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INL Grid Simulation and Scenario Planning Capabilities

Power & Energy Systems

June 9, 2017

Rob Hovsapian, Ph.D. Department Manager, Power & Energy Systems

Idaho National Laboratory

INL Real Time Energy Systems Laboratory’s Demonstration Complex and Test Bed

• Power and Energy Integration Test Environment

– Real Time Emulation Test Bed - hardware-in-the-loop capabilities for demonstrations and dynamic analysis

• Power system devices • Integration with HES • Control and integration strategies • Coupling with energy storage

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Fuel Cell

EMTS / RTDS Simulator

Real-Time Hardware-In-the-Loop Modeling and Testing Environment

Real Time Digital Simulator (RTDS)

Hardware in LoopVariable Energy

Generation Device(s)

Real Component

Renewable Energy

Virtual Component

Conventional Power

Generation

Virtual Component

Operation Data

(Wind, Solar, Hydro)

Actual Data

Simulation /Controller In the loop

(SCADA)

Simulated Data

Actual Power Grid Simulated Larger Grid (regional or national )

Grid-In-the-Loop

Controller-Hardware-In-the-Loop

Hardware-In-the-Loop

Power-Hardware-In-the-Loop

At-scale Integ. Eng. V&V

Test Environment

FC / Electrolyzer PEV

Device controller /

Energy Management

Conventional & RE

Generation

Operation Data PEV, FC, Elec. Wind,

Solar, Hydro)

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The Energy Demonstration Test Bed

UtilityInterface

PNNLWestern Grid Data

RTSimulator

NRELVariable

Generation Data

Wind Farm OutputWater Power OutputNuclear Power Plant OutputSolar and Other Outputs

Wind

Hydro

Solar & Other ORNLHydro Data

H2Production

Energy Storage

Variable and ConstantGeneration Resources

Variable Loading

Experimental GridInterfacing GridSupporting PowerSinks and Storage

Power Converter

Power Converter

Real-time grid monitoring and control through centralized SCADA operations center

INL Power Grid

Ring

INL Isolated Test Loop

CITRIC

MFC Pad

Scoville

Secure power system • 60-mile, dual-fed, 138-kV

transmission loop • 7 distribution substations • 3 commercial feeds

Real-time digital simulation for power system hardware-in-the-loop testing

Integrated Grid Environment - Electrical / Mechanical / Thermal Co-Simulation

RTDS/INL

Thermal Power Plant Models

Hydropower Plant Models

Energy Storage Models

finite state machine

Power System Models

RTDS/ (Other Sites)

Fuel Cell

Electrolyzer

HT – FC / Electrolyzer

V2G

INL’s Current Projects Related to Grid Simulation and Scenario Planning

Real Time Thermal Electrical Co-simulation

RT co-simulation of electrical-thermal-mechanical systems with physics based models 7

Multi-time Scale of Energy Storage Devices

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GMLC 1.3.9 – Smart Reconfiguration of Idaho Falls Power Distribution Network

• NS3-based communication layer is emulated for co-simulation of power systems and control/communication network between RT models and hardware devices

NS3-based Communicat ion Layer

Cont rols

I nterface

Cont roller HI LHardware Protect ion Relays

I nterface

V,I -AMPs

NS3 communication layer-based setup for RT HIL Testing 9

CEC Microgrid Project – Blue Lake Rancheria, CA PG&E Grid

• Black Start with Diesel generator • Automatic reconnect to grid when islanded with Diesel generator • Transition to Islanded Operations with MGMS Unresponsive

Microgrid Went Live

04/28/2017

Fig. 5 BLR Microgrid Setup and HIL Testing

Dynamic Modeling and Validation of Electrolyzers in Real Time Grid Simulation

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Multiple electrolyzers controlled by Front End Controller can enhance overall grid stability by limiting frequency excursions

59.992

59.979

Fault location: Node 39 Fault type: Three phase balance Fault duration: 0.1 seconds

59.992

59.992

59.979

59.979

59.996

59.996

59.997

59.992

59.992

59.992

Loca

l Fre

quen

cy (H

z)

NODE 39

NODE 40

NODE 32

Frequency Support by Multiple Electrolyzers

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Variability of Renewable / Hydrogen Refueling Stations • Renewable Energy sources such as wind and solar demonstrate high degree

of time dependent variability i.e., seconds to minutes to days… • Electrolyzers have an innate capability to respond in seconds to follow control

set 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 constraint

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• Objective: Offset time-dependent, aggregated variability of solar and wind power using electrolysis

• Total of 13 MW electrolyzer plant is used for this example

• 2018 test case projections from ARB on vehicle fuel use to generate 1,800 kg/day of hydrogen for 7,200 FCEVs

• Approximate fuel dispensed in Santa Clara, Sacramento, San Francisco, Marin, Contra Cost and Alameda county

• Total energy consumed to generate this hydrogen demand 90.28 MWh/day

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2

4

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10

12

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0 5 10 15 20

Rea

l Pow

er in

MW

Time of the day

Total Wind and Solar Generation

2018 Case with 7,200 FCEVs

Wind, Solar, and Electrolysis • Advanced control of a 13 MW

electrolysis plant to offset variability of wind and solar power

• A fixed and predictable power injected into the grid from solar and wind plant due to coordinated operation with electrolyzers

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2

4

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0 5 10 15 20

Rea

l Pow

er in

MW

Time of the day

Electrolyzer performance to produce 1800 kg/day

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0.5

1

1.5

2

2.5

3

0 5 10 15 20

Rea

l Pow

er in

MW

Time of the day

Aggregate Feed into the Grid (2018)

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INL’s Capabilities Related to Related to Grid Simulation and Scenario Planning

Integrated Multi-time Scale Real-Time Simulation Test-bed

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Thermal (ms to s) and Mechanical (s to m ins) Real- t ime Co-simulat ion

Sim ulat ion t im e step 50μs

Power System under Test

Com m unicat ion Layer Em ulat ion

I ntegrated Mult i- t im escale Real- t im e Sim ulat ion Testbed

t im e step ~ 500ns

I nterface

Cont rolsWide-bandgap

Power Converter

Cont rolsI nterfacePower HI L

Cont roller HI Lunder Test

I nterfaceCont rols

Hardware Devices under Test

Data Acquisit ion

Power Elect ronics Co-simulat ion

Utility Devices

Renewable

Energy

Microgrids

Demand Respons

e

Controllable Grid

Emulator

INL Network – 500ns

500 ns

Real-time Simulation with Communication Emulators With the integration of modern and legacy utility devices, it is imperative to co-simulate communication with power system devices

Distributed Architecture for Simulation, Testing and Visualization using HIL

Communication Layer (multi-protocol, multi-

topology)

Power System Node-1

Power System Node-2

Power System Node-n

Virtual Real Time Power

Systems

Visualization facility at INL*

* Source: Center for Advanced Energy Studies at Idaho National Laboratory

Data link

System Under Test (Power Hardware)

COM

Actual Hardware Power Systems

CO

M

COM

COM Communication network 1-10Gb/s

• Graphical work Instruction • Operator Training • Real Time Situational

Awareness for Grid Operator

• Power System Simulated in Virtual Real-time Platform

Scalable Hardware-In-the-Loop (HIL) Co-simulation

HIL Devices

- Electrolyzer/Fuel Cells - Electric Vehicles

Power System

Communication Network

• Power System Issues • Communication Issues • Interoperability • Data Latency

• Operations under • Harsh Environments • Degraded Conditions

• Survivability operations

Potential scenarios testing

100+ microcontroller-based cards programmed as power system hardware nodes

(Validated against PHIL experiments)

Advanced Telemetry

Real-time Connectivity Across Organizations • RT-Super Lab for the Futuristic Grids • Collaboration with Academia, Research Labs,

Utilities Real-time Connectivity with RTDS, Opal-RT, Typhoon HIL, and other Novel Hardware Assets for Large Scale Testing

Multi-Lab Co-simulation and (P)HIL- Grid Testing

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Western System Coordinating Council (WSCC) 9-bus system approximation

European HV transmission network benchmark (CIGRÉ)

MMC-based MVDC Test Bed

220

kV

22 k

V22

kV

22 k

V

63

MVA

55

MVA

63

MVA

Distribution system – a portion of Turin City, Italy

Controller-In-the-Loop

Thank You &

Questions

Rob Hovsapian rob.hovsapian@inl.gov

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