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Artificial intelligence in renewable...

Hatti, Mustapha.

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Artificial intelligence in renewable energetic systems = smart sustainable energy systems /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence in renewable energetic systems/ edited by Mustapha Hatti.
Reminder of title:	smart sustainable energy systems /
other author:	Hatti, Mustapha.
Published:	Cham :Springer International Publishing : : 2018.,
Description:	xii, 531 p. :ill., digital ;24 cm.
[NT 15003449]:	NPC Multilevel Inverters Advanced Conversion Technology in APF -- Optimization Study of Hybrid Renewable Energy System in Autonomous Site -- Ensemble of Support Vector Methods to Estimate Global Solar Radiation In Algeria -- Study of percentage effect of Polymer blends system on physical properties using MM/QM approach -- Optimization and characterization of Nanowires Semiconductor based-Solar Cells -- Using Phase Change Materials (PCMs) to reduce energy consumption in buildings -- Optimization of Copper Indium Gallium Diselenide Thin Film Solar Cell (CIGS)
Contained By:	Springer eBooks
Subject:	Engineering. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-73192-6
ISBN:	9783319731926

Artificial intelligence in renewable energetic systems = smart sustainable energy systems /
Artificial intelligence in renewable energetic systemssmart sustainable energy systems /[electronic resource] :edited by Mustapha Hatti. - Cham :Springer International Publishing :2018. - xii, 531 p. :ill., digital ;24 cm. - Lecture notes in networks and systems,v.352367-3370 ;. - Lecture notes in networks and systems ;v.35..

NPC Multilevel Inverters Advanced Conversion Technology in APF -- Optimization Study of Hybrid Renewable Energy System in Autonomous Site -- Ensemble of Support Vector Methods to Estimate Global Solar Radiation In Algeria -- Study of percentage effect of Polymer blends system on physical properties using MM/QM approach -- Optimization and characterization of Nanowires Semiconductor based-Solar Cells -- Using Phase Change Materials (PCMs) to reduce energy consumption in buildings -- Optimization of Copper Indium Gallium Diselenide Thin Film Solar Cell (CIGS)

This book includes the latest research presented at the International Conference on Artificial Intelligence in Renewable Energetic Systems held in Tipaza, Algeria on October 22-24, 2017. The development of renewable energy at low cost must necessarily involve the intelligent optimization of energy flows and the intelligent balancing of production, consumption and energy storage. Intelligence is distributed at all levels and allows information to be processed to optimize energy flows according to constraints. This thematic is shaping the outlines of future economies of and offers the possibility of transforming society. Taking advantage of the growing power of the microprocessor makes the complexity of renewable energy systems accessible, especially since the algorithms of artificial intelligence make it possible to take relevant decisions or even reveal unsuspected trends in the management and optimization of renewable energy flows. The book enables those working on energy systems and those dealing with models of artificial intelligence to combine their knowledge and their intellectual potential for the benefit of the scientific community and humanity.

ISBN: 9783319731926

Standard No.: 10.1007/978-3-319-73192-6doiSubjects--Topical Terms:

586835
Engineering.

LC Class. No.: Q342 / .A785 2018

Dewey Class. No.: 621.042

Artificial intelligence in renewable energetic systems = smart sustainable energy systems /
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520 $a This book includes the latest research presented at the International Conference on Artificial Intelligence in Renewable Energetic Systems held in Tipaza, Algeria on October 22-24, 2017. The development of renewable energy at low cost must necessarily involve the intelligent optimization of energy flows and the intelligent balancing of production, consumption and energy storage. Intelligence is distributed at all levels and allows information to be processed to optimize energy flows according to constraints. This thematic is shaping the outlines of future economies of and offers the possibility of transforming society. Taking advantage of the growing power of the microprocessor makes the complexity of renewable energy systems accessible, especially since the algorithms of artificial intelligence make it possible to take relevant decisions or even reveal unsuspected trends in the management and optimization of renewable energy flows. The book enables those working on energy systems and those dealing with models of artificial intelligence to combine their knowledge and their intellectual potential for the benefit of the scientific community and humanity.
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