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NSF Workshop
Real Time Data Analytics for the Resilient
Electric Grid
Data Driven Measuring and Enabling
Resiliency of the Community Grids
Rob Hovsapian, Ph.D.
Manager, Power and Energy Systems
Idaho National Laboratory
August 3rd, 2018
Integrated Multi-Scale Real-Time Simulation Test-bed
2
Real world PHIL & CHIL testing capabilities.
1 - INL Utility Scale Microgrid Project – Red Cross Evacuation
▪ Funded by California
Energy Commission’s
Electric Program
Investment Charge
▪ PON-14-301
▪ Program Goal:
Demonstration of Low
Carbon-Based Microgrids
for Critical Facilities
▪ Partners – INL, Siemens,
Tesla (Utility scale Storage)
Humboldt University, PG&E
Blue Lake Rancheria – CEC Project
• Microgrid provides resilience to the power supply in the area, a Red Cross evacuation route.
• Operating and troubleshooting complex systems in a test environment.
• Developers could safely conduct fine-tuning and de-risk transitions to the end-user’s live systems.
• Partners included the California Energy Commission ($5M with 20% cost share), Siemens, Tesla and Humboldt State University.
California Energy Commissioner – ProjectFuture & Existing Energy Infrastructure
Digital Blue Print, Rapid Prototyping Design Environment and Functionality Testing via CHIL
Microgrid Modes of Operation:
1. Grid connected 2. Black start transition3. Off-grid operation4. Resynchronization to
PG&E network
PG&E Power System Network
INL
Blue Lake Rancheria , CASiemens
MGMS
Modbus/DNP3.0 connection
BLR – Benefits / Awards
Energy Savings
First year savings were 563 MWh.
Greenhouse Gases
159 metric tons of CO2 were abated during the first year.
Job Creation
This project has resulted in the creation of four permanent, new jobs at
BLR. This is a 10% increase in the tribal government workforce.
Public Safety
The BLR campus now has a supply of locally generated green power,
which together with battery storage, provides emergency power to
support their role as a Red Cross shelter in times of need.
Awards:• FEMA’s 2017 Whole Community Preparedness Award
• DistribuTECH 2018 Project of the Year for DER Integration
Idaho Falls Power - Smart Reconfiguration of Idaho Falls Power Distribution Network for Enhanced Quality of Service
Idaho Falls Power Regional Distribution Network
microPMUs
PMUs
SEL HIL
(to be extended)
Protection devices
and
Switches Hard
ware P
MU
Analog/digital output
Analog/digital output
Measurement
Measurement
Control action
Analog output
Software PMU
Va
Vb
Vc
q
d
INL Energy Systems Laboratory
Priority Description
1 – 4
Very High Priority Loads
(Examples: Hospitals, Control/Command
center, Emergency Response/Dispatch)
5 – 9
High Priority Loads
(Examples: Airport, Correctional Facilities,
Police Department, Fire Station)
10 – 12 Medium Priority Loads
(Examples: Fire Station, State Services)
13 – 16
Low Priority Loads
(Examples: Water Treatment, Community
Care)
2 - Resilience Metrics Approach to design a Community Grid
Next Generation Microgrid Design
• Next generation of microgrid design tools– Communication emulation
– Co-simulation of • communication,
• power electronics (including SiC-based devices),
• power systems (including real-time emulation of protection system)
9
NS3-based Communicat ion Layer
Cont rols
I nterface
Cont roller HI LHardware Protect ion Relays
I nterface
V,I -AMPs
Resilience Based Reconfiguration/Operation
10
Example
Priority
Example
Load Description
1 – 4
Very High Priority Loads
(Examples: Hospitals,
Control/Command center,
Emergency
Response/Dispatch)
5 – 9
High Priority Loads
(Examples: Airport,
Correctional Facilities,
Police Department, Fire
Station)
10 – 12 Medium Priority Loads
(Examples: Fire Station,
State Services)
13 – 16
Low Priority Loads
(Examples: Water
Treatment, Community
Care)
Example Critical Loads (priority numbered)
3
4
10 12
13
14
1 2
11
15
8 9
5 6
7
16
Real-time Integrated HIL Testing
Idaho Falls Power Regional Distribution Network
microPMUs
PMUs
SEL HIL
(to be extended)
Protection devices
and
Switches Hardw
are PMU
Analog/digital output
Analog/digital output
Measurement
Measurement
Control action
Analog output
Software PMU
Va
Vb
Vc
q
d
INL Energy Systems Laboratory
11
• Black Start of IFP grid and re-synchronization to transmission grid• One scenario is investigated to test synchronization of City Bulb generator to a
T-grid source while City Gen is serving the local command center critical loads
Black Start – Preliminary HIL Testing March ‘17
Out of
Synchronis
m
In
Synchronis
m
► Synchronization controls are modeled in RTDS-RSCAD for seamless
resynchronization
► SEL 700GT+ Relay is used as Hardware-in-the-Loop (HIL) simulation with
analog and digital interfacing with RTDS
T-grid kept at
46kV, 60Hz,
20degrees
Total load
~ 874 kW
Station Transformer
4.16kV/12.47kV/46kV
City Bulb: 8.9MVASEL
700G
12
13
3 - Resilience By Design – Resilient Alaskan Distribution system Improvements using Automation, Network analysis, Control, and Energy storage (RADIANCE)
Goals and Objectives (cont’d.)Technical Approach: Integrated and iterative
field validation of resilience-based design and
operation to goals
Figure is modified directly based on GMLC Lab Call document
Project OverviewResilience Metrics Framework for Design and
Operation
Field validation of increasing resiliency of the overall distribution system by
leveraging resources from multiple networked microgrids
Leverage rotational and virtual inertia of microgrids assets including hydro,
diesel, energy storage, and micro PMU-based sensing to enhance
resilience of the overall regional distribution network
Develop and demonstrate practical use of resilience metrics for
coordinated operation, design to minimize outages, financial losses
Multiple Networked Microgrids in Distribution System
Cyber-security Architecture and Rapid Prototyping of
Controls
Field Validation of Resiliency Enhancement Methods
Rapid prototyping of controllers as HIL and cyber-vulnerability testing in a
real-time cyber-secure environment
1
2
3
4
• Storm Hardening
• Installation of backup
generator
Recovery
Resources strategically
placed
Request backup
Services and crew
Smart Load
Shedding
Process Validation
Critical Load
survival
Automated restoration
Smart recovery and
Repair-based restoration
Initial Forecast
Stage 2 Stage 3 Stage 4Stage 1
Event characterized Precede Event During Event Aftermath Recovery Phase
Resiliency enabling process is dynamic
Anticipate Withstand Recover
Develop a threat modelKnow the infrastructure
Anticipate impact of threat on the infrastructure
Building upon software tools developed in GMLC 1.3.9, CANVASS, resiliency
metrics will be calculated based on threat at a nodal as well as a network level.
Calculating Resiliency Metrics
Ability of an infrastructure component or
infrastructure to endure an high-impact event, may be
storm hardening, or backup individual
generators
Minimum spanning tree and critical-first restoration
strategies and resource optimization to enable
maximum resilience and minimum downtime
Architecture Design – Resiliency Framework
• Operational Resilience Metrics Computation Flowchart
Real-time Inputs
(weather, power grid)
Historical
Data
Probabilistic
Analysis
Physical
and
Communication
Infrastructure
Design
Operation
and
Controls
Real-time computation
of Resilience Metric
Thank you