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Renewable energy for buildings : technology, control, and operational techniques
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ISBN: 3031087313 3031087321 Year: 2022 Publisher: Cham, Switzerland : Springer,

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Book
Renewable Energy for Buildings
Authors: --- --- --- --- --- et al.
ISBN: 9783031087325 Year: 2022 Publisher: Cham Springer International Publishing :Imprint: Springer

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Digital
Renewable Energy for Buildings : Technology, Control, and Operational Techniques
Authors: --- --- --- ---
ISBN: 9783031087325 9783031087318 9783031087332 9783031087349 Year: 2022 Publisher: Cham Springer International Publishing

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The book covers practical applications and experimental results of integrating renewable energy technologies, energy storage facilities, and intelligent control and operation techniques into building energy systems. It introduces practical approaches to improving the energy systems of buildings in order to reduce energy consumption and cost. Renewable Energy for Buildings is suitable for retrofit engineers, energy engineers, and professionals, as well as researchers and developers in electrical engineering, architectural engineering, and mechanical engineering. Moreover, it can be used by undergraduate and graduate students to become familiar with the most recent developments in building energy systems. Examines the most recent developments in building energy systems; Looks at practical applications and theoretical aspects; Includes case studies.


Multi
Application of Machine Learning and Deep Learning Methods to Power System Problems
Authors: --- --- --- --- --- et al.
ISBN: 9783030776961 9783030776978 9783030776985 9783030776954 Year: 2021 Publisher: Cham Springer International Publishing :Imprint: Springer

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This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses. Offers innovative machine learning and deep learning methods for dealing with power system issues; Provides promising solution methodologies; Covers theoretical background and experimental analysis.

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