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transcript
Adamantios Marinakis, Scientist, 12th IEEE SB Power Engineering Symposium, Leuven, 24.03.2016
Enhancing Power System Operationwith WAMS
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1. Introduction to WAMS
2. Present WAMS applications: offered by ABB PSGuard
3. Future WAMS applications: data-based root-cause analysis and decision support
Presentation Outline
March 18, 2016
Introduction to WAMS
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MotivationFrom traditional to future grids
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Need for WAMS
Traditional grids:• Centralized power generation
• One-directional power flows
• Generation follows load
• Operation based on historicalexperience
Future grids:• More distributed power generation
• More intermittent renewable powergeneration
• Some consumers become prosumers
• More multi-directional power flows
• Load adapted to production
• Operation based more on real-timedata
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Basic IdeaWide Area Monitoring Systems
March 18, 2016
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PMU
PMU
PMU
PMU
PMU
PMU
PMU
PMUPhasor Measurement Unit
U1I3
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Wide Area Monitoring SystemsPhasor measurements
March 18, 2016
High accuracyprovides the basisfor an accuratemonitoring ofpower networks
RES670 V.2.0Timestamp accuracy: 1 microsecond
Absolute angle accuracy error: < 0.1 degree
CT/VT: 0.2 … 0.5%
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Wide Area Monitoring SystemsPositioning in system operation
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11IEC 60870-5-104
Reaction TimeDynamic Static
Coo
rdin
atio
nLe
vel
Component Protection
Direct local actions by on-linestatus confirmation
WAMS
Coordinated measures basedon dynamic view for monitoring,protection and control of powersystems
SCADA / EMS
Monitoring at SCADA / EMScycle rates actions initiated bylong term phenomena
PSGuard
Loca
llyN
etw
ork
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• PMUs at substations
• Phasor Data Concentrators (PDC)
• PSGuard at the control center
• Data from other control centers
• Interface with SCADA/EMS
Wide Area Monitoring SystemsTypical architecture
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WAMS applications
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• Advanced visualization of raw measurements• Voltage and phase angle profiles• Real-time power swing display• Phasor-assisted state estimation
• Monitoring and prediction of transmission capacity• Line thermal monitoring• Voltage stability monitoring• Power oscillation & damping monitoring
• Coordination of actions in emergency situations• Emergency FACTS/HVDC setpoint rescheduling• Wide-area control for damping oscillations
WAMS applicationsOverview
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WAMS applicationsVisualization of raw PMU measurements
March 18, 2016
VIDEO
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WAMS applicationsEvent driven data archiving
• Wide area disturbance recorder based onlogical trigger conditions
• Central triggering by observing network-widedata
• Configurable archiving length and resolution• Archives are provided in CSV file format• Continuous archiving provides daily archiving
for long-term data storage
March 18, 2016
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WAMS applicationsLine thermal monitoring (LTM)
• Measurement of Current and Voltage Phasors• Estimation of line resistance• Determination of conductor temperature• Real-time display of average temperature of
conductor• Patented method
March 18, 2016
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WAMS applicationsLine thermal monitoring (LTM)
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Line Mettlen-LavorgoFirst line to trip at the Italian blackout in 2003Line length ~120 km
WAMS applicationsLTM: pilot installation in the Alpes
Considerable differentiation of altitude over linelength
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Three line temperature monitoring technologies:1) surface acoustic wave, 2) tension sensors, 3) ABB PMU-based
WAMS applicationsLTM: pilot installation in the Alpes
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WAMS applicationsVoltage stability monitoring (VSM)
• Assessment of distance to Point of MaximumLoad ability (in MWs)
• Identify network equivalent• Stay on top section of PV Curve !• Trigger emergency actions when Power
Margin too small• Patented Method
March 18, 2016
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WAMS applicationsVoltage stability monitoring (VSM)
• Identification of three areas:• generation area• transmission corridor• load area
• Strategic placement of PMUs• Summation of the currents in each cut gives
the two currents, i1 and i2• The voltages v1 and v2 can be computed as
follows
=+
∗
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WAMS applicationsPower oscillation monitoring (POM)
• Real-time detection of power swings• Algorithm is fed with selected
voltage and current phasors• Detection of various swing
(power oscillation) modes• Quickly identifies amplitude and frequency of
oscillations• In service since 2005• Field experience in Switzerland,
Croatia, Mexico, Thailand, Finland, Norway,Austria
March 18, 2016
Mode Frequency
Mode Amplitude
Damping
Bus Voltage
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Ambient vs. Transient Oscillations• POM detects transient oscillations• PDM determines modes based on ambient
variations
WAMS applicationsPower damping monitoring
PDM capabilities:• Use of multiple input signals
• Mode shape determination
• Accurate determination of damping level
• Simultaneous detection of multiple modes
• Possibility to incorporate probing signals
March 18, 2016
-60 -40 -20 0 20 40 6049.85
49.9
49.95
50
50.05
50.1
Time (sec)
Freq
uenc
y(H
z)
ambient
transient
ambient
5600 5800 6000 6200 6400 6600
T86T77T76T74T62T61T16T01G16G15G14G13G12G11G10
G9G8G7G6G5G4G3G2G1 1
23456789101112131415161718192021222324
time/sample interval
normalised trend MW1
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PSGuard at Swissgrid
WAMS applicationsPOM & PDM: actual case
Major oscillation modes identified by PDM
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North-southmode East-west
mode
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WAMS applicationsPOM & PDM: actual case
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-20 0 20 40 60 800.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
Damping (%)
Freq
uenc
y
From ENTSO-E report: Sat. 19/02/2011 ~8:00: inter-areaoscillations within the Continental Europe power system.Highest impact observed in middle-south with amplitudes of+/- 100 mHz in S. Italy, power oscillation on several north-south corridor lines of up to +/- 150 MW & voltageoscillation on the 400 kV system of +/- 5 kV. Duration was~15 minutes. The oscillations started and finished withoutdirect correlation to known disturbances or forced outages.
POM warning
POM alarmat 8:02 am
POM alarmcondition cleared
PDM was correctlyidentifying thepresence of thepoorly damped mode
PDM output
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• Wide area power oscillation damping control (WA-POD)• Chose feedback signals from any PMU equipped
substation in Nordel• Coordinated POD action from several actuators
• SVC, FACTS, generators, HVDC
• Prototype WACS implemented and tested• Integration of PMUs with FACTS control
system• Wide area power oscillation damper with
local signal based POD as backup
• First successful pilots carried out in 2011by Statnett
WAMS applicationsFirst closed-loop wide-area control in Europe
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Data-based root-cause analysis anddecision support
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Mining WAMS dataMotivation
Stability indices:• LTM (line thermal monitoring)• VSM (voltage stability monitoring)• POM (power oscillation monitoring)• PDM (power damping monitoring)
What we have:An operator knows in real-time the stability indicesin its system⇒ The operator knows the system’s securitystatus
What is additionally needed:Given a candidate operating point• predict its expected security statusGiven an observed insecure operating point• determine the reason ;• modify the operating point to make it secure
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Mining WAMS dataOutline of proposed approach
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WAMSArchiveWAMSArchive
SCADA/WAMSArchive
SCADA/WAMSArchive
alignment/cleaning, etc.
SCADA/EMS
Data mining /MachineLearning
2) Predictstabilityindices
3) Correctoperating
point
WAMS
1) Associatesecurity withsystem state
Candidateoperating pointRegression /
ClassificationModel
SCADAArchiveSCADAArchive
PDC Stabilityindices
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Mining WAMS dataIllustrative example
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13k samples, produced by simulations
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Mining WAMS dataIllustrative example
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Typical action taken by system operators:
Reduce the intertie flow if damping ratio is below a selected value.
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Mining WAMS dataIllustrative example: Results
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PSS 63 PSS 51
Intertie flow
Gen 63
Feature selection objective: Find a subset of features thatcorrelate well with the target output but have little inter-correlation.
Features that are most relevant tothe inter-area oscillation dampingas identified by various algorithms
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Mining WAMS dataIllustrative example: Results
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Model training objective: Build a model that is able to predictwhether a candidate operating point is expected to correspond toa poorly damped oscillation mode.
Input features Accuracy (in %)
Intertie flow 95.60
Intertie flow & PSS status 96.62
ALL available features 99.65
Closure
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ClosureWhy do we need WAMS?
March 18, 2016
Real-time monitoring of power systems using synchrophasors,better use of existing equipment
Detection of incipient abnormal system conditions, reduced riskof instability, increased transmission capacity
Investment protection and step-wise improvement
Easy access to alarm, event list and disturbance information,integration into SCADA / EMS
Optimization through history data analysis, data storage forenhanced planning, post-mortem analysis
Betterobservability
Enhancedoperation
Know the limits
Supervision,alarms, events
Compare tooff-line
Real-time systemmonitoring
Improved systemplanning