Micro-Synchrophasors for Distribuon Systems · Micro-Synchrophasors for Distribuon Systems GRID...

Micro-SynchrophasorsforDistribu4onSystems

GRIDDATAMee4ngSanDiego,January27,2017

Dr.Alexandra(Sascha)vonMeier

Director,ElectricGridResearch,CaliforniaIns6tuteforEnergyandEnvironmentAdjunctProfessor,Dept.ofElectricalEngineeringandComputerScience

UniversityofCalifornia,Berkeley

SeanMurphyChiefScien6st

PingThings

Micro-synchrophasorsforDistribu4onSystems

Three-year,$4.4MARPA-EOPEN2012project(2013-2016)to•  developanetworkofhigh-precisionphasormeasurementunits(µPMUs)

andhigh-speeddatabase(BTrDB)•  exploreapplica6onsofµPMUdatafordistribu6onsystemstoimprove

opera6ons,increasereliability,andenableintegra6onofrenewablesandotherdistributedresources

•  evaluatetherequirementsforµPMUdatatosupportspecificdiagnos6candcontrolapplica6ons

EXISTINGPMUNETWORKTransmissionSystem

μPMUNETWORKDistribu6onSystem

BTrDBserver

µPMU

µPMU

µPMU

µPMU

µPMU

(YourplaZormhere)

Micro-synchrophasornetworkconcept:Createvisibilityfordistribu4oncircuitsbehindthesubsta4ontosupportac4vemanagementandintegra4onofdistributedresources

ARPA-EµPMUProjectFieldinstalla4ons:

UCBerkeley/LBNLSouthernCaliforniaEdisonRiversidePublicU6li6es

AlabamaPower(SouthernCo.)GeorgiaPower(SouthernCo.)TennesseeValleyAuthorityPacificGas&ElectricCo.

Illustra4on:MeasuredphaseshiZalong12kVdistribu4oncircuit

voltagephaseangledifferencebetweenPVarrayandsubsta8on

currentinjectedbyPVarray

Usecaseexample:DiagnosecauseofDGunittrips

PVarraytrip

voltagesag

causedbyphaseB-Cfault(palmfrondcontact)downthefeeder

Tapchangeoccursover~2cyclesGraphshowsindividual120-Hzsamples

Tapchangeratsubsta8ontransformerstepsvoltageupanddownasloadchangesoverthecourseoftheday

Usecase:Detectnormalandmis-opera4onofequipment

Usecase:Detectnormalandmis-opera4onofequipment

Example:Anomalyintapchangesignaturegivesearlywarningoftransformeragingorincipientfailure

Curiousvoltagesagcharacteris8callyfollowstapchangeopera8on

Keyresults•  µPMUinstrumentsmeetandexceedprojectgoals•  Projecthasgathered100+TBofdistribu6ongriddataatunprecedentedfidelity

andresolu6on•  BTrDB6me-seriesstorageandqueryprocessingperforms1400xfasterthan

leadingcommercialorresearchsolu6on,withunprecedentedstorageefficiency–  plusuniqueaddi6onalfunc6onality:fastchangeset,sta6s6calsummary,consistent

versioningofdata&dataprocessing

•  StrengthofµPMU-baseddiagnos6csderivesfromthe6medimensionanduniqueanaly6cframework:-  measurementprecision,temporalresolu6on,precisesynchroniza6on(PMU)-  dis6llateframework,exponen6altreesearchesatmul6ple6mescales(general)-  interac6veanaly6cs&visualiza6on(general)

•  Measurementshaveansweredcri6calearlyresearchques6onsaboutphasordataanddistribu6ongrids,whileraisingmanymore

•  µPMUtechnologyhasmetwithsomeinterestintheu6lityindustry;addi6onalworkthroughtheresearchprojectwillhelpapplica6onsbedevelopedfurtherbytheprivatesector.

Micro-synchrophasorsforDistribu4onSystems,Part2

18-month,$2MPlus-Upextensionproject2017-2018Collabora6onwiththreecommercializa6onpartnerswithdifferentapplica6onfoci:

SmarterGridSolu6ons:Planning,diagnos8cs&mi8ga8onforhigh-penetra8onPVdistribu8on

DoosanGridTech(formerly1EnergySystems):Informa8oninfrastructurefordistribu8onmonitoringandcontrol

PingThings:StreamanalysissoMwareforreal-8megriddata,T&Ddisturbanceeventdetec8onandanalysis

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ProjectObjec4ves:•  DeploySGSAc6veNetwork

ManagementDERMSplaZorminoneRPUtrialcircuitloca6on

•  UseµPMUandotheru6litydatatoinformadvancedgirdautoma6onandcontrolapplica6ons

•  EvaluatethebenefitsµPMUsbringtoplanningandreal-6mecontrolcomparedtotradi6onalgridmeasurements

“Planning,Diagnos8csandMi8ga8onforHigh-Penetra8onPVDistribu8on”

Partner:RiversidePublicU6li6es;TaskleadLBNL

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ValueProposi4on:•  ManagegridswithhighDER

penetra6onsclosertotheirlimits,usingempiricaldataintegratedintothediagnos6c,planningandopera6onalprocess

•  Defertheneedforgridreinforcementscausedbythegrowthofdistributedsolar

“Planning,Diagnos8csandMi8ga8onforHigh-Penetra8onPVDistribu8on”

“Informa8onInfrastructureforDistribu8onMonitoringandControl”Prospec6veu6litypartner:Aus6nEnergy;TaskleadCIEEProjectObjec4ves:•  IntegrateµPMUdatawithDoosanGridTech’sIntelligentController

(DG-IC)•  Buildalocalinforma6oninfrastructuretoenablemonitoringand

controlofcircuitperformanceonaDER-intensivecircuit,includingsolarPVandbaherystorage

•  CreateadatabackbonetoenableDERcontrolschemesonafeederthatcanscaleacrossdevicetypes

“Informa8onInfrastructureforDistribu8onMonitoringandControl”ValueProposi4on:•  Intelligentrecruitmentofdistributedresources,includingenergystorage

systems(ESS),maximizesthevalueoftheseassets•  Extendslifeofotheru6lityassets,suchasvoltageregula6ondevices•  Improvepowerqualityforthecustomer•  AssurethatDERsa6sfieslocaldistribu6onconstraintswhileserving

needsofthetransmission6er

PingThings+µPMU“StreamAnalysisSoMwareforReal-TimeGridData”Prospec6veu6litypartner:PG&E;TaskleadCIEEProjectObjec4ves:•  IntegrateµPMUdataintoStreamAnalysissoiware•  Demonstrateapplica6onofStreamAnalysisacrosstransmissionand

distribu6onsystems•  Studyspecificusecaseofgeomagne6cdisturbances(GMD)andtheir

impacts

PingThings+µPMU“StreamAnalysisSoMwareforReal-TimeGridData”

ValueProposi4on:•  Informpreven6vemeasurestominimizecostlydamagesfromGMD

(es6mated8-10B$/yr)•  Detec6onofanomaliessuchasvoltagesagssupportssitua6onal

awareness•  Beherandfasterforensicanalysisofanomaliessaves6me,supports

mi6ga6onandul6matelypreven6on•  Understandinganomaliesassociatedwithvariableanddistributed

genera6onsupportsappropriatemeasuresbyresponsibleparty,whetheru6lityorDGowner

Cross-cu^ngac4vi4esrelevanttoGRIDDATA

•  FurtherdevelopmentonBerkeleyTreeDatabase

(BTrDB)•  InterfacebetweenBTrDBandGridLAB-D•  LBNLPowerDataportal

Other Services

Other Services

Other Services

LocalBuffer

LocalBuffer

LocalBuffer

LocalBuffer...

Chunk Loader

Field Datacenter / Cloud Clients

BTrDBCluster

Distillate Framework Cluster

PlottingService

HTTP

MATLAB

IPython

etc ...

JSON / CSV

Analytics with 3rd party tools

Interactive visualization

Wired

Event Detection Service

Other Services

webapp

PMU

PMU

PMU

PMU

Internet

LTE modem

BerkeleyTreeDatabase(BTrDB)

ARPA-Eresearchprojectconfigura6on:ca.40µPMUssending120HzdataviaEthernetor3G/4Gwireless,12streamsperdevice(voltageandcurrentmagnitude&phaseangle)

MichaelAndersen,UCBerkeley

BerkeleyTreeDatabase(BTrDB)resolvesthedownsidesofstoringandu4lizinglarge,high-resolu4on4me-seriesdatastreams•  noneedtocompromisebetweendatacon6nuity,resolu6on,ease

ofaccess•  extremelyfastsearches(~200msforindividualsampleswithin

monthsof120-Hzdata)•  performsonlinecomputa6onofdatadis6llatestreams(e.g.power,

frequency,ratesofchange,differencesbetweenquan66es)•  dataavailableforviewinginploheranddownloadablethroughAPI

forexternalanaly6capplica6ons•  opensourcecodeavailableongithub

Transforma4veAdvancesinBTrDB

•  Dis6lla6oninfrastructurewithextremelyfastchangesetiden6fica6on–  Operatereal-6meonmanystreams,withholes,out-of-order,etc.

•  On-the-Flysta6s6calsummariesoveramul6-resolu6onstore

•  Mul6-resolu6onsearchandprocess–  Find‘needle’eventsinimmensehaystacksinstantly–  Drilldownexponen6allytoanalyze

BTrDB+GridLAB-D•  GridLAB-Dplayerobjectsenableexternal6me-seriesdatato

beusedinsimula6ons•  BTrDB+GridLAB-Dpythonscriptexposes6me-seriesdatain

GridLAB-Dplayerobjectformatinaspecialbuffer(namedpipeorFIFO)

•  GridLAB-Dopensbufferasifitwasaregularplayerfile•  Aseach6mestampisreadbyGridLAB-D,pythonscript

retrievesnext6mestampfromBTrDBandwritestothebuffer•  Pythonscriptcanvary6mestampresolu6on

GridLAB-DModel

Valida6on

GridLAB-DWhat-ifscenariosgivesimulated

networkbehavior

Newdataanalysisandcontrolschemes

Real-worldnetwork

measurement

BTrDBSynchrophasorandTelemetry

data

BTrDB+GridLAB-D

ReadtheARPA-EProjectImpactSheetathhp://beci.berkeley.edu/wp-content/uploads/2016/12/UCB-External-Project-Impact-Sheet_11102016.pdfPeruseliveandarchivalµPMUdataathhp://plot.upmu.organdhhp://powerdata.lbl.gov/

LearnaboutµPMUhardwareathhp://www.powersensorsltd.com/PQube3.php

Par6cipateintheNASPIDistribu6onTaskTeam(DisTT)www.naspi.org

GostraighttothesourceforBTrDBathhps://github.com/SoiwareDefinedBuildings/btrdb

Contactmewithques6onsatvonmeier@berkeley.edu

Resources

●  An internet scale, real time stream analytics company anchored in data science

●  Privately held with General Electric as one of several investors

●  Member, active participant of IEEE, CIGRE, JSIS, NASPI…

●  Currently working with utility clients in the Eastern Interconnect and WECC

●  ARPA-E Grant participant working on µPMU analytics with LBNL, CIEE, UC Berkeley

Internet Scale, Real Time Stream Analytics

@pingthingsIO

Operational PMU Data Coverage

Tsunami

A cloud-based application that simulates global PMU data volume in real time.

Simulates

•  thousands of PMUs and

•  tens of thousands of data streams

Cloud-based, scalable

Cost effective to operate

Test framework for other products including data ingest engine

BTrDB Advancements

ISO NE

•  October 2015 - July 2016

•  All available PMUs

•  891 time series

•  577,368,000,000 data points

PG&E

•  Core component to real-time data quality assessment tool

•  Deployment in utility est. Feb 2017

Data Quality Assurance

•  Real time data quality monitoring

•  Monitors multiple aspects of data quality

•  Web-based or off-line reporting

•  Text/email real time alerts

•  Designed to help identify location and root cause of the data problem with machine learning

Examining GMD Effects on Distribution