integrated models for transmission & distribuon plus

IntegratedModelsforTransmission&Distribu6onplusBonus1:UnitCommitment+PlanningBonus2:Distribu8onSteady-State+PHILBryanPalmin6er,PhDSeniorResearchEngineerPowerSystemsEngineeringCenterNa6onalRenewableEnergyLab

IEEE PES General Meeting 2016 July 21, 2016 Boston, Massachusetts

NREL/PR-5D00-66996NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

2

Amapofpower-systemssimula6ontools

•  Markets•  Transmission•  Distribu6on•  Devices•  Hardware•  Co-simula6on

•  Transient•  Dynamic•  Steady-State•  Planning

•  Technical•  Economic•  Techno-economic

Timestep

Spatial

msec sec min hr day yr/decade

nation

state

metro

zipcode

feeder

device

Technical (e.g. Power flow

Techno-Economic

Economic-focused

External Developer

NREL Tool

NREL Co-simulation

Simulation-only

Optimization sub-problem

Optimal-decision 2/2016-BSP

Sim Power SystemsMathworks

RTDSRTDS

PSS/E (Siemens)PSLF (GE)…MATPOWER (Cornell)

MAFRITNREL

eMegaSimOpal-RT

PSC

AD

MHI

FESTIVNREL

PlexosEnergy Exemplar

GridLAB-DPNNL

OpenDSS (EPRI)...CyME (Cooper)Synergi (DNV-GL)DEW (EDD)Windmil (Milsoft)

PV, Storage simsNREL SAM (NREL)

HEMS-simNREL

FESTIVNREL

TEADSNREL

REPRANREL

HoST (NREL)...DPV (EPRI)

ReEDSNREL

RPMNREL

dSol

ar, d

Stor

age,

dW

ind

(NRE

L)

Distribution PlanningToolsNREL

PSC

AD

MHI


RTDSRTDS


MAFRITNREL

eMegaSimOpal-RT

FESTIVNREL


GridLAB-DPNNL



HEMS-simNREL

FESTIVNREL

TEADSNREL

REPRANREL



ReEDSNREL

RPMNREL

dSol

ar, d

Stor

age,

dW

ind

(NRE

L)

IGMSNREL

IESMNRELTeDI

NREL

Palmin8er,etal.ModelingandSimula8onToolsforAnalyzingHighPenetra8onsofVariableRenewablesinElectricPowerSystems.ForthcomingNRELTechnicalReport

3

Theshortblanketproblem

Solu6ons•  StretchtheBlanket(Simplify)•  Usetwoblankets(Co-simula6on)•  Useabiggerblanket(BiggerComputer)

DomainA

DomainB

4

FlexibilityinPlanning:UC+Planning

Timestep

Spatial


nation

state

metro

zipcode

feeder

device

Technical (e.g. Power flow)

Techno-Economic

Economic-focused

External Developer

NREL Tool

NREL Co-simulation

Simulation-only




RTDSRTDS


MAFRITNREL

eMegaSimOpal-RT

PSCA

DM

HI

FESTIVNREL


GridLAB-DPNNL



HEMS-simNREL

FESTIVNREL

TEADSNREL

REPRANREL


ReEDSNREL

RPMNREL

dSol

ar, d

Stor

age,

dW

ind

(NRE

L)


PSCA

DM

HI


RTDSRTDS


MAFRITNREL

eMegaSimOpal-RT

FESTIVNREL


GridLAB-DPNNL



HEMS-simNREL

FESTIVNREL

TEADSNREL

REPRANREL



ReEDSNREL

RPMNREL

dSol

ar, d

Stor

age,

dW

ind

(NRE

L)

IGMSNREL

IESMNRELTeDI

NREL


5

FlexibilityinPlanning:UC+Planning

•  Opera6onalFlexibility➔UnitCommitment

WithPlanning➔ClusteredIntegerUC

o  MILPo  Fast(15-500x)o  Maintainskeyunit-leveldetails

–  Reserves–  On/Off&minimumup/down6me–  Maintenance

o  Lowerrors(0.3-1.4%forplanning)•  Results--FlexibilityImportantforPlanning

with:o  StrictCarbonLimitso  HighVariableRenewablePenetra6on

5

Infl xible Low-Carbon

Baseload

Increased Flexibility

Required by Variable

RenewablesInfl xible

Coal*

Quantity of (variable) RenewablesSt

rictn

ess

of C

arbo

n Po

licy

0Units on-line, Ûĝ,b,t

nĝ

Units on maintenance, Mĝ,b

max

Units built, Nĝ

0

nĝmax

0

nĝmax

NG-CCNG-GT Nuclear(When)doesopera6onalflexibilityimpactplanning?

B.Palmin8erandM.D.Webster,“ImpactofOpera8onalFlexibilityonElectricityGenera8onPlanningWithRenewableandCarbonTargets,”IEEETransac8onsonSustainableEnergy,vol.7,no.2,pp.672–684,Apr.2016.

Stretch

6

Power-Hardware-in-the-LoopCo-simula6on

Timestep

Spatial


nation

state

metro

zipcode

feeder

device


Techno-Economic

Economic-focused

External Developer

NREL Tool

NREL Co-simulation

Simulation-only




RTDSRTDS


MAFRITNREL

eMegaSimOpal-RT

PSCA

DM

HI

FESTIVNREL


GridLAB-DPNNL



HEMS-simNREL

FESTIVNREL

TEADSNREL

REPRANREL


ReEDSNREL

RPMNREL

dSol

ar, d

Stor

age,

dW

ind

(NRE

L)


PSCA

DM

HI


RTDSRTDS


MAFRITNREL

eMegaSimOpal-RT

FESTIVNREL


GridLAB-DPNNL



HEMS-simNREL

FESTIVNREL

TEADSNREL

REPRANREL



ReEDSNREL

RPMNREL

dSol

ar, d

Stor

age,

dW

ind

(NRE

L)

IGMSNREL

IESMNRELTeDI

NREL

Co-simula8on


7

PHILwithLargerGridModels–PHILCo-simula6on

Combinesactualhardwaretes6ngusingPHILwithco-simula6onoflargerelectricpowergridusingoff-the-shelfmodelingtools.Veryflexiblearchitectureenablesmul6-sitetes6ng(e.g.NRELlinkstoPNNLandCSIRO),andscenarioflexibility•  ArbitraryGrid:loca6on,topology&equipment

•  Demo:IEEE8500and123withnohardwarechanges

•  Anyscenario:normalops,faults,con6ngencies•  Demo:Cloudtransients,homethermalphysicsmodels

•  Actualhardware:noproprietarymodelsrequired•  Demo:2advancedinvertersatvariouspointsofcommoncoupling

•  Mul6-site:hardwareand/orsimula6on•  Demo:PNNL(WA)linktoNREL(CO)•  CSIRO(Australia)

B.Palmin8er,B.Lundstrom,S.Chakraborty,T.Williams,“APower-Hardware-in-the-LoopPla_ormwithRemoteDistribu8onCircuitCo-simula8on,”IEEETransac8onsonIndustrialElectronics,2015.

8

NREL-PNNLRemotePHILTestCase:Three-phaseInverter

•  IEEE8500-nodetestfeeder

-  One7kVAreal-inverteroutputscaledupto140kVAinGridLAB-Dsimula6on

-  Thishardwareinverterwasopera6nginVVC

-  AddedalargenumbersmallUPFinverters;combinedoutputof800kW

•  Cloudtransientwasimplementedbasedonhistoricalweatherdata

•  ThehardwareinverterwithVVCwascapableofmaintainingconstantvoltageonthesecondary

0

500

1000

1500

Irra

dian

ce(W

/m2 )

10

20

30

40

50

Phas

e A

Rea

l Pow

er(k

W)

-40

-20

0

20

Phas

e A

Rea

ctiv

e Po

wer

(kV

Ar)

12:35 12:40 12:45275

280

285

290

Phas

e A

|V| a

t PC

C(V

)

base PF=1.0 PF=0.81

12:35 12:40 12:45122

123

124

125

126

127

128

|V| m

ax

Maximum voltage magnitude on secondary system

no solar base casedistributed PF=1.0 solardistributed PF=1.0 solar and VVC solar

12:35 12:40 12:45122

123

124

125

126

127

128

|V|ma

x

Time

Maximum voltage magnitude on secondary system

T.Williams,J.Fuller,B.Palmin8er,B.Lundstrom,S.Chakraborty,“ExaminingSolarPVControlSystemswithaHardware-in-the-LoopPla_orm,”inIEEEPhotovoltaicSpecialistsConference(PVSC),Denver,CO,2014.

9

ADMSTestbed

•  NRELisestablishingana6onal,vendor-neutralAdvancedDistribu6onManagementSystem(ADMS)testbedtoaccelerateindustrydevelopmentandadop6onofADMScapabili6es

•  Enableu6litypartners,vendors,andresearcherstoevaluateexis6ngandfutureADMSusecasesandintegratewithHILequipment

10

IntegratedT+D

Timestep

Spatial


nation

state

metro

zipcode

feeder

device


Techno-Economic

Economic-focused

External Developer

NREL Tool

NREL Co-simulation

Simulation-only




RTDSRTDS


MAFRITNREL

eMegaSimOpal-RT

PSCA

DM

HI

FESTIVNREL


GridLAB-DPNNL



HEMS-simNREL

FESTIVNREL

TEADSNREL

REPRANREL


ReEDSNREL

RPMNREL

dSol

ar, d

Stor

age,

dW

ind

(NRE

L)


PSCA

DM

HI


RTDSRTDS


MAFRITNREL

eMegaSimOpal-RT

FESTIVNREL


GridLAB-DPNNL



HEMS-simNREL

FESTIVNREL

TEADSNREL

REPRANREL



ReEDSNREL

RPMNREL

dSol

ar, d

Stor

age,

dW

ind

(NRE

L)

IGMSNREL

IESMNRELTeDI

NREL


11

Smart Grid functionality restores the balance

Hydro power plants

Nuclear Power Plants

Natural Gas Generators

Transmission System

Distribution Substations

Customers

Distributed storage

Solar Farms

Wind Farms

IntegratedSimula6ontheEmergingGrid

Home Energy Storage

Energy Efficiency

PHEV

Rooftop Solar

Distributed wind

Commercial Customers

11

12

ExampleApplica6ons• Past:AnalyzedistributedPVsupportforgridopera6ons• SuccessfulMediumScaleRun(s):118Transmissionbuses,743Distribu6onFeeders(PNNLtaxonomy),>1Mtotalbuses,>600khomes.Highly-scalable

• Current:Wholesalepriceinterac6onofDERs• Future:

•  IntegrateCommunica6ons(ns-3,GMLCTDCproject)• Alterna6vemarket,DR,andservicearchitectures• Co-simula6onwithHardwareviaPHIL

Summary:Anext-genera6onanalysisframeworkforfull-scaleintegratedmarket+transmission+distribu6onsimula6onthatsupportsmillionsofhighlydistributedenergyresources.

End-to-EndT&DModelingCapability• detailedmul6-periodwholesalemarkets(includingLMPs)• generator/reservedispatch(AGC)• ACPowerflow(bulktransmission)• Fullunbalanced3-phpowerflowfor100s-1000sofdistribu6onfeeders

• Physicsbasedend-usemodelsofbuildingsandDERs• Semi-AutomatedimportfromPLEXOS,SynerGEE,&CyME

NREL’sIntegratedGridModelingSystem(IGMS)providesafirst-of-a-kindco-simula6onwithtransmission-levelmarkets,1000sofdistribu6onfeeders,and1MsofDERs

IntegratedT&DGridModelingSystem(IGMS)FESTIV:

ISO Markets, UC & AGC

MATPOWERTransmission/Bulk:

AC Powerfl w, Volt/VAr

FESTIV Runtime plug-in

Bus AggregatorBus Aggregator

Bus Aggregator

bus.py bus.py ...

ZMQ

MPI

IGMS-Interconnect

bus.pybus.py

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

Alte

rnat

e D

istri

butio

n M

odel

Tim

eser

ies,

etc

.

...

HTT

P

HTT

P

HTT

P

Scen

ario

Aut

omat

ion

ISO

Tran

smiss

ion

Distrib

ution

Build

ing

Applianc

e

IGMSReport:NREL/TP-5D00-65550

13

HowIGMSWorks

BigComputer

Co-simula8on

14

•  Mul6-Marketo  Day-AheadSecurity-ConstrainedUnitCommitment(Daily)

o  Real-6meSCUnitCommitment(Hourly)

o  Real-6meSCEconomicDispatch(5-min)

o  AGCreserves

•  US-style(currently):o  Nodalpriceso  CoupledReserveMarkets

FESTIV:ISO Markets, UC & AGC

Every4-60

sec(AGC

period) Every4-60sec(AGCperiod)

FESTIVTool:E.ElaandM.O’Malley,“StudyingtheVariabilityandUncertaintyImpactsofVariableGenera8onatMul8pleTimescales,”IEEETrans.PowerSyst.,vol.27,no.3,pp.1324–1333,Aug.2012.

15

•  Mul6-Market:o  Daily,Hourly,5-min,AGC

•  T:ACPowerflow(pos-seq,balanced)





Every4-60

sec(AGC


MATPOWERTool:Zimmerman,etal.,“MATPOWER:Steady-StateOpera8ons,Planning,andAnalysisToolsforPowerSystemsResearchandEduca8on,”IEEETransac8onsonPowerSystems,vol.26,no.1,pp.12–19,Feb.2011.

16



•  Nodal:o  Voltageo  Priceso  (Services)






Bus Aggregator

bus.py bus.py ...

ZMQ

MPI

IGMS-Interconnect

bus.pybus.py

Every4-60

sec(AGC


Bus.pyTool:T.Hansen,B.Palmin8er,S.Suryanarayanan,Maciejewski,andSiegel."Bus.py:AGridLAB-DCommunica8onInterfaceforSmartDistribu8onGridSimula8ons”,2015IEEEPESGeneralmee8ng

17




•  D:Powerflow(3ph,AC,unbalanced)

•  Physics:o  DERso  Load






Bus Aggregator

bus.py bus.py ...

ZMQ

MPI

IGMS-Interconnect

bus.pybus.py

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

Alte

rnat

e D

istri

butio

n M

odel

Tim

eser

ies,

etc

.

...

HTT

P

HTT

P

HTT

P

Every4-60

sec(AGC


GridLAB-DTool:Chassin,etal.,“GridLAB-D:AnAgent-BasedSimula8onFrameworkforSmartGrids,”JournalofAppliedMathema8cs,vol.2014,pp.1–12,2014.

18

•  Return:o  Powero  Reac6veo  (Bids)




•  D:Powerflow(3ph,AC,unbalanced)

•  Physics:o  DERso  Load






Bus Aggregator

bus.py bus.py ...

ZMQ

MPI

IGMS-Interconnect

bus.pybus.py

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

Alte

rnat

e D

istri

butio

n M

odel

Tim

eser

ies,

etc

.

...

HTT

P

HTT

P

HTT

P

Every4-60

sec(AGC



19






Bus Aggregator

bus.py bus.py ...

ZMQ

MPI

IGMS-Interconnect

bus.pybus.py

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

Alte

rnat

e D

istri

butio

n M

odel

Tim

eser

ies,

etc

.

...

HTT

P

HTT

P

HTT

P

Scen

ario

Aut

omat

ion

ISO

Tran

smiss

ion

Distrib

ution

Build

ing

Applianc

e

Every4-60

sec(AGC



20

Representa6veIGMSResults

Note:Projectsjuststar8ngnowwillbethefirsttouserealu8litydata

21

•  AdvancedDERInverters:newQdemandslargelymetlocally

•  AdvancedDERInverterscanhelpmanagetransmissionvoltages

SomeIni6al(Proof-of-Concept)Results

•  ImprovedPVforecast:quan6fyinterchangeerror&ACEimpacts

Time (1-minute increments)0 200 400 600 800 1000 1200 1400

Volta

ge (p

.u.)

0.94

0.95

0.96

0.98

1

1.02

1.04

1.05

1.06

Voltage envelope without advanced inverters

Voltage envelope with advanced inverters

SolarPenetration(energy)

Visibility(Forecast)

ProductionCost

$1000s/day

CPS2Violations AACEE ACEStd.

Dev.

9% none9% persistence9% perfect

7,0125,636

InfeasibleRTSCEDat10amsimulationtime-

-25%


-7%


-4%

InfeasibleRTSCEDat10amsimulationtime

14% none14% persistence14% perfect

6,8336,5585,654

--10%-22%

--2%-23%

--1%-13% OnthePathtoSunShot-Distribu8on:NREL/TP-5D00-65331

22

BulkImpactsofDERs

•  HVACandHotWatercontrollersinGridLAB-D

•  System-widedemandimpact

See:Palmin8eretal.IEEETransac8onsonSmartGrid(ToAppear)

23

GeneralObserva6onsonLinkingModels

24

•  Lotsofefforthasgoneinto(sub)domain-specifictools.o  (Sousethem)o  Trustedbystakeholderso  Con6nuetoimprove

•  Allowsfocusonthe“glue-ware”o  Fastero  Manyframeworks

•  EncouragesModularityo  Swap/addmodelsasneeded

1.Co-simula6onisgreatforleveragingexis6ngtools

hop://legomyphoto.wordpress.com/


PFLOWTransmission

Powerfl w

FESTIV plug-in PFlow adapter


Bus Aggregator

bus.py bus.py ...

ZMQ

MPI

IGMS-Interconnect

bus.pybus.py

ZMQ ZMQ

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

Alte

rnat

e D

istri

butio

n M

odel

Tim

eser

ies,

etc

.

...

HTT

P

HTT

P

HTT

P

Scen

ario

Aut

omat

ion

ISO

Tran

smiss

ion

Distrib

ution

Build

ing

Applianc

e






Bus Aggregator

bus.py bus.py ...

ZMQ

MPI

IGMS-Interconnect

bus.pybus.py

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

GR

IDLa

b-D

Dis

tribu

tion

Pow

erfl

w,

Hom

e &

Appl

ianc

e Ph

ysic

s

Alte

rnat

e D

istri

butio

n M

odel

Tim

eser

ies,

etc

....

HTT

P

HTT

P

HTT

P

Scen

ario

Aut

omat

ion

ISO

Tran

smiss

ion

Distrib

ution

Build

ing

Applianc

e

B.Palmin6er,etal.,“Experiences…withtheIntegratedGridModelingSystem(IGMS),”inPowerSystemsComputa8onConference(PSCC’16),Genoa,Italy,2016.

25

2.It’snotjustthetool:RemembertheRestoftheWorkflow

Okenthesimula8onitselfisthe“easy”part,comparedtoset-up,outputprocessing,andanalysis

ScenariosOptimizationUncertainty

UsableInputData

OutputVisualize

SimulationToolsSimulation

ToolsSimulationTools

Questions

RawData Answers


IGMS-InputDataConversion

Transmission:PLEXOStoFESTIV–withRPM

0"

200"

400"

600"

800"

1000"

1200"

1400"

1600"

0:00" 3:00" 6:00" 9:00" 12:00" 15:00" 18:00" 21:00" 0:00"

Total&G

enera+

on&(M

W)&

Fes/v1IGMS"Gen"Fes/v1CPLEX"Gen"Plexos"Gen"Fes/v"Gen"

Distribu6on:SynerGEEandCYMEtoGridLAB-D

POC:JulietaGiraldez


27

IGMS-Popula6ngFeederswithHouses&PV

Scenario sim start: 4/16/2020 sim duration: 1 d sim timestep: 1 min

Transmission•  FESTIVcase•  IGMS-FESTIV

modelrulesandconfigura6on

•  Startup.matfile

Distribu6on•  Assignfeeder

modelstonodes•  glmgenop6ons

forpopula6ngGridLAB-D

•  LHSsampling

bus.pysetupMultiNodeBus GridlabBus ConstantBus FileBus

CorefeederprocessingbuiltonevolvedformofOpenModelingFramework IGMSReport:NREL/TP-5D00-65550

28

IGMS-OutputProcessing


1.o _________ 1_oa_d .... re_a_1_s_ta_c_k_fo_r_i_g_m_s _______ _ load distribution of sing le bus feeders

E 0.8 _ _J

0.6

0.4

0.2

0.0 ~~~~~~~~~~~~~==::::::] 0 5000 10000 15000 20000 25000 30000 35000 40000 45000

time(s)

Load and Voltage o~----~-----~----~-----~ 0 5 10 15 20

The r 856 are colored by their maximum change in voltage, wnere mirKer colors have a greater change.

0

"' Q 120

110

100

90

BO

70

60

50

40

30

20

10

1.00

0.98

0.96

0.94

0.92

0.90

0.88

0.86

0.84

0.82

Q) 0 0, 0, 0, 0 48 =-0 >

46

44

42

40

38

36

34

32

IEEE 118-bus Voltage Contour, t• 2020-04-16 17:20:00

0.80

Thu 1603 AM 06 AM 09 AM 12 PM 03 PM 06 PM 09 PM Fri 17 Thu 1603 AM 06 AM 09 AM 12 PM 03 PM 06 PM 09 PM Fri 17

1.100

l.07S

l .OSO

l .02S

, .. 1.oooi,

i

0.97S

29

•  Co-simula6onperspec6ve:enablesmodelswapping•  Also:Well-definedAPIadvantages:

o  Mul6pledeveloperssimultaneously– Easiermerginginversioncontrol(youareusingsofwareversioncontrol,right?GITisgreat)

o  Refinecomponentsseparately•  Andkey:TESTING

o  Asynchronousdevelopment

o  Isolateproblems

3.ModularDesignalsoSimplifiesComplexDevelopment

FakeTool FakeTool

RealModel FakeTool

RealModel RealModel


30

4.BigModelscaninformsmallermodels

IGMSvsSeparateTools:LargestdifferenceseparatevsT+D:constantdistribu6onfactors

Tradi6onalTransmissionModels:

WithIGMS:VoltageErrors:Low

RealPowerErrors:High

Palmin8eretal.“IntegratedGridModelingSystem…”IEEETransac8onsonSmartGrid(ToAppear)andPalmin8eretal.NREL/TP-5D00-65550,Jan.2016.

31

Futuredirec6onsforT+D

•  EnhancedT&DeconomicanalysisinIGMSo  Retail-Wholesalemarketinterac6onso  DLMPdevelopment

•  Real-worldpartnersandvalida6ono  SuNLaMPT+DToolswithArgonneNa6onalLab

•  T+D+…Comms,Loads,Markets,etc.o  DoEGridModerniza6onT+D+C:withPNNL,LLNL,etal.o  Opportunis6cHybridCommunica6onSuNLaMP(Bri-MathiasHodge)

•  Marketinterac6onsofDR:“Prosumeraspricemaker”o  IGMS+IESM

•  PowerHardware-in-the-Loopo  ADMStestbed(Simulatepowersystem)o  ESIFPowerGridHub

•  PartnershipswithNRELAnalysisGroupo  high-distributedenergyfuturesstudyo  Futureelectricitysystemanalysis

32

FullReferencesIntegratedGridModeingSystem(IGMS)forT+D•  B.Palmin6er,E.Hale,B.-M.Hodge,K.Baker,andT.Hansen,“Experiencesintegra6ngtransmissionand

distribu6onsimula6onsforDERswiththeIntegratedGridModelingSystem(IGMS),”inProceedingsofthe19thPowerSystemsComputa8onConference(PSCC’16),Genoa,Italy,2016.

•  B.Palmin6er,E.Hale,T.Hansen,W.Jones,D.Biagioni,H.Sorensen,andB.-M.Hodge,“IGMS:AnIntegratedISO-to-ApplianceScaleGridModelingSystem,”IEEETransac6onsonSmartGrid,SpecialIssueonHighPerformanceCompu6ng(HPC)Applica6onsforaMoreResilientandEfficientPowerGrid,(InReview)

•  B.Palmin6er,E.Hale,T.Hansen,W.Jones,D.Biagioni,K.Baker,H.Wu,J.Giraldez,H.Sorensen,M.Lunacek,N.Merket,J.Jorgenson,andB.-M.Hodge,“IntegratedDistribu6on-TransmissionAnalysisforVeryHighPenetra6onSolarPV(FinalTechnicalReport),”Na6onalRenewableEnergyLaboratory,Golden,CO,NREL/TP-5D00-65550,Jan.2016.

•  B.Palmin6er,“TheIntegratedGridModelingSystem(IGMS)forCombinedTransmissionandDistribu6onSimula6on,”presentedatthePowerandEnergySocietyGeneralMee6ng,Denver,CO,29-Jul-2015.hop://www.nrel.gov/docs/fy16os6/65552.pdf

•  B.Palmin6er,R.Broderick,B.Mather,M.Coddington,K.Baker,F.Ding,M.Reno,M.Lave,andA.Bharatkumar,“OnthePathtoSunShot:EmergingIssuesandChallengesinIntegra6ngSolarwiththeDistribu6onSystem,”Na6onalRenewableEnergyLaboratory,Golden,CO,NREL/TP-5D00-65331,May2016.

•  T.M.Hansen,R.Kadavil,B.Palmin6er,S.Suryanarayanan,A.A.Maciejewski,H.J.Siegel,E.K.P.Chong,andE.Hale,“EnablingSmartGridCosimula6onStudies:RapidDesignandDevelopmentoftheTechnologiesandControls,”IEEEElectrifica8onMagazine,vol.4,no.1,pp.25–32,Mar.2016.

BonusExamples:•  B.Palmin6erandM.D.Webster,“ImpactofOpera6onalFlexibilityonElectricityGenera6onPlanningWith

RenewableandCarbonTargets,”IEEETransac6onsonSustainableEnergy,vol.7,no.2,pp.672–684,.2016.•  B.Palmin6er,B.Lundstrom,S.Chakraborty,T.Williams,“APower-Hardware-in-the-LoopPlawormwith

RemoteDistribu6onCircuitCo-simula6on,”IEEETransac6onsonIndustrialElectronics,2015.

[email protected]

national laboratory oft e U.S.

integrated models for transmission & distribuon plus

Documents