only addresses the immediate concerns of the energy sector but also details how to achieve a more sustainable future. By emphasizing breakthroughs in CV and AI, the objective is clear: to drive societal progress through research, innovation, and technological advancements in the domain of renewable energy. Academic researchers, professors, college students, and business professionals focused on the intersection of digital transformation and renewable energy will find this book to be an indispensable guide to navigating the challenges and opportunities that lie ahead. With a diverse array of recommended topics, this book stands as a testament to the evolving landscape of AI and computer vision, shaping a sustainable energy future for generations to come.
Author: Pinaki Pratim Acharjya
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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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. Machine Learning and Computer Vision for Renewable Energy positions itself as a catalyst for this change. The book not only addresses the immediate concerns of the energy sector but also details how to achieve a more sustainable future. By emphasizing breakthroughs in CV and AI, the objective is clear: to drive societal progress through research, innovation, and technological advancements in the domain of renewable energy. Academic researchers, professors, college students, and business professionals focused on the intersection of digital transformation and renewable energy will find this book to be an indispensable guide to navigating the challenges and opportunities that lie ahead. With a diverse array of recommended topics, this book stands as a testament to the evolving landscape of AI and computer vision, shaping a sustainable energy future for generations to come.
Author: Ashutosh Kumar Dubey
Publisher: Elsevier
ISBN: 9780443289477
Category : Technology & Engineering
Languages : en
Pages : 0
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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: 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: 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: Rabindra Nath Shaw
Publisher: Academic Press
ISBN: 0323984010
Category : Science
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: George K. Thiruvathukal
Publisher: CRC Press
ISBN: 1000540960
Category : Computers
Languages : en
Pages : 395
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Book Description
Energy efficiency is critical for running computer vision on battery-powered systems, such as mobile phones or UAVs (unmanned aerial vehicles, or drones). This book collects the methods that have won the annual IEEE Low-Power Computer Vision Challenges since 2015. The winners share their solutions and provide insight on how to improve the efficiency of machine learning systems.
Author: Krishna Kumar
Publisher: Academic Press
ISBN: 0323914284
Category : Science
Languages : en
Pages : 418
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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
Author: Suman Lata Tripathi
Publisher: CRC Press
ISBN: 1000392457
Category : Technology & Engineering
Languages : en
Pages : 423
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Book Description
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: Neeraj Priyadarshi
Publisher: John Wiley & Sons
ISBN: 1119786282
Category : Computers
Languages : en
Pages : 484
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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.
Author: Arpit Jain
Publisher: CRC Press
ISBN: 1000934004
Category : Computers
Languages : en
Pages : 160
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Book Description
The text provides sustainable energy solutions using smart technologies such as artificial intelligence, blockchain technology, and the Internet of Things. It further presents several case studies on applications of the Internet of Things, artificial intelligence, and blockchain technology in the field of sustainable energy. Focuses on the integration of smart technology including artificial intelligence and sustainable energy Covers recent advancements in energy management techniques used in residential and commercial energy systems Highlights the use of artificial intelligence, machine learning, and their applications in sustainable energy Discusses important topics such as green energy, grid modernization, smart security in the power grid, and fault diagnosis Presents case studies on the applications of the Internet of Things, blockchain, and artificial intelligence in sustainable energy The text showcases the latest advancements, and the importance of technologies including artificial intelligence, blockchain, and Internet of Things in achieving sustainable energy systems. It further discusses the role of machine learning, applied deep learning, and edge computing in renewable energy. The text cover key concepts such as intelligent battery management system, energy trading, green energy, grid modernization, electric vehicles, and charging station optimization. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including electrical engineering, electronics and communication engineering, computer engineering, and environmental engineering.
