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AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties. ​Covers renewable energy sector fundamentals; Explains the application of big data in distributed energy domains; Discusses AI and IoT prediction methods and models.
Energy has been a crucial element for human beings and sustainable development. The issues of global warming and non-green energy have yet to be resolved. This book is a collection of twelve articles that provide strong evidence for the success of artificial intelligence deployment in energy research, particularly research devoted to non-intrusive load monitoring, network, and grid, as well as other emerging topics. The presented artificial intelligence algorithms may provide insight into how to apply similar approaches, subject to fine-tuning and customization, to other unexplored energy research. The ultimate goal is to fully apply artificial intelligence to the energy sector. This book may serve as a guide for professionals, researchers, and data scientists—namely, how to share opinions and exchange ideas so as to facilitate a better fusion of energy, academic, and industry research, and improve in the quality of people's daily life activities.
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.
This transformative book explores the power of artificial intelligence (AI) in revolutionizing the utilities industry. It covers crucial topics such as intelligent grids, decentralized energy resources, customer engagement, electric vehicle integration, and more, providing a comprehensive and practical guide to successfully navigate the energy transition. In today's world, the urgency of addressing climate change and transitioning to sustainable energy systems is undeniable. With approximately 60 percent of global greenhouse gas emissions attributed to the energy sector, utilities play a vital role in achieving sustainability goals. The traditional utility business model faces disruption from renewable energy, changing consumer expectations, and regulatory shifts. Embracing AI emerges as a key solution to optimize operations, enhance grid reliability, and meet evolving customer demands. Through compelling case studies and industry-specific use cases, you will discover how AI drives innovation, improves operational efficiency, and contributes to a greener and more sustainable world. As the demand for cleaner and more sustainable energy practices grows, this book demonstrates how AI can support utilities in meeting these demands, making them more resilient, agile, and customer-centric. Whether you're a seasoned industry expert or a curious student, this book equips you with the knowledge and insights to embrace sustainability, navigate the complex energy landscape, leverage AI to shape a positive future, and join the movement towards a greener world, empowered by AI's potential in the utilities industry. What You Will Learn Understand the challenges and opportunities for utilities in the context of climate change, energy poverty, and the evolving business landscape Discover how rapid transformation is needed in the utilities sector to overcome challenges and leverage opportunities for a sustainable future Gain insight into the role of technology, particularly artificial intelligence (AI), as a critical tool for utilities in their transformation journey Be aware of how AI can be applied in building the future utility industry, including its potential impact on energy efficiency, intelligent energy ecosystems, community engagement, and new business models Gain knowledge of the adoption of AI and machine learning technologies in the utility industry, including the current state, barriers, significant influencing factors, and an AI adoption maturity model for utilities Recognize the sustainability imperative for utilities and how AI can help in achieving sustainable energy practices Become familiar with the transformation of power generation, microgrids, intelligent transmission and distribution systems, utilities retail, mobility through electric vehicles, and the integration of distributed energy resources (DER) using AI Gain insight into the potential of AI in addressing challenges and driving innovation in the energy ecosystem, such as optimizing power generation assets, enhancing grid intelligence, improving customer service, and enabling clean energy awareness in the metaverse Who This Book Is For Professionals and decision makers in the global utilities industry who want to leverage artificial intelligence (AI) technologies to transform their operations and address challenges and opportunities in the energy sector. This book may also appeal to researchers, academics, and students in the fields of energy engineering, environmental science, data analytics, and AI who want to gain a deeper understanding of AI in the utilities sector and its implications for sustainable energy systems.
ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY AND CLIMATE CHANGE Written and edited by a global team of experts in the field, this groundbreaking new volume presents the concepts and fundamentals of using artificial intelligence in renewable energy and climate change, while also covering the practical applications that can be utilized across multiple disciplines and industries, for the engineer, the student, and other professionals and scientists. Renewable energy and climate change are two of the most important and difficult issues facing the world today. The state of the art in these areas is changing rapidly, with new techniques and theories coming online seemingly every day. It is important for scientists, engineers, and other professionals working in these areas to stay abreast of developments, advances, and practical applications, and this volume is an outstanding reference and tool for this purpose. The paradigm in renewable energy and climate change shifts constantly. In today’s international and competitive environment, lean and green practices are important determinants to increase performance. Corresponding production philosophies and techniques help companies diminish lead times and costs of manufacturing, improve delivery on time and quality, and at the same time become more ecological by reducing material use and waste, and by recycling and reusing. Those lean and green activities enhance productivity, lower carbon footprint and improve consumer satisfaction, which in reverse makes firms competitive and sustainable. This practical, new groundbreaking volume: Features coverage on a wide range of topics such as classical and nature-inspired optimization and optimal control, hybrid and stochastic systems Is ideally designed for engineers, scientists, industrialist, academicians, researchers, computer and information technologists, sustainable developers, managers, environmentalists, government leaders, research officers, policy makers, business leaders and students Is useful as a practical tool for practitioners in the fields of sustainable and renewable energy sustainability Includes wide coverage of how artificial intelligence can be used to impact the struggle against global warming and climate change
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.
Artificial intelligence (AI) has a huge impact on science and technology, including energy, where access to resources has been a source of geopolitical conflicts. AI can predict the demand and supply of renewable energy, optimize efficiency in energy systems, and improve the management of natural energy resources, among other things. This book explores the use of AI tools for improving the management of energy systems and providing sustainability with smart cities, smart facilities, smart buildings, smart transportation, and smart houses. Featuring research from International Federation for Information Processing's (IFIP) “AI in Energy and Sustainability” working group, this book provides new models and algorithms for AI applications in energy and sustainability fields. Any short-term, mid-term and long-term forecasting, optimization models, trend foresights and prescriptions based on scenarios are studied in the energy world and the smart systems for sustainability. The contents of this book are valuable for energy researchers, academics, scholars, practitioners and policy makers.
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.
This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. 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 engaged in the study and performance prediction of renewable energy systems.