6 books on AI for Energy [PDF]

October 24, 2024

These books offer a deep understanding of how artificial intelligence can be applied to optimize energy generation, distribution, consumption, and management.

1. Decision Making Using AI in Energy and Sustainability: Methods and Models for Policy and Practice
2023 by



Artificial intelligence (AI) has profoundly influenced various domains, including energy, which is pivotal amid geopolitical resource challenges. This book delves into AI's role in predicting renewable energy demand and supply, optimizing energy system efficiency and enhancing natural resource management. It explores AI applications across smart cities, facilities, buildings, transportation and homes, aiming to bolster sustainability. With contributions from the International Federation for Information Processing’s “AI in Energy and Sustainability” working group, the book introduces novel models and algorithms tailored for these fields. It covers short-term, mid-term and long-term forecasting, optimization models, trend analysis and scenario-based prescriptions crucial for energy researchers, academics, practitioners and policymakers striving for sustainable energy solutions.
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2. Renewable Energy and AI for Sustainable Development
2023 by Sailesh Iyer, Anand Nayyar, Mohd Naved, Fadi Al-Turjman



The book "Renewable Energy and AI for Sustainable Development" delves into the growing electronic device usage of the past two decades, where system configurations frequently require upgrades and devices quickly become obsolete. It emphasizes the importance of green computing, which entails environmentally conscious management from design and manufacturing to use and disposal. This comprehensive resource explores innovative approaches to energy conservation, efficient e-waste management and the utilization of renewable energy sources for fostering a sustainable and eco-friendly environment. The book covers a range of topics, including AI-based sustainable models, alternative energy sources and successful case studies. It offers practical insights, mathematical equations and real-world applications, serving as a valuable reference for stakeholders in green computing, e-waste management, renewable energy and sustainable transformation. The book also explores cutting-edge technologies like the internet of energy and artificial intelligence, particularly the roles of machine learning and deep learning in advancing renewable energy and sustainable ecosystems, while also examining future trends in renewable energy. This resource is intended for engineers, architects, technicians, scientists, researchers and consultants interested in energy systems, as well as individuals working on renewable energy and sustainable computing initiatives, providing a comprehensive overview of the global renewable energy landscape and its intersection with science and technology.
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3. AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems
2023 by S. Vijayalakshmi, Savita ., Balamurugan Balusamy, Rajesh Kumar Dhanaraj



The book "AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems" delves into the possibilities of leveraging advanced applications such as artificial intelligence (AI), the Internet of Things (IoT) and Machine Learning (ML) for the design and modeling of energy systems, particularly in the context of renewable energy. Its primary goals are to illustrate how big data can contribute to enhancing energy efficiency and reducing demand, promoting the utilization of renewable energy sources and facilitating the transition from a centralized energy system to a distributed, efficient and integrated one. The contributions encompass the essential aspects of the renewable energy sector, encompassing solar, wind, biomass and hydrogen, along with discussions on building services and power generation systems. Furthermore, the book explores prediction methods for renewable energy properties and delves into the application of AI and IoT prediction models for estimating biomass thermal properties.
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4. Intelligent Renewable Energy Systems: Integrating Artificial Intelligence Techniques and Optimization Algorithms
2022 by Neeraj Priyadarshi, Akash Kumar Bhoi, P. Sanjeevikumar, S. Balamurugan, Jens Bo Holm-Nielsen



This book compiles a series of expert-authored papers that explore the integration of artificial intelligence techniques and optimization algorithms to enhance renewable energy systems. It serves as a comprehensive resource for engineers, maintenance personnel, students and anyone interested in staying updated on the latest advancements in energy systems technology. Renewable energy is a pivotal topic, influencing global economic stability and individual energy consumption choices. The book delves into the modeling, simulation, design and control of renewable energy systems, leveraging recent artificial intelligence (AI) and optimization methods to improve their performance. Traditional renewable energy sources often suffer from limited power conversion efficiency due to their intermittent and variable nature. In contrast, modern AI and optimization techniques excel in handling data ambiguity, noise, imprecision and nonlinear behavior exhibited by renewable energy sources. By offering a thorough examination of the latest AI and optimization approaches applied to green energy systems, this book becomes an invaluable resource for researchers, industry professionals and both undergraduate and graduate students in the field of renewable energy. It is a must-have addition to any library, catering to a diverse audience, including engineers, scientists, managers and other renewable energy professionals seeking to expand their knowledge and expertise in this dynamic field.
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5. AI and IOT in Renewable Energy
2021 by Rabindra Nath Shaw, Nishad Mendis, Saad Mekhilef, Ankush Ghosh



This book explores the cutting-edge research concerning the utilization of artificial intelligence and the Internet of Things (IoT) within the realm of renewable energy systems. As modern renewable energy systems demand the integration of state-of-the-art technology like AI and IoT to create cost-effective, intelligent and efficient solutions, this work delves into the pivotal role of these technologies. Intelligence enables the system to optimize power generation, enhancing energy efficiency, while IoT provides wireless, flexible operation capabilities. Consequently, the application of intelligent AI and IoT paradigms is gaining prominence in the domain of renewable energy systems. The book delves into advanced applications of artificial intelligence and IoT in the development of renewable energy systems, covering diverse areas such as solar energy systems, electric vehicles and more. It encompasses various AI techniques, including artificial neural networks, genetic algorithms, fuzzy logic and hybrid systems that combine these methods. Targeting a wide audience, from undergraduates to researchers and industry professionals engaged in the study and performance prediction of renewable energy systems, this book offers valuable insights into the future of renewable energy technology.
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6. Artificial Intelligence Techniques for a Scalable Energy Transition: Advanced Methods, Digital Technologies, Decision Support Tools, and Applications
2020 by Moamar Sayed-Mouchaweh



This book explores the utilization of artificial intelligence techniques in the context of energy transition, encompassing a wide range of applications such as energy production, distribution, management, renewable energy, cybersecurity, Industry 4.0 and the Internet of Things, among others. It distinguishes itself by placing a particular emphasis on the application of AI methods to address the various challenges associated with different facets of energy transition. The contributions within are categorized based on market dynamics and interactions among key stakeholders (e.g., service providers, manufacturers, customers, utilities, integrators), the structure of smart grid architecture (including the physical, infrastructure and business layers), the concept of the digital twin in the smart grid (encompassing business, operational, fault/transient and asset models) and the specific application domains (such as demand-side management, load monitoring, microgrids, energy consulting, energy conservation, dynamic pricing, revenue management and smart meters). This comprehensive book serves as a valuable resource for researchers, professionals and stakeholders interested in harnessing the potential of artificial intelligence for a scalable and efficient energy transition.
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