Enhancing Power System Operation with WAMS

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

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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

March 18, 2016

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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

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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

=+

∗

March 18, 2016

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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

March 18, 2016

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