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Real-Time Operation Tools
Using PMU Data
Dr. Pengwei Du
On behalf of
Jeff Dagle, PE
Chief Electrical Engineer
Advanced Power & Energy Systems Group
Pacific Northwest National Laboratory
(509) 375-3629
Nov. 16, 2012
ERCOT Phasor Technology Workshop
November 16, 2012
Pacific Northwest National Laboratory:
Battelle-managed and mission-driven
DOE Office of Science Laboratory
Operated by Battelle since 1965
Outstanding science, impactful solutions
Nearly 5,000 employees
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Our vision
PNNL will be recognized
worldwide and valued
nationally and regionally
for our leadership in
science and for rapidly
translating discoveries
into solutions for
challenges in energy,
the environment, and
national security.
Examples of phasor-based advanced
analytics projects at PNNL
Mode Meter and Spectral Analysis
Real-Time Wide-Area Monitoring Tool Based on Characteristic Ellipsoid Method (CELL)
Modal Analysis for Grid Operations (MANGO)
Typical Patterns, Atypical Events, and Uncertainty in Complex Systems
Funding acknowledgement U.S. Department of Energy, Office of Electricity Delivery and Energy Reliability, Consortium for Electric Reliability Technology Solutions (CERTS)
California Energy Commission
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Mode Meter and Spectral Analysis
Dr. Ning Zhou (PI) Pacific Northwest National Laboratory
Measurements vs Model Simulation
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[1] Kosterev, D. N., C. W. Taylor,
and W. A. Mittelstadt, “Model
Validation for the August 10,
1996 WSCC System Outage,”
IEEE Transactions on Power
Systems, vol. 14, no. 3, pp. 967-
979, August 1999.
Initial Results from
the Comprehensive
Simulation Model
using Component-
based Modeling
Method
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Observed COI Power (Dittmer Control Center)
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Time in Seconds
Model
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Time in Seconds
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Observed COI Power (Dittmer Control Center)
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0 10 20 30 40 50 60 70 80 90
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Time in Seconds
Model
Reality
Po
wer
Tra
nsf
er
No
rth
-So
uth
Oscillations in Power Grid
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[bitmap version
1100
1200
1300
1400
1500 15:42:03
15:48:51
15:47:36
Power (MW)
August 10, 1996 Western Power System Breakup
California-Oregon Intertie
Tim
e D
om
ain
~ -3.1%
< ~3.5%
Damping
~ 8.4%
Early Warning
~6 minutes
Fre
q D
om
ain
Mode Meter
Problem statement:
Unstable oscillations occur in power
system and may cause system
breakup and power outage(e.g.
western system break on Aug 10,
1996.)
Mode meter:
Approach: to detect unstable
oscillations in a power system
using measurement data.
Impact: increases asset utilization by
improving confidence in oscillation
detection and enables proactive
actions to prevent system breakup
and power outage.
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In an event playback, PNNL mode meter prototype tool can detect
the low damping oscillations 6 minutes before the breakup of WECC
on Aug 10th, 1996.
Spectral Analysis
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Spectral history of bus frequency for August 14 2003
North East Blackout. 12:00-16:10 EDT
"Performance of 'WAMS East' in Providing Dynamic Information for the North East Blackout of August 14,
2003", J. F. Hauer, Navin Bhatt, Kirit Shah, and Sharma Kolluri. Invited paper for IEEE/PES Panel on Major Grid
Blackouts of 2003 in North America and Europe, IEEE PES General Meeting, Denver, CO, June 6-12, 2004.
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Real-Time Wide-Area Monitoring Tool Based
on Characteristic Ellipsoid Method (CELL)
Dr. Yuri Makarov (PI), Dr. Ruisheng Diao Pacific Northwest National Laboratory
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Project Objectives and Quick Overview
Objective:
Develop a relatively simple, easy-to-implement and easy-to-use tool to monitor, predict the dynamic behavior of power systems for wide-area situational awareness, prediction and decision making support for operators
Specific Objectives:
Monitor dynamic behaviors of power systems
Identify system disturbances
Provide wide-area situation awareness far beyond a single control area
Supply predictive and actionable information (in progress)
Demonstration and Testing:
Tested on WECC (Western Electricity Coordinating Council) model
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CELL: Minimum Volume Inclusive
Ellipsoid
System trajectory Simple quadratic algebraic equation
An optimization procedure minimizes the volume of CELL
CELL encloses all recent points of system trajectory
Key characteristics of CELL:
♦ volume ♦ derivative of the volume
♦ eccentricity ♦ characteristic sizes
♦ orientation of axes ♦ projection of axes
11 1 2
22 2 22 1 2
1 1 2 2
1 2
( , ,..., )
( , ,..., )...
...
( , ,..., )
n
n
n n
nn n
dxF x x x
dt
dxF x x x
a y a y a y cdt
dxF x x x
dt
Physically meaningful system Information:
♦ disturbances (type, location, size, etc)
♦ damping
♦ coherency of oscillations
Case Study: Full WECC Model
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Overview of the full WECC operational model: 16,031 buses 3,993 transmission lines 3,216 generators 6,330 transformers
Operating conditions: 2009 heavy summer base case 25 operating conditions
Simulated five types of events at various locations: Generator trips: 112 machines Line trips: 117 transmission lines Three-phase faults: 111 bus locations Load loss: 34 loads Shunt switching: 23 locations Over 19,000 simulations
Selected only 12 PMUs across WECC to identify types and locations of various events
Performance (Success rate, %): Generator trip locations (13 zones): 97.86% Load loss locations (3 zones): 98.24% Line trip locations (9 zones): 95.21% Fault locations (9 zones): 99.01% Event types (5 types): 97.48%;
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Modal Analysis for Grid Operations (MANGO)
Dr. Henry Huang (PI), Dr. Ning Zhou (CO-PI) Pacific Northwest National Laboratory
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MANGO
Power Grid
Real-Time Phasor and
SCADA Measurements
Mode Meter
Mode Shape
Estimation
MANGO
Pa
ram
ete
r
Se
lecto
r
Operation
Procedures
Stage 1:
Manual
(Operator-in-the-loop)
Stage 2:
Automatic
(beyond scope)
Generation re-dispatch
Load shedding
Capacitor switching
……
Modes and Mode Shapes
Key
Operation
Parameters
Power Flow and
Dynamic Models
Mode Estimation
MANGO Model
Feasibility
Test
Recommended Actions
Operation Parameters
Mo
de
s
Target Modes
(damping)
Relative Modal Sensitivity Estimate on
WECC model
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M a j o r i n t e r a c t i o n p a t h
" I n d e x " g e n e r a t o r
S U N D A N C E
K E M A N O
M I C A
C O L S T R I P
P A L O
V E R D E
H O O V E R
G R A N D C O U L E E
M E A D F O U R C O R N E R S
S H A S T A
C A N A D A
M E X I C O
G M S H R U M
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Typical Patterns, Atypical Events, and
Uncertainty
in Complex Systems
Brett G. Amidan (PI) Pacific Northwest National Laboratory
Morning Report
The Morning Report was developed to help the aviation industry use mathematical methods to look at thousands of flights a day. These analyses focused on -
Typical patterns, that characterize >99% of the flights
Atypical events, that are worthy of individual inspection
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PNNL is applying this technology to power system analysis.
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Discovering Atypical Events
Finds the UNENVISIONED entities
that are anomalous.
End-users do NOT have to know what
they are looking for.
Viewable reports, drill-down plots,
and interactive data viewers allow
the user to explore each anomaly.
SitAAR (Situation Awareness Alerts in Real-time)
We have demonstrated a reporting system which finds
atypicalities and typical patterns for power grid.
Next step is to convert this to a real-time process –
Process enough data within the domain to be able to
establish typical patterns, using a mathematically-based
classification approach.
Use “active learning” to refine the patterns with domain
input.
Allow for the creation of new patterns, as they develop.
Add control chart alerts.
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Thank you!
Questions?
Contact: Jeff Dagle, PE
Chief Electrical Engineer
Advanced Power & Energy Systems Group
Pacific Northwest National Laboratory
(509) 375-3629
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