Grid Simulation And Scenario Planning

INL Grid Simulation and ScenarioPlanning Capabilitieswww.inl.govPower & Energy SystemsJune 9, 2017Rob Hovsapian, Ph.D.Department Manager, Power & Energy SystemsIdaho National Laboratory

INL Real Time Energy Systems Laboratory’sDemonstration Complex and Test Bed Power and Energy Integration TestEnvironmentEMTS / RTDSSimulator– Real Time Emulation Test Bed hardware-in-the-loop capabilities fordemonstrations and dynamic analysis Power system devicesIntegration with HESControl and integration strategiesCoupling with energy storageFuel Cell2

Real-Time Hardware-In-the-Loop Modeling andTesting EnvironmentReal TimeDigitalAt-scaleInteg.Eng.SimulatorV&VTest (RTDS)EnvironmentActual Power GridSimulated Larger Grid(regional or national )Grid-In-the-LoopHardware-In-the-LoopHardware in LoopVariable EnergyGenerationDevice(s)RenewableEnergyFC/ ElectrolyzerPEVConventional ware-In-the-LoopVirtual ComponentReal ComponentDevice /ControllercontrollerInSimulationthe loop/(SCADA)EnergyVirtual ComponentOperationDataOperationPEV, FC,DataElec. Wind,(Wind, Solar, Hydro)Solar, Hydro)ManagementSimulated DataActual DataController-Hardware-In-the-Loop3

The Energy Demonstration Test BedNRELVariableGeneration DataPNNLWesternGrid DataHydroSolar & OtherPower torWind Farm OutputWater Power OutputNuclear Power Plant OutputSolar and Other OutputsVariable and ConstantGeneration ResourcesPower ConverterInterfacing GridExperimental GridVariable LoadingH2ProductionSecure power system 60-mile, dual-fed, 138-kVtransmission loop 7 distribution substations 3 commercial feedsINLPower GridRingEnergyStorageSupporting PowerSinks and StorageCITRICScovilleINL Isolated Test LoopReal-time digitalsimulation for powersystem hardware-inthe-loop testingReal-time grid monitoringand control throughcentralized SCADAoperations centerMFCPad

Integrated Grid Environment - Electrical /Mechanical / Thermal Co-SimulationRTDS/INLRTDS/ (Other Sites)Power System Modelsfinite state machineElectrolyzerFuel CellHT – FC / ElectrolyzerHydropower Plant ModelsThermal Power Plant Models Energy Storage ModelsV2G

INL’s Current Projects Related to GridSimulation and Scenario Planning

Real Time Thermal Electrical Co-simulationRT co-simulation of electrical-thermal-mechanical systems with physicsbased models7

Multi-time Scale of Energy Storage Devices8

GMLC 1.3.9 – Smart Reconfiguration of Idaho FallsPower Distribution Network NS3-based communication layer is emulated for co-simulation of powersystems and control/communication network between RT models andhardware devicesCont rolsI nt erfaceV,I - AMPsI nt erfaceNS3- based Com m unicat ion LayerHardware Prot ect ion RelaysCont roller HI LNS3 communication layer-based setup for RT HIL Testing9

CEC Microgrid Project – Blue LakeRancheria, CA PG&E Grid Black Start with Diesel generator Automatic reconnect to grid when islanded with Diesel generator Transition to Islanded Operations with MGMS UnresponsiveMicrogridWent Live04/28/2017Fig. 5 BLR Microgrid Setup and HIL Testing

Dynamic Modeling and Validation of Electrolyzersin Real Time Grid Simulation11

Frequency Support by Multiple Electrolyzers59.99259.99659.992Local Frequency (Hz)59.97959.99259.99659.97959.992NODE 39Multiple electrolyzers controlled byFront End Controller can enhanceoverall grid stability by limitingfrequency excursions59.992NODE 4059.99759.97959.992NODE 32Fault location: Node 39Fault type: Three phase balanceFault duration: 0.1 seconds12

Variability of Renewable / HydrogenRefueling Stations Renewable Energy sources such as wind and solar demonstrate high degreeof time dependent variability i.e., seconds to minutes to days Electrolyzers have an innate capability to respond in seconds to follow controlset points How can electrolyzers offset the variability observed by the power?– Grids expected predictable and non-varying generation sources– Hydrogen demands per day for different years are used as a constraint13

2018 Case with 7,200 FCEVsReal Power in MW Objective: Offset time-dependent,aggregated variability of solar andwind power using electrolysis Total of 13 MW electrolyzer plant isused for this example 2018 test case projections fromARB on vehicle fuel use to generate1,800 kg/day of hydrogen for 7,200FCEVs Approximate fuel dispensed inSanta Clara, Sacramento, SanFrancisco, Marin, Contra Cost andAlameda county Total energy consumed to generatethis hydrogen demand 90.28MWh/dayTotal Wind and Solar Generation14121086420051015Time of the day2014

Wind, Solar, and Electrolysis Advanced control of a 13 MWelectrolysis plant to offset variabilityof wind and solar power A fixed and predictable powerinjected into the grid from solarand wind plant due tocoordinated operation withelectrolyzersAggregate Feed into the Grid (2018)123102.582Real Power in MWReal Power in MWElectrolyzer performance to produce 1800 kg/day61.54120.500051015Time of the day20051015Time of the day20

INL’s Capabilities Related to Related toGrid Simulation and Scenario Planning16

Integrated Multi-time Scale Real-Time Simulation Test-bedI nt egrat ed Mult i- t im escale Real- t im e Sim ulat ion Test bedCont roller HI Lunder TestPower HI LDat a Acquisit ionHardwareDevices under TestPower Syst em under TestI nt erfaceCont rolsSim ulat ion t im e st ep 50μsCom m unicat ion Layer Em ulat ionI nt erfaceI nt erfaceCont rolsCont rolsTherm al ( m s t o s) and Mechanical ( s t o m ins)Real- t im e Co- sim ulat iont im e st ep 500nsWide- bandgapPower Convert erPower Elect ronics Co- sim ulat ion17

Real-time Simulation with Communication EmulatorsWith the integration of modern and legacy utility devices, it is imperativeto co-simulate communication with power system ableEnergy500 nsMicrogridsDemandResponseINL Network – 500ns

Distributed Architecture for Simulation, Testingand Visualization using HIL Power SystemSimulated in VirtualReal-time PlatformPowerSystemNode-1Data linkPowerSystemNode-2Graphical work InstructionOperator TrainingReal Time SituationalAwareness for GridOperatorVisualization facility at INL*COMCOMPowerSystemNode-nCOMSystem Under Test(Power Hardware)Communication LayerVirtual RealTime PowerSystemsCOM(multi-protocol, multitopology)Communication network 1-10Gb/s*Actual Hardware Power SystemsSource: Center for Advanced Energy Studies at Idaho National Laboratory

Scalable Hardware-In-the-Loop (HIL) Co-simulationPowerSystemHIL DevicesAdvancedTelemetry100 microcontrollerbased cardsprogrammed aspower systemhardware nodes(Validated againstPHIL experiments)Communication NetworkPotential scenarios testing Power System Issues Communication Issues Interoperability Data Latency- Electrolyzer/Fuel Cells- Electric Vehicles Operations under Harsh Environments Degraded Conditions Survivability operations

Real-time Connectivity Across Organizations RT-Super Lab for the Futuristic Grids Collaboration with Academia, Research Labs,UtilitiesReal-time Connectivity withRTDS, Opal-RT, TyphoonHIL, and other NovelHardware Assets for LargeScale Testing

Multi-Lab Co-simulation and (P)HIL- Grid TestingMMC-basedMVDC Test BedController-Inthe-Loop22 kV55MVA220 kV63MVAWestern SystemCoordinating Council(WSCC)9-bus system approximation22 kVEuropean HV transmissionnetwork benchmark (CIGRÉ)63MVA22 kVDistribution system –a portion of Turin City,Italy22

Thank You&QuestionsRob Hovsapianrob.hovsapian@inl.gov23

NS3sed communication layer is emulated for co-ba -simulation of power systems and control/communication network between RT models and hardware devices . NS3-based Communication Layer Controls Interface. Hardware Protection Relays. Controller HIL Interface. V,I-AMPs. NS3 communication l