Power System Controls: Today and Futureieeepes.feit.ukim.edu.mk/bose_ieee_distlec_mk.pdf ·...
Transcript of Power System Controls: Today and Futureieeepes.feit.ukim.edu.mk/bose_ieee_distlec_mk.pdf ·...
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College of Engineering and Architecture
Power System Controls: Today and Future
Anjan BoseWashington State University
Pullman, WA, USA
IEEE Distinguished Lecture
Skopje, Macedonia
May, 2010
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College of Engineering and Architecture
What is a SMART Grid?
• Self-heals
• Motivates and includes the consumer
• Resists attack
• Provides power quality for 21st century needs
• Accommodates all generation and storage options
• Enables markets
• Optimizes assets and operates efficiently
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College of Engineering and Architecture
Transmission vs Distribution
• Smart Meters
• Demand side load control
• Distribution automation (including two-way flow)
• Micro-grids
• Real-time pricing
Will talk mainly about Transmission
• Prevent cascading blackouts
• Wide-area control
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College of Engineering and Architecture
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College of Engineering and Architecture
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College of Engineering and Architecture
Balancing Authorities
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College of Engineering and Architecture
West European Power Grid
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College of Engineering and Architecture
XinJiang AutonomousRegion
South
CentralEast
Northwest
North
NortheastChina GridChina Grid
1 BTB
HVDC
3 HVDC
1 500kV AC
2 parallel 500 kV AC
1 HVDC
Tibet
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College of Engineering and Architecture
Communication for Power System
Control Center
RTU RTU RTU
Third Party•Analog measurements
•Digital states
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College of Engineering and Architecture
Substation Automation
• Many substations have
� Data acquisition systems at faster rates
� Intelligent electronic devices (IED)
� Coordinated protection and control systems
� Remote setting capabilities
• Data can be time-stamped by satellite
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College of Engineering and Architecture
Phasor Measurements
Super PDC
PDC PDC PMU
PMU PMU PMUPMUPMU
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College of Engineering and Architecture
Monitoring the Power Grid
• Alarms
� Check for overloaded lines
� Check for out-of-limit voltages
� Loss of equipment (lines, generators, feeders)
� Loss of communication channels
• State estimator
• Security alerts
� Contingencies (loading, voltage, dynamic limits)
� Corrective or preventive actions
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College of Engineering and Architecture
Control of the Power Grid• Load Following – Frequency Control
� Area-wise� Slow (secs)
• Voltage Control� Local� Slow to fast
• Protection� Local (but remote tripping possible)� Fast
• Stability Control� Local machine stabilizers� Remote special protection schemes� Fast
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College of Engineering and Architecture
Communication for Power System (proposed)
Networks
Substation
Substation
Substation
Control Center
Third Party
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College of Engineering and Architecture
Proposed Communications
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College of Engineering and Architecture
Each Application – Different Data
• Monitoring at the control center
� Needs all data points
� But at slow rates (every few seconds)
• Special Protection Schemes
� Needs few data points
� But at fast rates (many times a second)
• Each application must access this data in a different way
� Moving real time data from source to application is a complex optimization task
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College of Engineering and Architecture
Basic GridStat Functionality
Publishers Subscribers
AreaController
Management Plane
Area Controller
Load Following
…
Generator
ISO
…
Wide Area Computer Network
(Data Plane)
QoS Control
QoS Meta-Data
US/EU-WideMonitoring?(future??)
QoS Requirements
PMU
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College of Engineering and Architecture
Data Base Issues
• Real time data base must be distributed
� Large amounts of calculated data must be part of this data base
• Static data base must be distributed
• Historical data base will require still another design
• Substation data bases and system level data bases have to be coordinated
• All data bases in the same interconnection will have to be coordinated
• Standards will be key
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College of Engineering and Architecture
What is Wide Area Control?
• Wide area implies ‘not local’ i.e. input-output signals not confined to one substation
• Control implies a controller that uses measurements as input signals to compute output signals for control equipment
• Input signals: frequency, currents, voltages, phase angles, watts, vars, switch status, etc.
• Output signals: generator output, transformer taps, HVDC, SVC, UPFC, switch status
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College of Engineering and Architecture
What is Wide Area Control?
• Control also implies computation
� Detection of emergencies
� Identification of emergencies
� Calculation of controls
• ‘Wide area’ also implies communication
� Signals are sampled (digital)
� Signals have time delays (latency)
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College of Engineering and Architecture
What WACs are feasible?
• Slow control (10-seconds)
� AGC
� Regional voltage control
� Phasor measurements not needed
• Oscillation control (seconds)
• Transient stability control (sub-seconds)
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College of Engineering and Architecture
What have we learnt?
Technology is available for ad hoc development and demonstration of WACs
� Have a good idea
� Test on simulations
� Design the prototype• Measurements needed
• Point-to-point communications needed
• Controls needed
� Install and test on real time data
� Close the loop
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College of Engineering and Architecture
What have we learnt?
Systematic development of WACs will require
• Communications infrastructure
� Networked, high-bandwidth
� User-friendly applications level middleware
• Detection/identification algorithm development
• Controller design process
� Determining best inputs, outputs
� Developing output calculations
• Off-line testing methods
� Nonlinear, digital simulations
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College of Engineering and Architecture
State Estimator
HIERARCHICAL STATE
ESTIMATOR
HIERARCHICAL STATE
ESTIMATOR
BA SEBA SE
BA SEBA SE
RC SE
COMMUNICATION NETWORKCOMMUNICATION NETWORK
RC EMS
BAEMS
BAEMS
BAEMS
BAEMS
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College of Engineering and Architecture
Two-Level Linear State Estimator
• Substation Level
� Substation Model
� Circuit Breaker State Estimator
� Bus Voltage State Estimator
� Bad Data Detection & Identification
• Control Center Level
� System Model
� Topology Processor (system level)
� State Estimator
� Bad Data Detection & Identification
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College of Engineering and Architecture
Database & Communication Architecture
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College of Engineering and Architecture
Substation Level LSE
• Zero-Impedance Current State Estimator
� Circuit Breaker Oriented Substation Model
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College of Engineering and Architecture
� Analog State Estimation• State:
� Currents on Circuit Breakers
• Measurements:
� Injection Currents to Nodes:
� Currents on Circuit Breakers:
• Measurement Functions
� Kirchhoff’s Current Law
� Identity Matrix
� Formula:
Substation Level LSE
inj injKCL
cb cb
z rAz = = x + = Hx + r
Iz r
cbz
injz
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College of Engineering and Architecture
• Zero-Impedance Voltage State Estimator
� State:• Complex Bus Voltages
� Measurements:• Voltage from PMUs
� Measurement Functions
� Solutions:
Substation Level LSE
~ ~ ~ ~ ~ ~
1
1
1
z = H x+ r x+ r
=
M2 1,2 1 ,
1
2 1,2 1
1
m
i i i real
ireal m
i i
i
w z
x
w
− −
=
− −
=
=
∑
∑
2 ,2 ,
1
2 , 2
1
m
i i i im a g
iim a g m
i i
i
w z
x
w
=
=
=
∑
∑
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College of Engineering and Architecture
Control Center Level LSE• Topology Processor
� Merging Substation Topologies (STDFs)
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College of Engineering and Architecture
• State Estimation
� States• Complex Bus Voltages
� Measurements (Phasor)• Bus Voltages
• Two Direction Branch Currents
• Injection Currents
� Measurement Functions
Control Center Level LSE
11
22
bus
b
b
b
b
inj
V I
YIz = = Hx + r = x + r
YI
YI
%
%%% % %% % %
%%
%%
busV%
1bI%
2bI%
injI%
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College of Engineering and Architecture
Transitional Multi-Area State EstimatorDatabase & Communication Architecture
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College of Engineering and Architecture
• State Estimation - Whole System
� Linear Area
� Non-linear Area
� Boundary Buses
Transitional Multi-Area State Estimator
1 1
,int ,b
,int ,b
Min ( )
s.t. [ , ]
( ) ([ , ] )
p qT
i i i j j j
i j
T T T
i i i i i i i i
T T T
j j j j j j j j
r Wr r W r
z H x r H x x r
z h x r h x x r
= =
+
= + = +
= + = +
∑ ∑%% %
% %% %% % % %
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College of Engineering and Architecture
Conclusions
• Controls at the substation level get more sophisticated every day
• Real time data collection increases at the subs
• Utilizing these measurements and controls at the system level remains difficult
• The communication infrastructure to move this data has to be built
• The software infrastructure to handle the data has to be built
• Only then can the smart grid applications be implemented