Table Of ContentShahab Bahrami · Ali Mohammadi
Editors
Smart
Microgrids
From Design to Laboratory-Scale
Implementation
Smart Microgrids
Shahab Bahrami • Ali Mohammadi
Editors
Smart Microgrids
From Design to Laboratory-Scale
Implementation
123
Editors
ShahabBahrami AliMohammadi
UniversityofBritishColumbia DepartmentofElectricalandComputer
Vancouver,BC,Canada Engineering
LouisianaStateUniversity
BatonRouge,LA,USA
ISBN978-3-030-02655-4 ISBN978-3-030-02656-1 (eBook)
https://doi.org/10.1007/978-3-030-02656-1
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Preface
This book paves the way for researchers working on the smart microgrids spread
over the fields of electrical engineering, power systems, and smart infrastructures.
Furthermore,itprovidesthereaderswithacomprehensiveinsighttounderstandan
in-depth big picture of smart microgrids as well as an all-inclusive framework for
laboratory-scaleimplementationofamicrogrid.
It is suitable for senior undergraduate students, graduate students who are
interestedinresearchinareasrelatedtofuturesmartgridsandmicrogrids,andthe
researchersworkingintherelatedareas.Thisbookalsocanbeusedasareference
book for researchers who want to develop laboratories on smart microgrids for
futureresearch.
Here are the unique aspects of this book, which address the smart microgrids
frombothdesignandimplementationperspectives:
The book specifies the importance and position of the microgrids in the future
powersystems.
– Thisbookprovidesacomprehensiveinvestigationofrecentlydevelopedcontrol,
management,andoptimizationmethodsformicrogrids.
– The book provides basics and mathematical foundations needed to analyze and
simulatemicrogrids.
– This book also can be used as a reference book for related courses in electrical
andcomputerengineering.
Vancouver,BC,Canada ShahabBahrami
BatonRouge,LA,USA AliMohammadi
v
Contents
AnOverviewofFutureMicrogrids ............................................ 1
AliMohammadiandShahabBahrami
Laboratory-Scale Microgrid System for Control of Power
DistributioninLocalEnergyNetworks–PartI:TheoryandDesign...... 7
RaselMahmudandArashNejadpak
Laboratory-Scale Microgrid System for Control of Power
DistributioninLocalEnergyNetworks–PartII:Implementation
andCaseStudy................................................................... 29
RaselMahmudandArashNejadpak
AHierarchicalApproachBasedontheFrank–WolfeAlgorithm
andDantzig–WolfeDecompositionforSolvingLargeEconomic
DispatchProblemsinSmartGrids............................................. 41
JianyiZhang,M.HadiAmini,andPaulWeng
AComprehensiveStudyofGameTheoryApplicationsforSmart
Grids,DemandsideManagementProgramsandTransportation
Networks.......................................................................... 57
AliMohammadiandSanazRabinia
Micro-Small-Scale Horizontal Axis Wind Turbine Design
andPerformanceAnalysisforMicro-GridsApplications................... 65
AdelEl-Shahat,MehediHasan,andAlmoatazY.Abdelaziz
ADistributedCoordinationFrameworkforSmartMicrogrids............ 119
IrfanKhan,YiheZhang,HengyuXue,andMashoodNasir
Index............................................................................... 137
vii
About the Editors
ShahabBahrami receivedhisBScandMAScbothinelectricalengineeringfrom
Sharif University of Technology, Tehran, Iran, in 2010 and 2012, respectively. He
received the PhD in electrical and computer engineering from the University of
BritishColumbia(UBC),Vancouver,BC,Canada,in2017.Dr.Bahramicontinued
to work as a postdoctoral research fellow at UBC until January 2018. He has
received Sharif University’s Exceptional Talents Scholarship Award in 2010 and
various prestigious scholarships at UBC, including the distinguished and highly
competitive UBC’s Four-Year Fellowship (2013–2017), which is open to all local
and international graduate students at UBC, as well as the Graduate Support
Initiative Award from the Faculty of Applied Science at UBC (2014–2017). Dr.
BahramialsoreceivedaBestPaperAwardattheIEEEPacificRimConferenceon
Communications,ComputersandSignalProcessing(PACRIM2015).Dr.Bahrami
iscurrentlyaTechnicalProgramCommittee(TPC)memberofIEEEInternational
Conference of Communications (ICC 2018) and IEEE International Conference
on Smart Energy Systems and Technologies (SEST 2019). He is also a reviewer
of various journals and conferences, including the IEEE Transactions on Power
Systems, IEEE Transactions on Smart Grid, and IEEE SmartGridComm. He has
publishedmorethan40refereedjournalandconferencepapersinthesmartenergy
systems-related areas. His research interests include smart microgrids, power flow
analysis, demand side management, game theory, optimization, and algorithm
designwithapplicationstosmartgrid.
AliMohammadi received his BS in electrical engineering (telecommunication)
from Shahid Bahonar University of Kerman, Kerman, Iran, 2012, and his MS in
electrical engineering (telecommunication) from Shiraz University of Technology,
Shiraz,Iran,2014.HeiscurrentlypursuinghisPhDintheDepartmentofElectrical
and Computer Engineering, Louisiana State University, LA, USA. His research
interests include smart grids, power system optimization, machine learning, game
theory,andgraphtheory.
ix
An Overview of Future Microgrids
AliMohammadiandShahabBahrami
An Introduction to smart microgrids and their role in future power systems is
provided in this chapter. In the following, we provide the abstract of all chapters
ofthisbookaswellassomeadditionalstudiesforfurtherdetails.
1 OverviewofChapter “Laboratory-ScaleSmartMicrogrid
SystemforControlofPowerDistributionin LocalEnergy
Networks”
One of the promising solutions to achieve sustainable energy systems in future
smart cities is to deploy microgrids in local energy networks. Due to the decen-
tralizednatureofmicrogrids,large-scaleutilizationoftheseresourceswillincrease
the reliability of the energy systems and facilitate the integration of renewable
energyresourcestoenablemoreenvironmentally-friendlyenergynetworks.Chapter
“Laboratory-Scale Smart Microgrid System for Control of Power Distribution
in Local Energy Networks” presents development of a highly reconfigurable,
laboratory–scale microgrid testbed. The proposed microgrid system integrates
several distributed generation (DG) units representing photovoltaic panel, wind
turbine, and battery energy storage. The schematic of the proposed system can be
customizedtoinvestigatenumerousgridarchitecturesandcontrolscenarios.Inthis
A.Mohammadi((cid:2))
DepartmentofElectricalandComputerEngineering,LouisianaStateUniversity,BatonRouge,
LA,USA
e-mail:[email protected]
S.Bahrami
UniversityofBritishColumbia,Vancouver,BC,Canada
e-mail:[email protected]
©SpringerNatureSwitzerlandAG2019 1
S.Bahrami,A.Mohammadi(eds.),SmartMicrogrids,
https://doi.org/10.1007/978-3-030-02656-1_1
2 A.MohammadiandS.Bahrami
study, the loads and energy resource allocation are realized by assessment of the
loads and resources priority.Therefore, a hierarchical procedure willtake place to
allocatethepowertodifferentbuseswithinamicrogrid.Also,theauthorsdescribe
thetest-bedimplementationofthedesignedmicrogrid.Formoredetailsonthistopic
pleaserefertothefollowingstudies[1–5].
2 OverviewofChapter “Laboratory-ScaleMicrogridSystem
forControlofPowerDistributioninLocalEnergy
Networks”
In chapter “Laboratory-Scale Microgrid System for Control of Power Distribution
in Local Energy Networks”, the authors provide the detailed implementation of
their proposed microgrid framework. As a case study, a droop-based load sharing
algorithm with the capability of controlling the active and reactive powers have
been implemented. Several load sharing scenarios have been studied to verify the
capabilityofthesuggestedprototypeinperformanceevaluationandverificationof
differentcontrolstrategiesformicrogrids.Theperformedexperimentsconfirmthe
capacity of the proposed structure in microgrid research and development (R&D),
as well as education. For more details on this topic please refer to the following
studies[6–10].
3 OverviewofChapter “AHierarchicalApproachBased
onthe Frank-WolfeAlgorithmand Dantzig-Wolfe
DecompositionforSolvingLarge-ScaleEconomicDispatch
ProblemsinSmartGrids”
Chapter “A Hierarchical Approach Based on the Frank-Wolfe Algorithm and
Dantzig-Wolfe Decomposition for Solving Large-Scale Economic Dispatch Prob-
lems in Smart Grids” presents a decomposition method to solve the economic
dispatchproblemforaclusterofmicrogrids.
Theeconomicdispatchproblemaimsatdeterminingboththepowergeneration
and demand levels of each microgrid under boundary and power flow constraints
inordertominimizeanon-linearconvexeconomiccost,whichisexpressedasthe
combinationofgenerationcostsanddemandutilities.
Directly solving large economic dispatch problems is difficult because of the
non-linearityoftheobjectivefunction,memorylimitationsandprivacyissues.The
authors propose a decomposition method based on a combination of the Frank-
Wolfe algorithm to tackle the non-linearity and the Dantzig-Wolfe decomposition
tosolvetheabove-mentionedtwoissues.Formoredetailsonthistopicpleaserefer
tothefollowingstudies[11–15].
AnOverviewofFutureMicrogrids 3
4 “AComprehensiveStudy ofGameTheoryApplications
forSmartGrids, DemandSide ManagementPrograms,
andTransportationNetworks”
Game theory is a powerful analytical tool for modeling decision makers strate-
gies, behaviors and interactions. A decision maker and decisions can benefit or
negatively impact other decision makers interests. Game theory has been broadly
used in economics, politics and engineering field. For example, game theory
can model decision making procedure of different companies competing with
each other to maximize their profit. Chapter “A Comprehensive Study of Game
Theory Applications for Smart Grids, Demand Side Management Programs, and
Transportation Networks” presents a brief introduction to game theory and its
applications. The focus of this chapter is noncooperative Stackelberg game model
and its applications in solving power system related problems. These applications
include but not limited to; expanding transmission network, improving power
systemreliability,containingmarketpowerintheelectricitymarkets,solvingpower
system dispatch, executing demand response and allocating resources in wireless
networks.Finally,thischapterelaboratesonsolvingagametheoryproblemthrough
an example. For more details on this topic please refer to the following studies
[16–20].
5 OverviewofChapter “Micro-Small-ScaleHorizontalAxis
Wind Turbine DesignandPerformanceAnalysisfor
Micro-GridsApplications”
Wind energy has become one of the world’s popular growing renewable energy
sources for electricity generation. In order to spread this technology to mankind,
itisnecessarytodevelop turbinesinawaythatpeoplecanuseitindividuallyand
comfortably. Although significant progress has been achieved in the wind turbine
technology, there is still scope to reduce the cost and improve the performance
of small-scale wind turbines. Moreover, low wind velocity should also be utilized
properlytoachievesaturatedenergyproduction.Small-scalewindenergysystems
suchasSmallScaleHorizontalAxisWindTurbines(SSHAWT)canprovideaclean,
prospectiveandviableoptionforenergysupply.Moreover,thisenergysystemcan
alsobeutilizedasoneofthereliablepowersourcesformicrogrids.Thefirstpartof
the current study focuses on the aerodynamic design and performance analysis of
small-scalehorizontalaxiswindturbinebladeusingthebladeelementmomentum
(BEM)methodwiththemostupdatedandcorrectedmodel.Inthiscase,theblade
is designed with a single airfoil. Results show that the maximum coefficient of
performance is 0.446 at the tip speed ratio 6.5 which is very good indication in
preliminary stage power prediction. The second part of the study concentrates on
