Machine Learning And Computer Vision For Renewable Energy
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Machine Learning And Computer Vision For Renewable Energy
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Author : Acharjya, Pinaki Pratim
language : en
Publisher: IGI Global
Release Date : 2024-05-01
Machine Learning And Computer Vision For Renewable Energy written by Acharjya, Pinaki Pratim and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-01 with Technology & Engineering categories.
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.
Computer Vision And Machine Intelligence For Renewable Energy Systems
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Author : Ashutosh Kumar Dubey
language : en
Publisher: Elsevier
Release Date : 2024-09-20
Computer Vision And Machine Intelligence For Renewable Energy Systems written by Ashutosh Kumar Dubey and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-20 with Technology & Engineering categories.
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
Introduction To Ai Techniques For Renewable Energy System
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Author : Suman Lata Tripathi
language : en
Publisher: CRC Press
Release Date : 2021-11-25
Introduction To Ai Techniques For Renewable Energy System written by Suman Lata Tripathi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-25 with Technology & Engineering categories.
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.
Sustainable Development Through Machine Learning Ai And Iot
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Author : Pawan Whig
language : en
Publisher: Springer Nature
Release Date : 2024-09-24
Sustainable Development Through Machine Learning Ai And Iot written by Pawan Whig and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-24 with Computers categories.
This book constitutes the refereed proceedings of the Second International Conference on Sustainable Development through Machine Learning, AI and IoT, ICSD 2024, held in Virtual Event, during April 27–28, 2024. The 38 full papers presented here were carefully reviewed and selected from 167 submissions. These papers have been categorized into the following sections: This volume encompassing a diverse array of topics at the intersection of cutting-edge technologies and practical applications. Each chapter delves into innovative approaches and solutions, providing valuable insights into contemporary challenges and opportunities in various domains. Here, we explore the realms of blockchain, data science, machine learning, artificial intelligence, and more, offering in-depth analyses and practical implementations.
Iot Machine Learning And Blockchain Technologies For Renewable Energy And Modern Hybrid Power Systems
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Author : C. Sharmeela
language : en
Publisher: CRC Press
Release Date : 2023-01-27
Iot Machine Learning And Blockchain Technologies For Renewable Energy And Modern Hybrid Power Systems written by C. Sharmeela and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-27 with Computers categories.
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.
Artificial Intelligence And Machine Learning Applications For Sustainable Development
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Author : A. J. Singh
language : en
Publisher: CRC Press
Release Date : 2025-01-28
Artificial Intelligence And Machine Learning Applications For Sustainable Development written by A. J. Singh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-28 with Technology & Engineering categories.
The book highlights how technologies including artificial intelligence and machine learning are transforming renewable energy technologies and enabling the development of new solutions. It further discusses how smart technologies are employed to optimize energy production and storage, enhance energy efficiency, and improve the overall sustainability of energy systems. This book: Discusses artificial intelligence-based techniques, namely, neural networks, fuzzy expert systems, optimization techniques, and operational research Showcases the importance of artificial intelligence and machine learning in the energy market, demand analysis, and forecasting of renewable energy applications Illustrates strategies for sustainable development using artificial intelligence and machine learning applications Presents applications of artificial intelligence in the domain of electronics transformation and development, smart cities, and renewable energy utilization Highlights the role of artificial intelligence in solving problems such as image and signal processing, smart weather monitoring, smart farming, and distributed energy sources It is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields, including electrical, electronics and communications, energy, and environmental engineering.
Explainable Artificial Intelligence And Solar Energy Integration
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Author : Pandey, Jay Kumar
language : en
Publisher: IGI Global
Release Date : 2024-10-16
Explainable Artificial Intelligence And Solar Energy Integration written by Pandey, Jay Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-16 with Computers categories.
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.
Leveraging Ai For Innovative Sustainable Energy Solar Wind And Green Hydrogen
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Author : Hammouch, Hind
language : en
Publisher: IGI Global
Release Date : 2025-05-15
Leveraging Ai For Innovative Sustainable Energy Solar Wind And Green Hydrogen written by Hammouch, Hind and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-15 with Technology & Engineering categories.
Artificial intelligence (AI) and intelligent technologies play a vital role in transforming the energy sector, which is key to delivering lower carbon footprints combined with increased levels of security. AI-driven innovations in solar, wind energy, green hydrogen generation increase efficiency to achieve further sustainability. Furthermore, the disruptive impact of AI-based solutions in the energy sector is informative for initiating more sustainable industrial and commercial purposes and practices worldwide. Thus, AI-enabled systems and their capabilities in generation, distribution of energy and consumption can contribute to helping build more robust and greener infrastructures for our resources. Leveraging AI for Innovative Sustainable Energy: Solar, Wind and Green Hydrogen offers practical steps for incorporating green hydrogen into established energy systems that can help to realize net-zero emissions targets. It inspires innovation by detailing the experiences of real-life case studies and presenting forward-looking viewpoints that make collaboration between various sectors possible, all towards embracing renewable energy solutions on a global scale. Covering topics such as hydrogen power, marketing strategies, and public education campaigns, this book is an excellent resource for environmental advocates, sustainability practitioners, policymakers, manufacturers, industry leaders, professionals, researchers, scholars, academicians, and more.
Artificial Intelligence For Renewable Energy Systems
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Author : Ashutosh Kumar Dubey
language : en
Publisher: Woodhead Publishing
Release Date : 2022-08-01
Artificial Intelligence For Renewable Energy Systems written by Ashutosh Kumar Dubey and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-01 with Science categories.
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
Large Language Models For Sustainable Urban Development
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Author : Nitin Liladhar Rane
language : en
Publisher: Springer Nature
Release Date : 2025-07-01
Large Language Models For Sustainable Urban Development written by Nitin Liladhar Rane and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Computers categories.
With rapid urbanization defining the 21st Century, cities face mounting challenges in achieving sustainability, equity, and functionality. This book explores how innovative technologies such as Artificial Intelligence (AI) and Large Language Models (LLMs) can transform urban development by offering intelligent, data-driven solutions. LLMs go beyond automation, acting as co-creators in addressing environmental sustainability, resource management, and equitable development. By analyzing regulations, best practices, and real-time data on phenomena such as air pollution and traffic, these models empower urban planners to design smarter, more sustainable cities while fostering collaboration across disciplines. Divided into five sections, the book explores the diverse applications of LLMs, from optimizing renewable energy systems and enhancing urban planning to revolutionizing construction practices and improving resource efficiency. It highlights case studies on integrating AI with smart infrastructure, ecological balance, and disaster resilience. While underscoring their transformative potential, the book also examines ethical considerations such as bias, privacy, and environmental impact. More than a collection of research, this work is a call to action for urban planners, data scientists, policymakers, and researchers to harness AI responsibly in building greener, more equitable urban futures.