國立虎尾科技大學 |

Artificial intelligence for integrated smart energy systems in electric vehicles

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Artificial intelligence for integrated smart energy systems in electric vehicles/ edited by Surender Reddy Salkuti.
其他作者:	Salkuti, Surender Reddy.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xix, 733 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Electrical Power Engineering. -
電子資源:	https://doi.org/10.1007/978-3-031-94276-1
ISBN:	9783031942761

Artificial intelligence for integrated smart energy systems in electric vehicles
Artificial intelligence for integrated smart energy systems in electric vehicles[electronic resource] /edited by Surender Reddy Salkuti. - Cham :Springer Nature Switzerland :2025. - xix, 733 p. :ill. (some col.), digital ;24 cm. - Lecture notes in electrical engineering,v. 14271876-1119 ;. - Lecture notes in electrical engineering ;v. 34 .

Artificial Intelligence in Electric Vehicles for Sustainable Driving -- Modernization of Electric Grids for Charging of Electric Vehicles -- Mitigating Impacts of Electric Vehicle Charging Stations to the Distribution Systems by Optimal Operation of Soft Open Point -- Performance Evaluation of Artificial Neural Networks for Electric Vehicle State of Charge Estimation across Different Driving Cycles -- GJO-Pattern Search Algorithm based DG and Capacitor Placement in Distribution Network with Zone based Installation of EVCSs, etc.

This book provides a comprehensive exploration of cutting-edge research in electric vehicles (EVs) integrated smart energy systems with a main focus on the application of artificial intelligence (AI). This book offers a wide and comprehensive practical approach with the applications of AI to address the challenges and opportunities of modern hybrid energy systems for developing advanced hybrid intelligent methodologies for forecasting and scheduling variable power output from renewable energy sources (RESs) and EVs. This will enhance system flexibility and facilitate the integration of RESs and EVs efficiently, which is a step towards a sustainable future. The chapters cover diverse topics offering valuable knowledge and methodologies including an introduction to Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Cybersecurity, and their applications in modern power and energy systems, intelligent control of power electronics for RESs and EVs, intelligent charging management of EVs, etc. This book aims to provide insights into various suitable solutions to increase the security, reliability, and interoperability of the grid under high penetration of renewable energy, storage systems, and electric transport in the context of the modern smart grid. The multi-objective optimization problems such as economic and emission dispatch problems; flexibility and reliability problems; and economic and reliability problems are solved to determine the trade-off solutions using efficient evolutionary algorithms. The chapters cover diverse topics offering valuable knowledge and methodologies including an introduction to Artificial Intelligence (AI), Machine Learning (ML), IoT, Cybersecurity, and their applications in modern power and energy systems, intelligent control of power electronics for RESs and EVs, intelligent charging management of EVs, etc.

ISBN: 9783031942761

Standard No.: 10.1007/978-3-031-94276-1doiSubjects--Topical Terms:

1365891
Electrical Power Engineering.

LC Class. No.: TL220

Dewey Class. No.: 629.2293

Artificial intelligence for integrated smart energy systems in electric vehicles
LDR:03564nam a2200349 a 4500 001 1159580
003 DE-He213
005 20250702130316.0
006 m d
007 cr nn 008maaau
008 251029s2025 sz s 0 eng d
020 $a 9783031942761 $q (electronic bk.)
020 $a 9783031942754 $q (paper)
024 7 $a 10.1007/978-3-031-94276-1 $2 doi
035 $a 978-3-031-94276-1
040 $a GP $c GP
041 0 $a eng
050 4 $a TL220
072 7 $a THR $2 bicssc
072 7 $a TEC007000 $2 bisacsh
072 7 $a THR $2 thema
082 0 4 $a 629.2293 $2 23
090 $a TL220 $b .A791 2025
245 0 0 $a Artificial intelligence for integrated smart energy systems in electric vehicles $h [electronic resource] / $c edited by Surender Reddy Salkuti.
260 $a Cham : $c 2025. $b Springer Nature Switzerland : $b Imprint: Springer,
300 $a xix, 733 p. : $b ill. (some col.), digital ; $c 24 cm.
338 $a online resource $b cr $2 rdacarrier
490 1 $a Lecture notes in electrical engineering, $x 1876-1119 ; $v v. 1427
505 0 $a Artificial Intelligence in Electric Vehicles for Sustainable Driving -- Modernization of Electric Grids for Charging of Electric Vehicles -- Mitigating Impacts of Electric Vehicle Charging Stations to the Distribution Systems by Optimal Operation of Soft Open Point -- Performance Evaluation of Artificial Neural Networks for Electric Vehicle State of Charge Estimation across Different Driving Cycles -- GJO-Pattern Search Algorithm based DG and Capacitor Placement in Distribution Network with Zone based Installation of EVCSs, etc.
520 $a This book provides a comprehensive exploration of cutting-edge research in electric vehicles (EVs) integrated smart energy systems with a main focus on the application of artificial intelligence (AI). This book offers a wide and comprehensive practical approach with the applications of AI to address the challenges and opportunities of modern hybrid energy systems for developing advanced hybrid intelligent methodologies for forecasting and scheduling variable power output from renewable energy sources (RESs) and EVs. This will enhance system flexibility and facilitate the integration of RESs and EVs efficiently, which is a step towards a sustainable future. The chapters cover diverse topics offering valuable knowledge and methodologies including an introduction to Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Cybersecurity, and their applications in modern power and energy systems, intelligent control of power electronics for RESs and EVs, intelligent charging management of EVs, etc. This book aims to provide insights into various suitable solutions to increase the security, reliability, and interoperability of the grid under high penetration of renewable energy, storage systems, and electric transport in the context of the modern smart grid. The multi-objective optimization problems such as economic and emission dispatch problems; flexibility and reliability problems; and economic and reliability problems are solved to determine the trade-off solutions using efficient evolutionary algorithms. The chapters cover diverse topics offering valuable knowledge and methodologies including an introduction to Artificial Intelligence (AI), Machine Learning (ML), IoT, Cybersecurity, and their applications in modern power and energy systems, intelligent control of power electronics for RESs and EVs, intelligent charging management of EVs, etc.
650 2 4 $a Electrical Power Engineering. $3 1365891
650 2 4 $a Control and Systems Theory. $3 1211358
650 1 4 $a Electrical and Electronic Engineering. $3 1388937
650 0 $a Battery charging stations (Electric vehicles) $3 1091170
650 0 $a Artificial intelligence $x Engineering applications. $3 889372
650 0 $a Renewable energy sources. $3 558536
650 0 $a Electric vehicles. $3 639235
700 1 $a Salkuti, Surender Reddy. $e editor. $3 1401818
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in electrical engineering ; $v v. 34 $3 773550
856 4 0 $u https://doi.org/10.1007/978-3-031-94276-1
950 $a Engineering (SpringerNature-11647)