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Advances in artificial intelligence for renewable energy systems and energy autonomy

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advances in artificial intelligence for renewable energy systems and energy autonomyedited by Mukhdeep Singh Manshahia ... [et al.].
其他作者:	Manshahia, Mukhdeep Singh.
出版者:	Cham :Springer International Publishing :2023.
面頁冊數:	xxii, 285 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Renewable energy sourcesTechnological innovations.
電子資源:	https://doi.org/10.1007/978-3-031-26496-2
ISBN:	9783031264962$q(electronic bk.)

Advances in artificial intelligence for renewable energy systems and energy autonomy
Advances in artificial intelligence for renewable energy systems and energy autonomy[electronic resource] /edited by Mukhdeep Singh Manshahia ... [et al.]. - Cham :Springer International Publishing :2023. - xxii, 285 p. :ill. (chiefly col.), digital ;24 cm. - EAI/Springer innovations in communication and computing,2522-8609. - EAI/Springer innovations in communication and computing..

Chapter 1. General Approaches to Assessing Electrical Load of Agro-Industrial Complex Facilities When Justifying the Parameters of the Photovoltaic Power System -- Chapter 2. RBFNN for MPPT Controller in Wind Energy Harvesting System -- Chapter 3. Simulation Optimum Performance All-Wheels Plug-In Hybrid Electric Vehicle -- Chapter 4. Artificial Intelligence application to flexibility provision in energy management system: a survey -- Chapter 5. Machine Learning Applications for Renewable Energy Systems -- Chapter 6. New Technologies and Equipment For Smelting Technical Silicon -- Chapter 7. Reconfiguration of distribution network considering photovoltaic system placement based on metaheuristic algorithms -- Chapter 8. Technology of Secondary Cast Polycrystalline Silicon And Its Application In The Production Of Solar Cells -- Chapter 9. Machine Learning Applications for Renewable based Energy Systems -- Chapter 10. Bi-Objective Optimal Scheduling of Smart Homes Appliances using Artificial Intelligence -- Chapter 11. Optimal placement of photovoltaic systems and wind turbines in distribution systems by using Northern Goshawk Optimization algorithm -- Chapter 12. Granulated silicon and thermal energy converters on its basis -- Chapter 13. Security Constrained Unit Commitment with Wind Energy Resource using Universal Generating Function.

This book provides readers with emerging research that explores the theoretical and practical aspects of implementing new and innovative artificial intelligence (AI) techniques for renewable energy systems. The contributions offer broad coverage on economic and promotion policies of renewable energy and energy-efficiency technologies, the emerging fields of neuro-computational models and simulations under uncertainty (such as fuzzy-based computational models and fuzzy trace theory), evolutionary computation, metaheuristics, machine learning applications, advanced optimization, and stochastic models. This book is a pivotal reference for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in artificial intelligence, renewable energy systems, and energy autonomy. Based on sustainability as a fundamental factor for intelligent computing; Focuses on the role AI plays in smart living, energy transition, and sustainable development; Covers a broad range of green energy-related topics.

ISBN: 9783031264962$q(electronic bk.)

Standard No.: 10.1007/978-3-031-26496-2doiSubjects--Topical Terms:

530862
Renewable energy sources
--Technological innovations.

LC Class. No.: TJ808

Dewey Class. No.: 333.794

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520 $a This book provides readers with emerging research that explores the theoretical and practical aspects of implementing new and innovative artificial intelligence (AI) techniques for renewable energy systems. The contributions offer broad coverage on economic and promotion policies of renewable energy and energy-efficiency technologies, the emerging fields of neuro-computational models and simulations under uncertainty (such as fuzzy-based computational models and fuzzy trace theory), evolutionary computation, metaheuristics, machine learning applications, advanced optimization, and stochastic models. This book is a pivotal reference for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in artificial intelligence, renewable energy systems, and energy autonomy. Based on sustainability as a fundamental factor for intelligent computing; Focuses on the role AI plays in smart living, energy transition, and sustainable development; Covers a broad range of green energy-related topics.
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