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Methods for Optimal Charging of Large Fleets of Electric Vehicles.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Methods for Optimal Charging of Large Fleets of Electric Vehicles./
Author:	Le Floch, Caroline.
Description:	1 online resource (147 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
Subject:	Alternative Energy. -
Online resource:	click for full text (PQDT)
ISBN:	9780355576344

Methods for Optimal Charging of Large Fleets of Electric Vehicles.
Le Floch, Caroline.

Methods for Optimal Charging of Large Fleets of Electric Vehicles. - 1 online resource (147 pages)

Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.

Thesis (Ph.D.)--University of California, Berkeley, 2017.

Includes bibliographical references

Today's electric grid must be transformed to meet modern consumption behaviors and safely integrate renewable energy sources. This has led to major efforts to develop grid-scale energy management solutions and ensure safety and reliability of our modern power network. In particular, large penetrations of Plug-in Electric Vehicles (PEVs) are expected increase energy needs and peak consumption, which would bring new challenges for utilities and grid operators.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355576344Subjects--Topical Terms:

845381
Alternative Energy.
Index Terms--Genre/Form:

554714
Electronic books.

Methods for Optimal Charging of Large Fleets of Electric Vehicles.
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100 1 $a Le Floch, Caroline. $3 1188078
245 1 0 $a Methods for Optimal Charging of Large Fleets of Electric Vehicles.
264 0 $c 2017
300 $a 1 online resource (147 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 79-07(E), Section: B.
500 $a Adviser: Scott Moura.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2017.
504 $a Includes bibliographical references
520 $a Today's electric grid must be transformed to meet modern consumption behaviors and safely integrate renewable energy sources. This has led to major efforts to develop grid-scale energy management solutions and ensure safety and reliability of our modern power network. In particular, large penetrations of Plug-in Electric Vehicles (PEVs) are expected increase energy needs and peak consumption, which would bring new challenges for utilities and grid operators.
520 $a In this work, we develop optimization methods to coordinate the charging of large fleets of PEVs in distribution grids. We show that different methods should be applied, based on the infrastructure requirements and the objective of the controller.
520 $a The first Chapter Optimal Charging of Fleets of Electric Vehicles with Discrete Charging rates: PDE Modeling and Control Techniques presents a continuum modeling framework to coordinate PEV charging with discrete charging rates. We consider PEVs as loads, which diffuse along the State Of Energy (SOE) axis, and can be in three different categories: charging, discharging or idle. We use a discretized form of Partial Differential Equations (PDEs) to model the dynamics of the system and control the transitions between each category. The second Chapter Dual Splitting Framework for Optimal Charging of Fleets of Electric Vehicles with Continuous Charging rates proposes a tailored distributed optimization method to coordinate PEV charging for load shaping. Three iteration methods are presented and their convergence characteristics are detailed. The third Chapter Electric Vehicle Charging in the Smart Grid: Plug-and-Play Model Predictive Control techniques studies a voltage-regulation scenario for PEV charging. Power flow and distribution grid constraints are modeled, and PEV charging is controlled with Plug-and-Play Model Predictive Control. Finally, the final chapter Behavioral study of Demand Response programs studies the impact of non rational choices on energy consumption and on the success of Demand Response programs.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Alternative Energy. $3 845381
650 4 $a Applied mathematics. $3 1069907
655 7 $a Electronic books. $2 local $3 554714
690 $a 0363
690 $a 0364
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of California, Berkeley. $b Civil and Environmental Engineering. $3 1183008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10600396 $z click for full text (PQDT)