Artificial Intelligence for Energy Efficiency - Lee, Dasheng; Jeng, Ming-Shan; Tsai, I-Haur
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Artificial Intelligence for Energy Efficiency is a comprehensive exploration of AI application technologies. The book integrates AI algorithms with the operational principles of electrical machinery and energy systems and introduces how these algorithms can alter the operational characteristics of such systems. With a focus on their use in enhancing energy efficiency, it imparts interdisciplinary knowledge and a deep understanding of the principles and methods of AI applications. The book begins with an overview of global trends in enhancing energy efficiency, followed by an introduction to AI…mehr

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Produktbeschreibung
Artificial Intelligence for Energy Efficiency is a comprehensive exploration of AI application technologies. The book integrates AI algorithms with the operational principles of electrical machinery and energy systems and introduces how these algorithms can alter the operational characteristics of such systems. With a focus on their use in enhancing energy efficiency, it imparts interdisciplinary knowledge and a deep understanding of the principles and methods of AI applications. The book begins with an overview of global trends in enhancing energy efficiency, followed by an introduction to AI algorithms applied in this field. Subsequent chapters, supported by industry case studies, delve into AI applications in enhancing motor efficiency, building and energy saving for building equipment, and smart city development. The book also addresses AI computing power saving and discusses the evolution of AI and the limits of energy efficiency improvement. It concludes with future prospects and the most beneficial application of AI for sustainable human development. Artificial Intelligence for Energy Efficiency is an essential read for graduate students in mechanical, electrical, architectural, and energy-related fields, as well as researchers interested in the intersection of AI and energy efficiency. This comprehensive guide offers a wealth of research case studies, making it a valuable reference tool for professionals in the energy sector.
Autorenporträt
Prof. Lee has published 23 SCI papers in the past five years (2019-2023), all related to the application of Artificial Intelligence (AI) in enhancing energy efficiency. These papers have been extensively cited, with an average citation count of 36 for the nine papers where he was the first author. His Field-Weighted Citation Impact (FWCI) is 1.235, and he has achieved an h-index of 20. His latest publication in "Applied Thermal Engineering" focuses on "Artificial Intelligence Enabled Energy-Efficient Heating, Ventilation, and Air Conditioning System: Design, Analysis, and Necessary Hardware Upgrades." This paper details the design methods for improving the energy efficiency of HVAC systems using AI and has already garnered 3 citations within three months of publication. These achievements demonstrate Prof. Lee's unique academic insights in AI for Energy Efficiency. Beyond academic accomplishments, in the past five years, Prof. Lee has undertaken 46 research projects commissioned by the government and enterprises, totaling 3.1 million USD. Most of these projects relate to the application of AI in energy conservation, including in air conditioning systems, buildings, factories, and even urban public facilities. His extensive experience in industry-academia collaboration enriches his book on AI for Energy Efficiency, providing many practical examples of improved energy efficiency, making the content more comprehensive.