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Artificial intelligence of things for smart green energy management

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence of things for smart green energy managementedited by Sarah El Himer ... [et al.].
other author:	El Himer, Sarah.
Published:	Cham :Springer International Publishing :2022.
Description:	xiii, 234 p. :ill. (chiefly color), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Renewable energy sources.
Online resource:	https://doi.org/10.1007/978-3-031-04851-7
ISBN:	9783031048517$q(electronic bk.)

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.3..

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$q(electronic bk.)

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

190766
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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505 0 $a 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.
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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