Grid Optimal Integration of Electric Vehicles: Examples with Matlab Implementation

228 Pages·2018·10.395 MB·English

by  Andrés Ovalle,Ahmad Hably,Seddik Bacha (auth.)

Studies in Systems, Decision and Control 137
Andrés Ovalle
Ahmad Hably
Seddik Bacha
Grid Optimal
Integration of
Electric Vehicles:
Examples with Matlab
Implementation
Studies in Systems, Decision and Control
Volume 137
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Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences,
Warsaw, Poland
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é
Andr s Ovalle Ahmad Hably
(cid:129)
Seddik Bacha
Grid Optimal Integration
of Electric Vehicles:
Examples with Matlab
Implementation
123
Andrés Ovalle SeddikBacha
Grenoble INP,G2Elab Grenoble INP,G2Elab
UniversitédeGrenoble Alpes, CNRS UniversitédeGrenoble Alpes, CNRS
Grenoble Grenoble
France France
Ahmad Hably
Grenoble INP,Gipsa-lab
UniversitédeGrenoble Alpes, CNRS
Saint Martin d’Hères
France
ISSN 2198-4182 ISSN 2198-4190 (electronic)
Studies in Systems,DecisionandControl
ISBN978-3-319-73176-6 ISBN978-3-319-73177-3 (eBook)
https://doi.org/10.1007/978-3-319-73177-3
LibraryofCongressControlNumber:2017961754
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To our families
Foreword
This book is a compilation of recent research results on distributed optimization
algorithmsfortheintegralloadmanagementofplug-inelectricvehicle(PEV)fleets
and their potential services to the electricity system. The proposed methodologies
optimallymanagePEVfleetschargeanddischargeschedulesbyapplyingclassical
optimization,gametheory,andevolutionarygametheorytechniques.Itisintended
to be used in graduate optimization and energy management courses.
Afterashortoverviewofthecontextandthestate-of-the-artinChap.1,aclassical
centralized linear algorithm is presented in Chap. 2. In Chap. 3, a decentralized opti-
mizationapproachusingdynamicprogramming(DP)algorithmsandapotentialgame
frameworkisdevelopedtooptimallymanagePEVchargingschedule.Chapters2and3
can be read independently. In Chaps. 4 and 5 further improvements have been intro-
duced for decentralized load management approaches by applying two evolutionary
game theory techniques: the Mixed Strategist Dynamics and the Escort Dynamics.
Thesetechniqueslieintheintersectionbetweenpopulationdynamicsandgametheory.
Theycanbeemployedtorepresenttheevolutionofthedistributionofapopulationofa
givenspeciesovermultipleterritories,dependingontheresourcestheseterritoriesoffer.
In these approaches, the energy consumed by a PEV, and its reactive power, are
quantities represented by individual populations. Then, we have multiple populations
interacting(multiplePEVsinteracting)overagivensetofterritories.Inthesemodels,
territories represent the three phases of the system at different instants ofthe day.
Applying the mathematical representation of these techniques, authors proposed
decentralizedoptimizationalgorithmsforPEVstoprovidemultipleancillaryservicesto
the electricity grid. These algorithms tackle the stochastic behavior of variables like
arrivalanddeparture,initialandfinalstateofcharge,andsocialoreconomicincentives
toPEVownersfromutilitygridmanagers.Withoutdifferentiationbetweensingleand
three-phase PEV chargers, the proposed methodologies seek to provide services like
load compensation (load shifting and peak shaving), load balancing among phases
of the system, reactive power supply, task and resource sharing among PEVs, and
interactionwithrenewableenergymicro-sourcesanddedicatedenergystoragedevices.
The proposed algorithms in this book are tested under multiple scenarios using
real data in collaboration with the SOREA electricity distribution company in the
vii
viii Foreword
region of Savoie, France. The main Matlab scripts are provided and commented.
Thesealgorithmscanbeimplementedinreal-timeapplicationsandcanbeextended
to other domains where energy management is required (smart buildings, energy
storage in railways systems, task sharing of micro-generators in micro-grids, etc.).
Thereadercantestandadaptthesescriptstohis/herspecificapplications.Thisbook
will be useful for students, researchers and engineers as well,in the domains of
electric vehicle grid integration in particular, and energy management ingeneral.
Montréal, QC, Canada Kamal Al-Haddad
January 2018 M.Sc.A. Ph.D. Fellow IEEE, Fellow CAE
Professor and Canada Research Senior Chair CRC-EECPE
Electric Energy Conversion and Power Electronics
Acknowledgements
Authorswouldliketoacknowledgetheworkofcollaboratorswhohelpedustoset
thebasesoftheresultspresentedinthisbook.ItisalsoapleasuretothankGustavo
Ramos,DavisMontenegro,JulianFernandez,KamalAl-Haddad,AlainOustaloup,
BenoîtRobyns,RachidIbtiouen,AdrianFlorescu,andanonymousreviewerswhose
perceptive comments have helped to improve this book immeasurably. Any flaws
that remain are, of course, the responsibility of the authors.
Grenoble, France Andrés Ovalle
Saint Martin d’Héres, France Ahmad Hably
Grenoble, France Seddik Bacha
January 2018
ix
Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 A Brief Review of the State of the Art . . . . . . . . . . . . . . . . . . . 3
1.2.1 PEV Load Management Approaches . . . . . . . . . . . . . . . 4
1.3 Book Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2 Centralized Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2.1 Constraints on the Charger . . . . . . . . . . . . . . . . . . . . . . 12
2.2.2 Constraints on Partial and Final States of Charge . . . . . . 13
2.2.3 Constraints on Voltage Levels . . . . . . . . . . . . . . . . . . . . 14
2.3 Details on the Voltage Level Modeling Approach . . . . . . . . . . . 14
2.3.1 Modeling both PEV and Residential Load
as a Current Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.4 Illustrative Example with 8-Node Grid Topology . . . . . . . . . . . 21
2.4.1 PEVs Without Charging Management—Grid Case 1 . . . 22
2.4.2 Charging Management—Grid Case 1—Single Tariff . . . . 23
2.4.3 Charging Management—Grid Case 1—Two Tariff
Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.4.4 Charging Management—Grid Case 2 . . . . . . . . . . . . . . . 26
2.5 Test Case with the IEEE European Low Voltage
Test Feeder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.5.1 The IEEE European Low Voltage Test Feeder and
Its Simplification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.2 Comparison Between the Approximated Linear Model
and the Accurate Model from OpenDSS . . . . . . . . . . . . 31
2.5.3 Description of the Integration of PEVs . . . . . . . . . . . . . . 33
2.5.4 Results with Single Tariff . . . . . . . . . . . . . . . . . . . . . . . 36
2.5.5 Results with Double Tariff . . . . . . . . . . . . . . . . . . . . . . 40
xi