1. From Fault Recording to Disturbance Recording
Sakis Meliopoulos
Georgia Power Distinguished Professor
School of Electrical and Computer Engineering
Georgia Institute of Technology
Atlanta, Georgia 30332

2. Outline
Why FR  DR
Requirements/data processing
Historian for Disturbance Play Back
Conclusions

3. Why FR  DR
Following the 2003 blackout, numerous engineers worked for months to align and synthesize fault recorded data for the purpose of re-creating the disturbance and the evolution of the blackout
There must be a BETTER WAY

4. FR  DR: How
For Disturbance Recording and playback:
Recording system requirements
Storage schemes (what to store – data processing - model)
Playback and system synthesizing

5. The SuperCalibrator Concept as a Data Compressor
What to Store
The SuperCalibrator Concept as a Data Compressor
Fact: A plethora of data is available at the substation level
The SuperCalibrator is conceptually very simple:
Utilizes all available data (Relays, DFRs, PMUs, Meters, etc.).
Utilizes a detailed substation model (three-phase, breaker-oriented model, instrumentation channel inclusive and data acquisition model inclusive).
At least one GPS synchronized device (PMU, Relay with PMU, etc.) Results on UTC time enabling a truly decentralized State Estimator.
Extracts the Real Time Model of the System form all available measurements mentioned above.
Recently this approach has been extended to dynamic state estimation with build in fault locating: PMU data of phasors, frequency and rate of frequency change are used to provide the dynamic state of the system in a reliable and robust way

6. Distributed Dynamic State Estimation Implementation
System is Represented with a Set of Differential Equations (DE)
The Dynamic State Estimator Fits the Streaming Data to the
Dynamic Model (DE) of the System

7. SuperCalibrator Measurement Set
Conversion of Non-Synchronized Measurements into Phasors
α is a synchronizing unknown variable
cos(α) and sin(α) are unknown variables in the state estimation algorithm.
There is one α variable for each non-synchronized relay

8. Dynamic State Estimation – Block diagram
Dynamic State Estimation Problem is Converted to Static by Integration
Least Squares Solution
Bad Data Detection
Bad Data Identification and Removal

9. Dynamic State Estimation: Numerical Experiments
Test System: 3 generating substations and an infinite bus connected through overhead transmission lines
Substation 1: Substation of interest where DSE is performed
Simulated 3 phase fault near Substation 3
DSE uses PMU and other relay measurements in the first substation
DSE algorithm estimates local and neighboring substation states

10. Numerical Experiments: Post Fault DSE Performance
Simulated and Estimated Voltage Magnitude at Substation 3 (neighboring substation) for post fault condition
Simulated and Estimated Voltage Phase angle at Substation 3 (neighboring substation) for post fault condition

11. Distributed Dynamic State Estimation Implementation 1
Physical Arrangement
Data Flow
Data/Measurements from all PMUs, Relays, IEDs, Meters, FDRs, etc are collected via a Local Area Network in a data concentrator.
The data is used in a dynamic state estimator which provides the validated and high fidelity dynamic model of the system.
Bad data detection and rejection is achieved because of high level of redundant measurements at this level.

12. Distributed Dynamic State Estimation: Implementation 2

13. The USVI WAPA System Provides an Excellent Testbed for the Distributed Dynamic State Estimator
The USVI WAPA system is a small MW, Five Substations, 35 kV/13 kV System. 17 relay/PMUs.
Faults create large swings of the generators as manifested by the frequency oscillations in the Feb 20, 2008 event.
In addition events are more frequent in the USVI system than mainland systems.

14. Distributed Dynamic State Estimation During a Fault
The Dynamic State Estimator Operates at 10 times per second
What happens when a fault occurs?
Introduce the Fault Location (F) as another State to be Estimated

15. Historian for Disturbance Play-Back Substation Storage Scheme
Full Model + Model Changes + Data
System FULL MODEL stored once a day in WinIGS format – time of day can be arbitrarily selected, for example at 2 am. (example storage follows)
Report system changes by exception – UTC time (example storage follows)
Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format. (example storage follows)

16. Substation Storage Scheme FULL MODEL + Model Changes + Data
System FULL MODEL stored once a day in WinIGS format.
Time of day can be arbitrarily selected, for example at 2 am.
Example storage:
MODEL 3
DEV_TITLE Long Bay Substation
NUMERIC_ID 77
NET_LAYER 3
GEO_COORDINATES
COORDINATES
COORDINATES
INTERFACES FDR-9B 3-0A0B2 FDR-8B FDR10B FDR-YH1 3-0B0D 3-0A0B1 FDR-7B
INTERFACES FDR-YH2
PARAMETERS LONGBAY VIWAPA VIWAPA
END_MODEL
MODEL 123
DEV_TITLE Feeder #11, Long Bay to East End Substation - Section 1
NUMERIC_ID 246
COORDINATES
COORDINATES
CIRCUITS 1
INTERFACES 3-0B0D_N 3-0B0D_A 3-0B0D_N 3-0B0D_B 3-0B0D_N 3-0B0D_C 3-0B0D_N UG350_N
INTERFACES UG350_A UG350_N UG350_B UG350_N UG350_C UG350_N
PARAMETERS CABLE
PARAMETERS VI34KV750KCM-CU-TS CKT1 CABLE VI34KV750KCM-CU-TS
PARAMETERS CKT1 CABLE VI34KV750KCM-CU-TS CKT1 CABLE CONDUIT8
PARAMETERS CKT1 COPPER 4/ CKT1
PARAMETERS 1 CKT
………
Substation Model
Transmission
Line Model

17. Substation Storage Scheme
Full Model + MODEL CHANGES + Data
Report system changes by exception – UTC time
MODEL_CHANGE
TIME
TYPE XFMR_TAP
DEVICE_ID 1265
VALUE R12
END_MODEL_CHANGE
TIME
TYPE BREAKER_OPERATION
DEVICE_ID 3409
VALUE CLOSE
. . .
SOC + Fractional Second
March 05, 01:44:
File Format – Each line begins with a keyword
optionally followed by one or more arguments.

18. Substation Storage Scheme Full Model + MODEL CHANGES + Data
Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format. The following File Types Are Used:
Configuration Files: Description of State Names Types and Locations
State Data Files: State Values plus Model Change Information
Triggered Event Files: Waveform data recorded for each triggering
event in COMTRADE format.

19. Substation Storage Scheme Full Model + MODEL CHANGES + Data
Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format.
Configuration File – One for Each Day
File Naming Standard: CompanyName_SubstationName_SOC.scf
File Content:
<Title or Brief Description>
<SOC> <uSec>
<Number of States>
<State Name>, <State Type>, <Bus Name>, <Phase>, <Power Device ID>
. . .
Where:
SOC: is the Second of Century Time Code defined as the number of seconds elapsed since midnight of January 1, 1970 (in UTC time)
uSec is a fractional second value in microseconds.
Above structure repeated each time the set of states changes

20. Substation Storage Scheme Full Model + MODEL CHANGES + Data
Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format.
State Data File – One for Each Day
File Naming Standard: CompanyName_SubstationName_SOC.sdf
File Content:
STATE_VECTOR <SOC> <uSec> <State Value> <State Value> <State Value>. . .
. . .
MODEL_CHANGE
TIME
TYPE BREAKER_OPERATION
DEVICE_ID 3409
VALUE CLOSE
END_MODEL_CHANGE

21. Substation Storage Scheme Full Model + MODEL CHANGES + Data
Storage of state data: at each occurrence of the state estimator, the estimated states are stored in COMTRADE-like format.
Triggered Event Files – One for Each Event
File Naming Standard:
CompanyName_SubstationName_SOC.cfg
CompanyName_SubstationName_SOC.dat
File Content:
Standard COMTRADE Waveform File Format

22. Re-Construction of System State
System Operation “Play Back” over a user specified time interval (t1 to t2)
Reconstructed state is presented via graphical visualization Techniques, ( 3-D rendering, animation etc) with multiple user options.

23. Wide Area Monitoring and Disturbance Play-Back
The SuperCalibrator at each substation stores the streaming data with (a) time tags, (b) network status, and (c) substation real time model at the time.
This data can be “played back” for any user specified past time interval. Various visualizations allow the user to observe specific performance parameters of the system. Examples are: (a) voltage profile evolution, (b) transient swings of the system, (c) electric current flow, etc.

24. Conclusions
The Dynamic State Estimator fits PMU data to the Dynamic Model of the System: Enables a powerful method to study system dynamics and predict performance.
Fault Location Estimation has been integrated into the Dynamic State Estimator.
Substation storage scheme (historian) that enables automated Disturbance Play Back. The implemented historian of (full model) + (model changes) + (data) has been presented. Comments and suggestions are welcome.
Need for standards for disturbance+model storage and playback that include coincident system models.