1. Grid Resilience and Intelligence Platform (GRIP) Use-case
CEC Advanced Simulation Program
TAC Meeting
Oakland, California
6 September 2019

2. Grid Resilience and Intelligence Platform (GRIP) Use-case
Alyona Ivanova (SLAC)
CEC Advanced Simulation Program
6 September 2019
This presentation was prepared with funding from the California Energy Commission under grant EPC SLAC National Accelerator Laboratory is operated for the US Department of Energy by Stanford University under Contract No. DE-AC02-76SF00515

3. Import & Validate (OpenFIDO)
Outline
External
datasets
External models
Shared datasets
Shared models
Import & Validate (OpenFIDO)
Simulate
(HiPAS & GLOW)
Analyse (custom)
CSV Files
Plots
MySQL Data
Copy/link
(Cloud Security)
Introduction
Objectives
Resilience overview
Anticipation
Pole model
Pole degradation
User Interface
Absorption
Model Overview
Planned Improvements
Acknowledgements
The GRIP project is funded by the US Department of Energy under the Grid Modernization Laboratory Consortium (GMLC).

4. Grid Resilience and Intelligence Platform (GRIP)
Applies artificial intelligence and machine learning to anticipate, absorb and recover from extreme events that affect the Distribution Energy System

5. GRIP Innovation and Impact
GRIP applies AI and ML for grid resilience.
National impact with platforms and analytics
Facilitates streamlining use of ML/AI applications for distribution resources.
Final deliverable: open-source commercially available product.
Year 1: Anticipation (Completed)
Year 2: Absorption (In-progress)
Year 3: Recovery (Future Work)

6. Anticipation Objectives
Determine use-cases for resilience.
Asset and protective device location and mapping
Predicting vulnerabilities to extreme weather conditions
Switch re-configuration
Predicting ferroresonance occurrences
Secondary voltage optimization with DERs
Vegetation management
Optimized work plans considering budget hardening options
Develop a new platform based on pre-existing Google tools.
Use previously DOE funded projects (VADER, OMF) as basis for GRIP
Test and validate anticipation solution with data and models provided by National Rural Electric Cooperative Association (NRECA).

7. Core GRIP Simulation Analysis
GridLAB-D implementation incorporates vulnerability analysis
Analytical pole and line vulnerability model using weather data
Calculation of pole vulnerability index, electrical fault propagation and restoration time
Wind stress simulation represents worst case scenario
Support for arbitrary vulnerability simulations
User ability to specify the electrical system model
Calculations of stresses loading to pole failures
Cables tension
Pole-mounted equipment
Pole tilt angle
Wind and ice loading

8. Internal pole degradation model
Applicable to wood poles only
Propagation of internal core degradation to outer edges
Degradation defined by minimum shell thickness
End-of-life thickness: 2”
Characterized by the difference between the outer core and inner core moment calculations
Accounts for pole base failures 2”

9. IEEE Standard test models
Image obtained from DOI: /TSG
Image obtained from DOI: /TDC

10. GRIP Further Design
Creating a dashboard that not only lists the simulations, but highlights status and results of each simulation.

11. Refining the layout data visualization

13. Absorption
Dynamic reconfiguration of the network into virtual islands after distribution circuit damage due to weather disturbances
Maximize amount of load that can be maintained during the fault
Uses DG, batteries, flexible DERs (water heaters, distributed batteries, EV chargers) when supporting virtual islands
Model development (SLAC/GridLAB-D) + Controls (Packetized Energy) + UI (Presence)
Typical sequence:
(1) Fault occurs
(2) Fault isolation
(3) Reconfiguration (Virtual Islanding)
(4) Load balancing

14. VIRTUAL ISLANDING TEST CASE built in GridLAB-D
001
Node representing the Bulk Grid
VIRTUAL ISLANDING TEST CASE built in GridLAB-D 1 NC NC 2 NC
002 4
Legend NC
Switch or circuit breaker/recloser that is closed (hot) 3
101
201
301
Switch or circuit breaker/recloser that is open (not hot) 5 7 9
102
202
Solar1
Solar2
302
Solar3
xyz
Distribution circuit node (or collection of nodes) with (eg) hundreds of customers. 6 10 8 11 12
103
203
303
Fault location NO NO
Battery1
Battery2
Battery3

15. CASE 1: SINGLE FEEDER FAULT
001
Node representing the Bulk Grid
CASE 1: SINGLE FEEDER FAULT 1 NC NC 2 NC
002 4
Legend NC
Switch or circuit breaker/recloser that is closed (hot) 3
101
201
301
Switch or circuit breaker/recloser that is open (not hot) 5 7 9
102
202
Solar1
Solar2
302
Solar3
xyz
Distribution circuit node (or collection of nodes) with (eg) hundreds of customers. 6 10 8 11 12
103
203
303
Fault location NO NO
Battery1
Battery2
Battery3

16. CASE 1: STEP 1 BREAKER TRIPS
001
Node representing the Bulk Grid
CASE 1: STEP 1 BREAKER TRIPS 1 NC NC 2 NC
002 4
Breaker
opens
Legend NC
Switch or circuit breaker/recloser that is closed (hot) 3
101
201
301
Switch or circuit breaker/recloser that is open (not hot) 5 7 9
102
202
Solar1
Solar2
302
Solar3
xyz
Distribution circuit node (or collection of nodes) with (eg) hundreds of customers. 6 10 8 11 12
103
203
303
Fault location NO NO
Battery1
Battery2
Battery3

17. CASE 1: STEP 2 FAULT ISOLATION
001
Node representing the Bulk Grid
CASE 1: STEP 2 FAULT ISOLATION 1 NC NC 2 NC
002 4
Legend NC
Switch or circuit breaker/recloser that is closed (hot) 3
101
201
301
Switch or circuit breaker/recloser that is open (not hot) 5 7
Sw. opens 9
102
202
Solar2
302
Solar1
Solar3
xyz
Distribution circuit node (or collection of nodes) with (eg) hundreds of customers. 6 10
Sw. opens 8 11 12
103
203
303
Fault location NO NO
Battery1
Battery2
Battery3

18. CASE 1: STEP 3 RECONFIGURATION
001
Node representing the Bulk Grid
CASE 1: STEP 3 RECONFIGURATION 1 NC NC 2 NC
002 4
Legend
Switch or circuit breaker/recloser that is closed (hot) 3
101
201
301
Switch or circuit breaker/recloser that is open (not hot) 5 7 9
102
202
Solar1
Solar2
302
Solar3
xyz
Distribution circuit node (or collection of nodes) with (eg) hundreds of customers. 6 10 8 11 12
103
203
303
Fault location
Battery1
Battery2
Battery3

19. Planned Improvements
Planned enhancements to the pole vulnerability model
Add effect of changing wind direction
Add ice build-up model and line loading effects
Extend taxonomy of impacts of vegetation on lines, poles, and equipment
Pole degradation
Pole top failures due to equipment, weather and animal impacts

20. Vegetation Risk Assessment
Risk modeling and quantification questions related to vegetation
Effect of vegetation on the electrical system
Other effects beside vegetation falling on lines (e.g., line-to-tree faults, etc.)
Additionally the effect of the electrical system on the surrounding community
Model the fire initiation and propagation risk through vegetation
Develop a vulnerability index for the surrounding community
Account for recent history, damage, impact zones, magnitudes
Use US Forest Service models to assist model development for fire behavior

21. GRIP Technical Team SLAC National Accelerator Laboratory PresencePG
Packetized Energy
National Rural Electric Cooperative Association
Lawrence Berkeley National Laboratory

22. Acknowledgements
GRIP Technical Advisory Group Members

23. Questions?