Phasor Measurements: Impact on EMS Control … · AREVA T&D Inc June 5-6/2006. 2 CIGRE Conference – June 05-06, 2006 2 ... SVC UVL shedding Remedial actions High speed trips Capacitor

CIGRE Conference – June 05-06, 20061 1

Phasor Measurements:

Impact on EMS Control Centers:State Estimation& Other Applications

Jay GiriRene Avila-Rosales

AREVA T&D Inc

June 5-6/2006


The Control Center Landscape is Changing

u Trends indicate a groundswell growth of PMUs in utilities worldwide

u In the next 5 years, this growth evolution could become a revolutionary new paradigm to operate in:

w500+ PMUs in Eastern US and Western US

wEach PMU provides dozens of data values, upto 60 times/sec

wSimilar dramatic growth trends in Brazil, Europe, etc.

u The big question is:

wHow will this benefit power system operations?


Power System Operations…

u Power grid has gradually evolved in an incremental manner over many decades

u Load and system conditions change continuously…

wQuasi-steady state conditions for majority of the time

wOccasionally goes into dynamically changing conditions

u Control center operators objective is: Use the EMS tools to make sure the “lights stay on all the time!”

u Prevent Blackouts!


EMS Applications

Operating System Operating System

Database & Development EnvironmentDatabase & Development Environment

SCADASCADA

Generation Generation ApplicationsApplications O

perator Console

Operator C

onsole

TransmissionTransmissionApplicationsApplications

Dat

a A

cqui

sitio

nD

ata

Acq

uisi

tion TrainingTraining

SimulatorSimulator

RealReal--Time ApplicationsTime Applications

Study mode / Modeling/ Archiving

DistributionDistributionApplicationsApplications

Power System(HV and MV substations)

Power System(HV and MV substations)


EyesEyes

Control Center Functions

SCADA

2 sec

AnalyticalBrain

AnalyticalBrain

Reactive Brain

Reactive Brain

Proactive Brain

AGC4 sec

SE & CA60 sec

DSSDTS

30 minFiscalBrain

MarketSystemTools


Asynchronous, Uncorrelated,

Telemetry view

Asynchronous, Uncorrelated,

Telemetry view

EMS Views of the Grid

SCADA

System-wide, correlatedExisting system-wide

view

System-wide, correlatedExisting system-wide

view

Generation, TiesEnergy Balance

(Freq) view

Generation, TiesEnergy Balance

(Freq) view

What is coming up nextFuture system-wide view

AGC

SE & CA

DSSDTS

PMU Data

PMU Data


EMS Benefits of “Phasor1” Data

u Phasor data

w Refresh rate 30 samples/sec

w Time tagged data

w Compatible with modern communication technology

w Responds to system dynamic behavior

w Angle-pair change means: MW change; ‘electrical distance change’

u EMS SCADA data

w Refresh rate 2-5 seconds

w Latency and skew

w Relies on legacy ‘older’ communication technology

w Responds to system static behavior

w Freq change means: Generation/Load imbalance

1“Phasor” is in quotes to suggest that we are not talking strictly about phasors, but about high speed, accurately time-tagged ‘synchronous’data in general.


Typical phasor measurements from A Single PMU

u 20 Hz:w Phase A, B, C current magnitude and phase angle

w Phase A, B, C voltage magnitude and phase angle

w Frequency + others

u1 Hzw Phase A, B, C Active Power

w Phase A, B, C Reactive Power

w Phase A, B, C Apparent Power

w Phase A, B, C power factor

w Total active power

w Total reactive power

w Total apparent power

w Total power factor

w Positive, Zero and Negative sequence current magnitude and phase

w Positive, Zero and Negative sequence voltage magnitude and phase + others


Industry Challenges

u Impacts of Deregulation

w Independent generation

w Transmission grid pushed closer to limits

u Congested Corridors

w Locations are less predictable

w Lack of transmission capacity

w National Interest corridors

u Dynamic Instabilities

w Cascading events

w Lack of reactive support

w Acts of nature


Evolution of Network Model Sizes

8,000 buses(reduced ECAR)

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

1,200 buses (Original EMP Test

Model)

6,000 buses(WECC

161 KV & above)

4,200 buses

8,000 buses

5,000 busesTransmission

23,000 buses Mar 05(Eastern Interconnect

Breaker Model73,000 buses )

32,000 buses

2,500 buses Dec 04(42,000 buses used for FAT/SAT)

11,000 buses (PSSE Bus/Branch replaced by detailed

breaker for MISO Area )1,400 buses

3,000 buses

2,000 buses

1.5M feedersDistribution

3,000 buses

5,000 buses


PMUs & EMS Applications 1

uModel data validation

u Immediate alerts of sudden system changes

u Contingency Analysis alerts:

wSudden angle-pair changes for critical corridors

u Forensic studies to recreate disturbance

u State Estimation (later)…



u Improved Visualization:Stability margins, geographic views of congested paths, unusual angle differences

u Prevent Cascading Events:Quickly identify imminent cascading events

u Dynamic Instability Prediction:Fast and accurate instability prediction

wWarning signals

wEarly detection



u New advanced EMS applications:Innovate new EMS applications to fully exploit PMU data, Decision support tools

uWide Area Monitoring and Control:

wDevelop an adaptive protective scheme to protect “the power system grid as an entity”.


Improved Visualization UI


PMU AllocationObjectives

u Deploy the PMUs based on the following questions:

wWhat is the problem to solve?

wWhat are the measurements that we need?

wHow often we need these measurements?

u Placement strategies based on problems being solved:

wQuasi steady-state conditions:Increase observability and controllability

wDynamice conditions:Capture critical local dynamics without complete observability. Locate to identify make inter-area modes observable


PMU integration issues for EMS

u Need for upgraded communication systems

u Communication delays and latency

u Calibration and accuracy of PMUS

u Calibration among different PMU vendors

u Accuracy under off nominal frequency conditions

u Efficient and reliable storage, archiving and retrieval


Dynamic Analysis functions

u PMU Measurements – in milli-seconds

u Improve visualization of voltage dynamic events (slow decline)

u Dynamic triggering based on PMU warning signals

wFrequency decline or rate of frequency

wSlow voltage decline or specific load level

wConsiderable phase angle separation on remote locations

w Inter-area oscillations

wCascading

u Use PMUs to provide early warning alerts!


Dynamic functions-PMU/PDC

VoltageInstabilityVoltage

Instability

Small signalInstability

Small signalInstability

TransientInstability

TransientInstability

PMULocal

SCADA

PMULocal

SCADA

Triggers

Frequency decline

Rate of frequency

Slow voltage decline

Specific Load level

Margin decline

Considerable angle separation

Inter-area oscillations

Cascading

Triggers

Frequency decline

Rate of frequency

Slow voltage decline

Specific Load level

Margin decline

Considerable angle separation

Inter-area oscillations

Cascading


Voltage instability prediction function

u Tens of seconds and minutes time frame

wProvide to the operator sufficient information about the stability margin i.e. P-V, Q-V plots for a specific corridor

wAlarm the PMU measurement values outside limits

Voltage instability prediction

~10 seconds

Voltage instability prediction

~10 seconds

Slow Voltage decline or Load level?


Capacitor SwitchingReactor SwitchingSVCUVL sheddingRemedial actionsHigh speed trips



Small signal instability prediction function

uMinutes time frame

wDetect power swings in the network

wProvide direct observation of inter-area oscillations modes

wThis is faster than the computation of eigenvalues using a detail model of a specific configuration

Inter-area and Local OscillationsInter-area and Local

Oscillations

Small signalinstability prediction~minutes

Small signalinstability prediction~minutes

PSS (Stabilizers)PSS (Stabilizers)


Angle instability prediction function

u Less than one second time frame

wStability margins presented to the operator

wFocus on reducing the stability swings via: generator tripping and capacitor/reactor switching control actions

Frequency decline?Frequency decline?

Angleinstability prediction

~milliseconds

Angleinstability prediction

~milliseconds

Controlled islandingGenerator trippingDynamic brakingUFL sheddingFast Load sheddingFACTS, HVDC etc.Remedial actionsHigh speed trips

Controlled islandingGenerator trippingDynamic brakingUFL sheddingFast Load sheddingFACTS, HVDC etc.Remedial actionsHigh speed trips


Real-Time Trending of Stability Margin


Frequency stability function

u Seconds and minutes time frame

wDetect generation/load imbalances

wEstimate impact of the imbalance on the load’s response and generators’ inertias

w If the estimated frequency is not acceptable, provide recommendations to operator to bring frequency back


PMUs & Wide-Area Implementations

u Wide-area Monitoring

w PMU technology at selected locations

w Vulnerability detection:

l angle difference, frequency and voltage rate of change

u Wide-area Protection

w Treat the grid like a device to be protected

w Selectivity, Robustness and Dependability

w Fast communication

u Wide-area Control

w Preventive/Corrective

w Adaptive Islanding

l Identify coherent groups of generators online

w Emergency

w Restorative


Wide Area Control

uGrid Protection, In the Future:

Develop protective control schemes that dynamically adapt to current power system conditions, to preserve the integrity of the power system grid as an entity.


Wide Area Control Framework

Reaction to catastrophes and Feedback Control

Voltage stability

~10 seconds

Small SignalStability

~minutes

Transient Stability

~milliseconds

Adaptive Restoration

~minutes

Wide-area State Estimation

~secondsControlled islandingGenerator trippingDynamic brakingUFL sheddingFast Load sheddingFACTS, HVDC etc.Remedial actionsHigh speed trips

PSS (Stabilizers)


Unit restartResynchronizationLoad restorationOther control actions

Inter-area and Local Oscillations


Frequency decline?

Margin decline or cascading?

Substation

SE

~milliseconds

Substation

SE

Substation

SE

PMUs


SE uses SCADA data to determine (every 1-5 minutes) a ‘best estimate’ of the current power system state:

Voltages, Angles, MW/MVAR flows, CB status, taps, etc

What is State Estimation (SE)?

One of the key solution variables in SE is the: bus voltage phase angle.

PMUs can now provide the direct measurement of voltage phase angle as well as current phasors.


StateEstimation

PMU PMUPMU

PDC

ContingencyAnalysis

SecurityEnhancement

DynamicSecurityAnalysis

Marketrevenue

sensitivities

OptimalPower Flow

SCADA

NetworkModel

ICCP &Other

SimultaneousFeasibility

Test

SE’s Role in Power System Operations

State Estimation has become a critical, ‘must-run successfully’ control center function.


Comparison of SE output with PMU Measurementswithin a few degrees!

courtesy BPA


uSE time frame is in seconds

uPMU data is ~30 or more samples per second

uPMU data needs to be merged with SCADA data

uStatistics for performance, accuracy and robustness

uEnable/Disable capabilities of PMU devices

uUtilize PMU data in neigboring external areas

SE use of PMUs

Issues


Existing SE Software

u PMU data is automatically used (whenever available) as input data for the SE solution algorithm:

wVoltage phasor data

wCurrent phasor data


A more Robust SE with PMU data

Synchronized Phasors

PMUPMU

PDC- Utility A

Time point Tables for all PMU

Processed data

Monitoring

Applications Input

PMUPMU

PDC-Other utilities


Processed data

Monitoring

Applications Input

PDC-Other utilities


Processed data

Monitoring

Applications Input

SCADA

Voltages

Currents

Frequency

SCADA

Voltages

Currents

Frequency

PMU Data Processing

PMUPMU

PMUPMU

GPSGPS

Local/Global warning signals

Robust State Estimation

i-Substation

Localized SE

n-Substation

Localized SE


Recent SE Experience with PMUs

u Demonstrate benefits of using real-time PMU data on SE

wUse real-time data snapshot from the control center SE

u Perform Studies to assess:

wPMU Sampling Impact on SCADA data

wPMU Local and Global Impact

wUse PMU data from neighboring external systems

wAccuracy of SE solution

wRobustness of SE solution

wReliability of SE solution over time

uOnsite demonstrations


Benefits Realized:

u SE quickly identified bad measurement data at the TVA PDC:

wSome values were off by sq. root of 3, some scaling issues; some were off by 120 degrees…

u PMU data accuracy class was less than we had hoped.

wOngoing EIPP/IEEE standards work will help

uWith just relatively few PMU data (compared to thousands of SCADA data), only local benefits were realized.

wNeed many more PMUs relative to SCADA data to see global benefits

u Substation topology telemetry errors/anomalies were identified (big help for the SE analyst!)

u Need for enhanced metrics to evaluate SE solution performance

u Need to evaluate side-by-side with an operational SE

wAugment operational SE SCADA data with new PMU data


Next Steps….PMU-SE Evaluation project continues

uParticipants:

wTVA, Entergy, Manitoba Hydro, Idaho Power, PG&E, ORNL, NE Univ, First Energy*, BPA*

uObjectives:

wAutomate PMU/PDC data transfer into the EMS

wImplement a parallel online SE in control center

wSimulate growth of PMUs for next few years and perform case studies to evaluate benefits

wImplement comprehensive SE metrics to faciltate evaluation of SE performance


Future of SE?

Independent of SCADA and Network ModelLinear SE?

Entire electrical interconnection

PMUs: Growth

V & angle

V & angle

V & angle

MW ~ angle diff

MW ~ angle diff

»System becomes

observable with around 50% stations

with PMU


Making Decisions in Control Centers

REACTIVE

PREVENTIVE

PREDICTIVE

PROACTIVECourtesy of PNNL


u Look-ahead simulation for real-time system prediction and disturbance mitigation

u Framework for Decision Support Systems

Advanced Situational Awareness & Decision Support System


Documents

Phasor Measurements: Impact on EMS Control … · AREVA T&D Inc June 5-6/2006. 2 CIGRE Conference – June 05-06, 2006 2 ... SVC UVL shedding Remedial actions High speed trips Capacitor