Computer Vision And Machine Intelligence For Renewable Energy Systems
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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
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.
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
Reliable Non Parametric Techniques For Energy System Operation And Control
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Author : Hongcai Zhang
language : en
Publisher: Elsevier
Release Date : 2025-07-01
Reliable Non Parametric Techniques For Energy System Operation And Control written by Hongcai Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Technology & Engineering categories.
Reliable Non-Parametric Techniques for Energy System Operation and Control: Fundamentals and Applications of Constraint Learning and Safe Reinforcement Learning Methods, a new Volume in the Advances in Intelligent Energy Systems, is a comprehensive guide to modern smart methods in energy system operation and control. This book covers fundamental concepts and applications in both deterministic and uncertain environments. It addresses the challenge of accuracy in imbalanced datasets and the limitations of measurements. The book delves into advanced topics such as safe reinforcement learning for energy system control, including training-efficient intrinsic-motivated reinforcement learning, and physical layer-based control, and more. Other chapters cover barrier function-based control and CVaR-based control for systems without hard operation constraints. Designed for graduate students, researchers, and engineers, this book stands out for its practical approach to advanced methods in energy system control, enabling sustainable developments in real-world conditions. - Bridges the gap between theory and practice, providing essential insights for graduate students, researchers, and engineers - Includes visual elements, data and code, and case studies for easy understanding and implementation - Provides the latest release in the Advances in Intelligent Energy Systems series, bringing together the latest innovations in smart, sustainable energy
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.
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.
Optimization In Sustainable Energy
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Author : Prasenjit Chatterjee
language : en
Publisher: John Wiley & Sons
Release Date : 2026-07-14
Optimization In Sustainable Energy written by Prasenjit Chatterjee and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-07-14 with Computers categories.
This state-of-the-art book offers cutting-edge optimization techniques and practical decision-making frameworks essential for enhancing the efficiency and reliability of sustainable energy systems, making it an invaluable resource for researchers, policymakers, and energy professionals. Optimization in Sustainable Energy: Methods and Applications brings together valuable knowledge, methods, and practical examples to help scholars, researchers, professionals, and policymakers address the growing challenges of optimizing sustainable energy. This volume covers a range of topics, including mathematical models, heuristic algorithms, renewable resource management, and energy storage optimization. Each chapter explores a different aspect of sustainable energy, providing both theoretical understanding and practical guidance. The volume explores challenges and opportunities surrounding the integration of multi-criteria decision-making techniques in energy planning, highlighting insights on environmental, economic, and social factors influencing the strategic allocation of resources. The use of evolutionary algorithms, machine learning, and metaheuristics to optimize energy storage, distribution, and optimization are also discussed. The transition towards sustainable energy is at the forefront of global priorities, driven by the urgent need to mitigate climate change, reduce carbon emissions, and enhance energy security. As countries and industries increasingly prioritize renewable sources like wind, solar, and hydroelectric power, the complexity of optimizing these systems becomes a critical challenge. Optimization in Sustainable Energy: Methods and Applications, is a comprehensive exploration of cutting-edge methodologies used to enhance the efficiency, reliability, and performance of sustainable energy systems. Audience Research scholars, academics, students, policymakers, and industry experts in mechanical engineering, electrical engineering, and energy science.
Advances In Artificial Intelligence For Renewable Energy Systems And Energy Autonomy
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Author : Mukhdeep Singh Manshahia
language : en
Publisher: Springer Nature
Release Date : 2023-06-14
Advances In Artificial Intelligence For Renewable Energy Systems And Energy Autonomy written by Mukhdeep Singh Manshahia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-14 with Technology & Engineering categories.
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.
Artificial Intelligence Tools Book
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Author : Manish Soni
language : en
Publisher:
Release Date : 2024-11-17
Artificial Intelligence Tools Book written by Manish Soni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-17 with Study Aids categories.
Welcome to the exciting and rapidly evolving world of artificial intelligence (AI). This book, "Artificial Intelligence Tools: Unlocking the Power of Intelligent Systems," is designed to be your comprehensive guide to understanding, implementing, and leveraging the cutting-edge tools that drive the advancements in AI. Whether you are a seasoned professional in the field or a curious newcomer, this book aims to provide you with valuable insights and practical knowledge to navigate the multifaceted landscape of AI tools. From machine learning algorithms to neural networks, readers will gain insights into the core concepts that form the backbone of intelligent systems. We aim to make complex ideas accessible, ensuring that readers, regardless of their technical background, can grasp the essentials of AI.
Integrating Artificial Intelligence Into The Energy Sector
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Author : Derbali, Abdelkader Mohamed Sghaier
language : en
Publisher: IGI Global
Release Date : 2025-04-08
Integrating Artificial Intelligence Into The Energy Sector written by Derbali, Abdelkader Mohamed Sghaier and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-08 with Business & Economics categories.
Artificial intelligence (AI) plays a crucial role in the energy sector, equipping machines with the capability to acquire knowledge and make decisions aimed at solving problems or enhancing outcomes to achieve specific objectives. The integration of AI in the energy domain holds promise in addressing climate change, reducing emissions resulting from technological advancements in industry, maintaining energy equilibrium, and mitigating environmental impacts. The integration of AI into the energy sector proves to be indispensable in furnishing industry and households with novel information services for overseeing energy infrastructure. This includes optimizing power generation, curbing consumption, and combating climate change, among other practices that underscore the potential role of AI. Integrating Artificial Intelligence Into the Energy Sector explores the applications of AI in energy sectors, and their usage in business, home, and organizational improvement. It examines solutions for sustainability, infrastructure development, and data management. This book covers topics such as data science, electric vehicles, and cloud computing, and is a useful resource for data scientists, engineers, business owners, climatologists, academicians, and researchers.