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Intelligent control and smart energy...

Blondin, Maude Josee.

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Intelligent control and smart energy management = renewable resources and transportation /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent control and smart energy management/ edited by Maude Josee Blondin ... [et al.].
其他題名:	renewable resources and transportation /
其他作者:	Blondin, Maude Josee.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xiv, 427 p. :ill., digital ;24 cm.
內容註:	Predictive Energy Management for Fuel Cell Hybrid Electric Vehicles (Zhou) -- Plug-in Hybrid Electric Buses with Different Battery Chemistries Total Cost of Ownership Planning and Optimization at Fleet Level based on Battery Aging (Lopez-Ibarra) -- Stochastic Optimization Methods for the Stochastic Storage Processes Control (Knopov) -- Challenges for a Massive Integration of Flexible Resources in LV Networks (Arboleya) -- Electrical railway power supply systems for high-speed lines: from traditional grids to smart grids (Castano-Solisr) -- Energy-efficient scheduling of intra-terminal container transport (Homayouni) -- Learning-based Control for Hybrid Battery Management Systems (Castro) -- Robust, Resilient, and Energy Efficient Satellite Formation Control (Phillips) -- A Methodology for the Assessment of Efficiency in Systems under Transient Conditions: Case Study for Hybrid Storage Systems in Elevators (Garcia) -- A holistic approach to the energy-efficient smoothing of traffic via autonomous vehicles (Hayat) -- Optimal energy management of electric vehicles supplied by battery and supercapacitors: A multi-objective approach (Nguyen) -- Transient Stability and Protection Evaluation of Distribution Systems with Distributed Energy Resources (Morais) -- Fuzzy Logic Control for Motor Drive Performance Improvement in EV Applications (C. Ta)
Contained By:	Springer Nature eBook
標題:	Energy conservation - Automation. -
電子資源:	https://doi.org/10.1007/978-3-030-84474-5
ISBN:	9783030844745

Intelligent control and smart energy management = renewable resources and transportation /
Intelligent control and smart energy managementrenewable resources and transportation /[electronic resource] :edited by Maude Josee Blondin ... [et al.]. - Cham :Springer International Publishing :2022. - xiv, 427 p. :ill., digital ;24 cm. - Springer optimization and its applications,v. 1811931-6836 ;. - Springer optimization and its applications ;v. 181..

Predictive Energy Management for Fuel Cell Hybrid Electric Vehicles (Zhou) -- Plug-in Hybrid Electric Buses with Different Battery Chemistries Total Cost of Ownership Planning and Optimization at Fleet Level based on Battery Aging (Lopez-Ibarra) -- Stochastic Optimization Methods for the Stochastic Storage Processes Control (Knopov) -- Challenges for a Massive Integration of Flexible Resources in LV Networks (Arboleya) -- Electrical railway power supply systems for high-speed lines: from traditional grids to smart grids (Castano-Solisr) -- Energy-efficient scheduling of intra-terminal container transport (Homayouni) -- Learning-based Control for Hybrid Battery Management Systems (Castro) -- Robust, Resilient, and Energy Efficient Satellite Formation Control (Phillips) -- A Methodology for the Assessment of Efficiency in Systems under Transient Conditions: Case Study for Hybrid Storage Systems in Elevators (Garcia) -- A holistic approach to the energy-efficient smoothing of traffic via autonomous vehicles (Hayat) -- Optimal energy management of electric vehicles supplied by battery and supercapacitors: A multi-objective approach (Nguyen) -- Transient Stability and Protection Evaluation of Distribution Systems with Distributed Energy Resources (Morais) -- Fuzzy Logic Control for Motor Drive Performance Improvement in EV Applications (C. Ta)

This volume aims to provide a state-of-the-art and the latest advancements in the field of intelligent control and smart energy management. Techniques, combined with technological advances, have enabled the deployment of new operating systems in many engineering applications, especially in the domain of transport and renewable resources. The control and energy management of transportation and renewable resources are shifting towards autonomous reasoning, learning, planning and operating. As a result, these techniques, also referred to as autonomous control and energy management, will become practically ubiquitous soon. The discussions include methods, based on neural control (and others) as well as distributed and intelligent optimization. While the theoretical concepts are detailed and explained, the techniques presented are tailored to transport and renewable resources applications, such as smart grids and automated vehicles. The reader will grasp the most important theoretical concepts as well as to fathom the challenges and needs related to timely practical applications. Additional content includes research perspectives and future direction as well as insight into the devising of techniques that will meet tomorrow's scientific needs. This contributed volume is for researchers, graduate students, engineers and practitioners in the domains of control, energy, and transportation.

ISBN: 9783030844745

Standard No.: 10.1007/978-3-030-84474-5doiSubjects--Topical Terms:

3599494
Energy conservation
--Automation.

LC Class. No.: TJ163.3 / .I57 2022

Dewey Class. No.: 658.26

Intelligent control and smart energy management = renewable resources and transportation /
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520 $a This volume aims to provide a state-of-the-art and the latest advancements in the field of intelligent control and smart energy management. Techniques, combined with technological advances, have enabled the deployment of new operating systems in many engineering applications, especially in the domain of transport and renewable resources. The control and energy management of transportation and renewable resources are shifting towards autonomous reasoning, learning, planning and operating. As a result, these techniques, also referred to as autonomous control and energy management, will become practically ubiquitous soon. The discussions include methods, based on neural control (and others) as well as distributed and intelligent optimization. While the theoretical concepts are detailed and explained, the techniques presented are tailored to transport and renewable resources applications, such as smart grids and automated vehicles. The reader will grasp the most important theoretical concepts as well as to fathom the challenges and needs related to timely practical applications. Additional content includes research perspectives and future direction as well as insight into the devising of techniques that will meet tomorrow's scientific needs. This contributed volume is for researchers, graduate students, engineers and practitioners in the domains of control, energy, and transportation.
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