Renewable energy generation is crucial for sustainability but its inconsistency in availability requires better storage solutions. The fusion of renewable energy technologies with AI can yield positive outcomes, such as increased energy efficiency, reduced carbon emissions, improved grid stability, and optimized storage techniques and methods. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes various case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges.
Features
This book is for researchers, academics, and graduate students in Energy and Environmental Sciences, and those interested in renewable energy, AI, and energy storage. It's also an excellent reference for industry and government professionals, energy policy makers, and analysts.
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Naveed Ahmed is an Associate Professor at the US–Pakistan Center for Advanced Studies in Energy, National University of Sciences and Technology (NUST), Islamabad. He is an accomplished researcher in energy technologies with over 42 peer-reviewed journal publications, several book chapters, and a strong record of externally funded research projects. He has actively contributed to leading international conferences in the field of energy systems. With more than 10 years of combined postdoctoral and industrial experience, Dr. Ahmed has established himself as a recognized academic contributing to advancements in renewable energy and thermal energy storage research.
Mumtaz A. Qaisrani, a Tenured Assistant Professor, specializing in Energy Engineering with a focus on renewable energy, solar and wind systems, and energy efficiency. He has published over 30 papers in SCI journals in his field, and he has reviewed over 40 manuscripts for various publishers. As an Academic Editor for the International Journal of Energy Research (IF 4.6), he contributes to the scientific community. His diverse academic background and extensive experience drive holistic research advancements in Energy Engineering.
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Hardcover. Condition: new. Hardcover. Renewable energy generation is crucial for sustainability but its inconsistency in availability requires better storage solutions. The fusion of renewable energy technologies with AI can yield positive outcomes, such as increased energy efficiency, reduced carbon emissions, improved grid stability, and optimized storage techniques and methods. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes various case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. FeaturesProvides a comprehensive overview of thermal energy storage methods and systems.Explains AI's role in enhancing thermal energy storage.Includes real-world case studies and discusses perspectives of how TES and AI contribute to sustainability.Addresses the integration of AI with digital twin technology, showcasing how AI algorithms can enhance the predictive accuracy and operational efficiency of digital twins in TES applications.Explores various AI-driven strategies and technologies that enhance the efficiency, reliability, and scalability of energy storage systems.This book is for researchers, academics, and graduate students in Energy and Environmental Sciences, and those interested in renewable energy, AI, and energy storage. It's also an excellent reference for industry and government professionals, energy policy makers, and analysts. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781032850184
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Hardcover. Condition: new. Hardcover. Renewable energy generation is crucial for sustainability but its inconsistency in availability requires better storage solutions. The fusion of renewable energy technologies with AI can yield positive outcomes, such as increased energy efficiency, reduced carbon emissions, improved grid stability, and optimized storage techniques and methods. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes various case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. FeaturesProvides a comprehensive overview of thermal energy storage methods and systems.Explains AI's role in enhancing thermal energy storage.Includes real-world case studies and discusses perspectives of how TES and AI contribute to sustainability.Addresses the integration of AI with digital twin technology, showcasing how AI algorithms can enhance the predictive accuracy and operational efficiency of digital twins in TES applications.Explores various AI-driven strategies and technologies that enhance the efficiency, reliability, and scalability of energy storage systems.This book is for researchers, academics, and graduate students in Energy and Environmental Sciences, and those interested in renewable energy, AI, and energy storage. It's also an excellent reference for industry and government professionals, energy policy makers, and analysts. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781032850184
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Hardcover. Condition: new. Hardcover. Renewable energy generation is crucial for sustainability but its inconsistency in availability requires better storage solutions. The fusion of renewable energy technologies with AI can yield positive outcomes, such as increased energy efficiency, reduced carbon emissions, improved grid stability, and optimized storage techniques and methods. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes various case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. FeaturesProvides a comprehensive overview of thermal energy storage methods and systems.Explains AI's role in enhancing thermal energy storage.Includes real-world case studies and discusses perspectives of how TES and AI contribute to sustainability.Addresses the integration of AI with digital twin technology, showcasing how AI algorithms can enhance the predictive accuracy and operational efficiency of digital twins in TES applications.Explores various AI-driven strategies and technologies that enhance the efficiency, reliability, and scalability of energy storage systems.This book is for researchers, academics, and graduate students in Energy and Environmental Sciences, and those interested in renewable energy, AI, and energy storage. It's also an excellent reference for industry and government professionals, energy policy makers, and analysts. This book provides a state-of-the-art perspective on thermal energy storage (TES) technologies integrated with renewable energy technologies and Artificial Intelligence (AI). It includes case studies and practical applications that offer actionable insights for professionals and researchers in the field and addresses real-world challenges. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781032850184
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