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Artificial intelligence of things fo...

El Himer, Sarah.

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Artificial intelligence of things for smart green energy management

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Artificial intelligence of things for smart green energy management/ edited by Sarah El Himer ... [et al.].
其他作者:	El Himer, Sarah.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xiii, 234 p. :ill. (chiefly color), digital ;24 cm.
內容註:	Artificial Intelligence of Things (AIoT) for Renewable Energies Systems -- Design of a Switching Module for Electricity Supply from Solar to Grid by Sensing Light Intensity -- Nonlinear Backstepping Control of a Grid-Connected Doubly Fed Induction Generator Wind Turbine -- Improving LVRT Capability of a Wind Turbine During a Voltage Sag in the Electrical Network -- Optimization of Two Hybrid Micro-Concentrator Photovoltaic Systems for Car-Roof Application -- Machine Learning-based Maximum Power Point Tracking Technique for Concentrated PV/TEG System under Non-Uniform Environmental Conditions -- Two-Dimensional Nanomaterials for Solar Cell Technology -- Improving Control for an Induction Machine using Artificial Intelligence -- Evaluation of the Recommended Algorithms in the Internet of Things -- Exposing Applications of IoT in Green Computing.
Contained By:	Springer Nature eBook
標題:	Renewable energy sources. -
電子資源:	https://doi.org/10.1007/978-3-031-04851-7
ISBN:	9783031048517

Artificial intelligence of things for smart green energy management
Artificial intelligence of things for smart green energy management[electronic resource] /edited by Sarah El Himer ... [et al.]. - Cham :Springer International Publishing :2022. - xiii, 234 p. :ill. (chiefly color), digital ;24 cm. - Studies in systems, decision and control,v. 4462198-4190 ;. - Studies in systems, decision and control ;v. 446..

Artificial Intelligence of Things (AIoT) for Renewable Energies Systems -- Design of a Switching Module for Electricity Supply from Solar to Grid by Sensing Light Intensity -- Nonlinear Backstepping Control of a Grid-Connected Doubly Fed Induction Generator Wind Turbine -- Improving LVRT Capability of a Wind Turbine During a Voltage Sag in the Electrical Network -- Optimization of Two Hybrid Micro-Concentrator Photovoltaic Systems for Car-Roof Application -- Machine Learning-based Maximum Power Point Tracking Technique for Concentrated PV/TEG System under Non-Uniform Environmental Conditions -- Two-Dimensional Nanomaterials for Solar Cell Technology -- Improving Control for an Induction Machine using Artificial Intelligence -- Evaluation of the Recommended Algorithms in the Internet of Things -- Exposing Applications of IoT in Green Computing.

This book is intended to assist in the development of smart and efficient green energy solutions. It introduces energy systems, power generation, and power demands which able to minimise generation costs, power loss or environmental effects. It proposes cutting-edge solutions and approaches based on recent technologies such as intelligent renewable energy systems (wind and solar) These solutions, applied to different sectors, can provide a solid basis for meeting the needs of both developed and developing countries. The book provides a collection of contributions including new techniques, methods, algorithms, practical solutions and models based on applying artificial intelligence and the Internet of things into green energy management systems. It provides a comprehensive reference for researchers, scholars and industry in the field of green energy and computational intelligence.

ISBN: 9783031048517

Standard No.: 10.1007/978-3-031-04851-7doiSubjects--Topical Terms:

543030
Renewable energy sources.

LC Class. No.: TJ808 / .A77 2022

Dewey Class. No.: 621.042

Artificial intelligence of things for smart green energy management
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520 $a This book is intended to assist in the development of smart and efficient green energy solutions. It introduces energy systems, power generation, and power demands which able to minimise generation costs, power loss or environmental effects. It proposes cutting-edge solutions and approaches based on recent technologies such as intelligent renewable energy systems (wind and solar) These solutions, applied to different sectors, can provide a solid basis for meeting the needs of both developed and developing countries. The book provides a collection of contributions including new techniques, methods, algorithms, practical solutions and models based on applying artificial intelligence and the Internet of things into green energy management systems. It provides a comprehensive reference for researchers, scholars and industry in the field of green energy and computational intelligence.
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