System-Wide Centrally Coordinated
P
Power
S
System
t O
Operation
ti and
dC
Control
t l
Challenges
g & Future Directions
CMU March 13, 2012
B. Fardanesh
New York Power Authority
The Ideal Control Scenario- Centrality
Limits &
Security
Criteria
System
Central
Controller
System Topology &
St t Estimator/
State
E ti t /
System Model Update
Power
System
MW/MVAR
Injection & Flow
Control Action
Area
j
Area
k
Economy
and Other
Objectives
Model-Based
Trajectory Planner/
Control Calculator
Area
i
Measurements
How Feasible?
2
Limitations:
• Structural: Geographically Distributed Nature
Communications
• Computational Speed
• Existence of Controllers
Control Bandwidth
Infrastructure
3
Relying
l i on Margini No Coordinated
C di
d Active
A i Steering
S i
Price Paid in Performance & Cost
Power
System State
Initial State
Ideal
Response
Time
Optimum
p
Final State
Reset
Action
Violations
Today’s
Response
Instability
4
Solution- A Way Out
• Can still exert Centrality and Coordinated
Control via Hierarchical (Multi-Level)
Control
• Offers a Divide and Conquer Capability
• Complex
l in
i its
i True Form
5
Hierarchical (Multi-Level) Control Structure
System-Wide Controller/Coordinator
Area Central
Controller
Area Central
Controller
Area Central
Controller
Power Flow
Information/Signal Flow
Cluster
Controller
Cluster
Controller
6
The Main Premise:
Minimization of operating margins or
maximum utilization of existing transmission
assets with heavier reliance on traditional as
well as new control equipment,
equipment taking full
advantage of high-bandwidth integrated and
centrally-coordinated
ll
di
d controll off power
injections and flows, with increased system
security and reliability.
7
Power System Operating Limits
• Transient and Small-Signal
Stability
• Voltage
V lt
Stability
St bilit
• Thermal
8
Maximum Thermal Limit
Voltage Limit
Id
dentify T
True Limits---Shrrink Marg
gins
While m
meeting R
Reliabilitty criteriia
Uncertainty in Computed Limits
On-Line (Dynamic) Rating
Inexpensive Limit Enhancer/Remover
On-Line Fast Security Assessment
Increased Confidence in Models
Small Signal Limit
Actual Operating Limit
Uncertain Limits
System-Wide Automatic Coordination
Intelligent Tools to Advise Operators
Crisp Limits
9
P
Power
S
System Control
C
l Mechanisms
M h i
• Injection
I j i (Shunt)
(Sh ) Controllers
C
ll
– Generator/AVR/PSS; Fixed Shunt
Capacitors/Reactors(no fine control); Shunt
FACTS Devices
• Routing (Series) Controllers
– Fixed Series Capacitors/Reactors(no fine
control) ; Phase-Shifters, Tap Changing Under
Load Transformers (step-wise
(step wise slow control);
Series FACTS Devices
10
Centralized Coordination
• A simpler form of Hierarchical Control:
Centralized Set-Point Coordination
• Separate
p
P and Q - Further Decomposition
p
• System-wide Automatic (Closed-Loop) Real
Power Control Existing for Years
• System-wide Closed-Loop Reactive Power
Control Not Quite Yet!
Control--Not
• Sacrifices Made:
Degraded Performance
g Margin
g Requirements
q
Large
11
To Reduce Margins
System-Wide
Automatic (Closed-Loop)
Control/Coordination for
Real/Reactive Injection &Flow
Computational
Speed and Algorithms
12
M ki a C
Making
Case ffor Additional
Additi l andd Faster
F t
Coordinated Controls:
Then we will have to:
 Squeeze
S
more off the
th existing
i ti margins
i on th
the power
system
 Expand the transmission capability via compensation
both fixed and variable
 Build only in new or existing substations and/or
underground to deal with NIMBY or BNANA
 Rely on additional and Faster Coordinated Controls
Operating with Less Margin Means More Reliance on Controls
13
Compensation and Control Solutions
• Usually a Hybrid of Switched Fixed and Vernier
Control
Controller Requirements:
• Reliability/Redundancy
• Adaptability
• Flexibility
Voltage-Sourced Converter (VSC) Based Controllers
offer such Potential
14
S t
System-wide
id Automatic
A t
ti Power
P
Control
C t l
(
(SAPC)
)
• Centrally-Coordinated Hierarchical Real Power
Control
Co
o too achieve
ac eve Maximum
a
u Utilization
U
a o closer
c ose too
Thermal Capacity of Transmission System
- Stabilization
- Frequency Control
- Coordinated
di
d MW Injection
j i andd Flow
l Controll
- Phase-Angle Equalization and
Reduction across the system
y) the need for Transmission
- Reduce ((Delay)
Expansion
15
S t
System-wide
id Automatic
A t
ti Voltage
V lt
Control
C t l
(
(SAVC)
)
• Centrally-Coordinated Hierarchical Voltage
C
Control
l to achieve:
hi
- Voltage Stability
- Voltage Profile Control
- Coordinated MVAr Injection and Flow
Control
- Maximum Distance to Voltage Collapse
- Reduced or Minimized Losses
16
What is Needed?
Hardware:
 Fast-acting MW/MVAr injection/absorption and flow
controllers
t ll including
i l di fast-dynamics
f td
i generators
t and/or
d/ energy
storage devices
 Adequate highly reliable less expensive VSC
VSC-based
based controllers
 Abundant highly reliable high-bandwidth communication
networks
 EHV level solid-state or power electronics based breakers to for
increased stability
 System-wide synchronous measurements for robust and fast
state and pparameter feedback
17
What is Needed?
Algorithms and Faster Computing:
 Criteria for selection of feedback quantities for coordinated
closed-loop power injection/flow control
 Determination of appropriate response rates of closed control
loops
 Robust, adaptive, high-bandwidth control algorithms for largescale structurally decentralized dynamic systems
 Faster computation capability to approach real-time optimization,
coordination and control
 Proven robust hierarchical control algorithms to overcome the
limitations in achieving wide-area integrated centralized
controller performance
 System/equipment model identification and validation tools
 Faster algorithms for system topology and state estimation
 Parallel
ll l algorithms
l i h andd faster
f
computers
18
System Voltage and Current Phasors
from all IEDs (Relays, DFRs,
PMUs, Metering, SCADA, RTUs
and PQ Monitors)
System Topology (Breaker
Status)
Super
Ca b a o
Calibrator
Database – CIM;
Data Correlation;
Analysis, Archive
Other Measurements
Temperatures
(equipment and
ambient), Pressures,
Sags, Dissolved gas in
oil, Mechanical
(vibration, air-gap,
etc.), Leakage currents,
Battery Monitors, PT,
CT conditions, etc.
Other Substations
or Generating
Stations
...
Alarms
A th i d
Authorized
LAN/WAN
Access
Secure
Power LAN
(Redundant)
Real-Time
Filtered,
Certified
Data
Secure Communications
Backbone
From other stations’
Super Calibrator
Operations/Control
Center -- EMS
Visualization
Vi li ti
State Estimation/State
Solution/Dynamic State Solution
Automatic
Feedback
Topology/Parameter Estimation and Identification
Model Identification/Enhancement
Voltage/MVAr Coordination; loss minimization
SPS/RAS Enable/Disable
Stability Monitoring and Control
Fault/Outage Management
Contingency Analysis/Security
Response Adequacy Measurement and
Monitoring
Power Quality Monitoring/Enhancement
Resource Adequacy,
q y Resource Commitment,
Scheduling, Markets
Advice to the
System Operator
Automatic
Feedback to
Other Stations
Alarms
Inteelligent Use off Sensinng and C
Commuunications
A Futuure Archhitecturre for Poower Syystems
Operrations and Coontrol
Substation or
Generating
Station
Direct Non-Iterative State
Estimation: A New Paradigm
0
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3
• A direct one-shot solution for the state of a
power system is
i now possible
ibl
• Full AC solution
• No more iterations
• No reliance on the “goodness” of the initial
guess
g
• An envisioned faster more robust solution
241.5
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10
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0
0  t12    130 
  

0
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0
 14.25  1989  1
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 241.5 2849
 64
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 120
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
 1125.5  11893 850
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
529
 50
  64.5
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A Simple Example
60
156
337
 17
0
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0
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0
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26
385
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0.5
 117
0
10
0
48
0
1
1
23.5
0
 100
0
 586
0
3
0
5
1
0
4
0
5
 351  25
 15
 0.75
 9.75
 1700
 17
1
0
0
0
9.5
117
0
1
0
 55  2120 95  40  1170
500
 61 101
 60  31
1
5
 15
 1.5  1.5
382
300
3
 50
 35
0
95
 10
 0.5
11700
0
0
5
 12
1
17
0
0
5
0
 100
0
60
0
5
0
0.5
 1.5
10
1
0  t1   1020 
 
 9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0
0  t6   0 
10
 3  t7   0 
   

0
 3  t8   0 
 
0
 15 t9   2210 



0
 5  t10   2465
  

 50  3  t11    754 
0
0  t12    130 
  

0
0  t13   145 
0
0  t14   0 
0
 14.25  1989  1
 30
0.5
0
 25
0
5
0
• Redundant Polynomial Equations
x1
 2 x1 x 2  x 3
2
241.5
 64

163.5

 13.5
 90

 0
 0

 0
 162

.5
1125

 231
 8

 64.5
 0
2 x2 x3  x2
2849
2
0
60
337
0
7.5
 x2
2
0  t1   1020
 
9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0
5 1
0
117 0 0  t6   0 
0
0
10 3  t7   0 
100 0 4
  

0
0 5
0
0 3  t8   0 
1
 
0
0 15 t9   2210
586 351 25 9.5



1170 382 50 95 11700 0 5  t10 2465
  

500 300 35 10
0 50 3  t11  754
5
3
0 0.5
0
0 0  t12  130





10
1
0
5 100 0 0  t13  145 
1
17 0
0
0
0 0  t14  0 
0
85
0
 2 x1
0
260 156 17 10 6
0
1667 120 12 321 15 1.5 175
0
0
97 26 0
10
1
10
0
0 118 0
5
0
0
85
0
29
5
0
3042 430
11893 850
0
26
26
385
55
9.5
0
0.5
117
2120
2600
26
529
0
61 101 60 31
15 1 1.5 1.5
5 60 5 0.5
0 1.5
12 0
0
0
10 1
0 1
48 23.5
95 40
14.25 1989 1
7 x1
x1
0
 241.5 2849
 64
0
260

  163.5 1667
 120

97
 26
  13.5
  90
10
0

0
 85
 0
 0
0
29

5
0
 0
  162
3042
430

 1125.5  11893 850

 2600 115
 231
 8
 26
 25

 50
529
  64.5
0
0
 0
60
337
0
7.5
0
 85
2
0
 2 x2 x3  x3
2
 x2
 14.25  1989
2
0  t1   1020 
 
 9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0  t6   0 
 3  t7   0 
 

0
 3  t8   0 
 
0
 15 t9   2210 





 2465
0
 5  t10
  

 50  3  t11    754 
0
0  t12    130 

  
0
0  t13   145 
0
0  t14   0 
1
 10
0 30 0.5
0 25
20 0
15 1700 0
0
3 0.75 17 5
0
0 9.75 1
0
5 x1 x 3  x1 x 2  3 x 3  x 2
115
25
50
0
 8
2
2
 26
 5 x 3   11
 5 x 2 x 3  12 x 1   13
0
 241.5 2849
 64
0
260

  163.5 1667
 120

 26
97
  13.5
  90
10
0

 85
0
 0
 0
0
29

5
0
 0
  162
3042
430

 1125.5  11893 850

 2600 115
 231
 8
 26
 25

529
 50
  64.5
0
0
 0
60
156
 12
0
0
0
26
337
 17
321
10
118
 9.5
0
0
 10
 15
1
0
0
10
7.5
6
 1.5
0
5
0
1
0
0
175
0
0
0
 100
 85
0
20
0
0
5
0
0  t1   1020 
 
 9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0  t6   0 
 3  t7   0 
 

0
 3  t8   0 
 
0
 15 t9   2210 



0
 5  t10   2465
  

 50  3  t11    754 
0
0  t12    130 
  

0
0  t13   145 
0
0  t14   0 
 14.25  1989  1
0
 30
0.5
0
 25
 15
 1700
0
0
 0.75
 17
3
5
 9.75
1
0
0
1
0
117
0
4
0
0
10
• Dual Transformation and Direct One-Shot Solution
 30
0
3
0
1
4
0.5
 15
 0.75
 9.75
0
0
0
 25
0
 1700
5
 17
0
1
117
0
0
10
26
0.5
0
0
0
1
5
385  117
48 23.5  586  351  25
 55  2120 95  40  1170 382  50
 61 101
 60  31
500
300  35
 15
 1.5  1.5
1
5
3
0
5
5
60
0.5
10
1
0
0
9.5
95
 10
 0.5
5
1
0
11700
0
0
 100
0
0
156
 12
0
0
0
26
 12
 17
321
10
118
 9.5
0
0
 10
 15
1
0
0
10
0
6
 1.5
0
5
0
1
 1.5
0
175
0
0
0
 100
1
0
20
0
0
5
0
17
0
26
0.5
0
385  117
48
 55  2120 95
 61 101
 60
 15
1
 1.5
5
60
5
 12
0
0
1
0
0
5
23.5  586  351  25
 40  1170 382  50
 31
500
300  35
 1.5
5
3
0
0.5
10
1
0
 1.5
1
17
0
0
9.5
95
 10
 0.5
5
0
1
0
11700
0
0
 100
0
0
 241.5 2849
 64
0
260

  163.5 1667
 120

97
 26
  13.5
  90
10
0

0
 85
 0
 0
0
29

5
0
 0
  162
3042
430

 1125.5  11893 850

 2600 115
 231
 8
 26
 25

529
 50
  64.5
 0
0
0
60
156
337
 17
0
 10
7.5
6
0
0
 85
0
 12
0
0
321
10
118
 15
1
0
 1.5
0
5
175
0
0
20
0
0
0
26
26
385
 9.5
0
0.5
 117
0
10
0
48
0
1
1
23.5
0
 100
0
 586
0
3
0
 15
 0.75
 9.75
 1700
 17
1
0
0
0
9.5
117
0
1
0
A Power System State Estimator/Solver
5
1
0
4
0
5
 351  25
 55  2120 95  40  1170
500
 61 101
 60  31
1
5
 15
 1.5  1.5
382
300
3
 50
 35
0
95
 10
 0.5
11700
0
0
5
 12
1
17
0
0
5
0
 100
0
60
0
5
0
0.5
 1.5
10
1
0  t1   1020 
 
 9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0
0  t6   0 
10
 3  t7   0 
   

0
 3  t8   0 
 
0
 15 t9   2210 



0
 5  t10   2465
  

 50  3  t11    754 
0
0  t12    130 
  

0
0  t13   145 
0
0  t14   0 
0
 14.25  1989  1
 30
0.5
0
 25
0
5
0
• Bus power injection equations in Rectangular from
• Naturally in the desired form:
Vi
241.5
 64

163.5

 13.5
 90

 0
 0

 0
 162

.5
1125

 231
 8

 64.5
 0
=ai + jbi
2849
0
60
337
0
7.5
0  t1   1020
 
9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0
5 1
0
117 0 0  t6   0 
0
0
10 3  t7   0 
100 0 4
  

0
0 5
0
0 3  t8   0 
1
 
0
0 15 t9   2210
586 351 25 9.5



1170 382 50 95 11700 0 5  t10 2465
  

500 300 35 10
0 50 3  t11  754
5
3
0 0.5
0
0 0  t12  130





10
1
0
5 100 0 0  t13  145 
1
17 0
0
0
0 0  t14  0 
0
0
260 156 17 10 6
0
1667 120 12 321 15 1.5 175
0
0
97 26 0
10
1
10
0
0 118 0
5
0
0
85
0
29
5
0
3042 430
11893 850
0
26
26
385
55
9.5
0
0.5
117
2120
2600
26
529
0
61 101 60 31
15 1 1.5 1.5
5 60 5 0.5
0 1.5
12 0
0
0
10 1
0 1
48 23.5
95 40
85
0
14.25 1989 1
0 30 0.5
0 25
20 0
15 1700 0
0
3 0.75 17 5
0
0 9.75 1
0
ReY . a a  b b   ImY . a b
N
ij
i l
j i
j i
115
25
50
0
ij
i
j
 a jbi   PG j  PD j
 ReYij . a j ai  aibj   ImYij . ai a j  bjbi   QG j  QD j j  2,N
N
i l
0
 241.5 2849
 64
0
260

  163.5 1667
 120

97
 26
  13.5
  90
10
0

0
 85
 0
 0
0
29

5
0
 0
  162
3042
430

 1125.5  11893 850

 2600 115
 231
 8
 26
 25

 50
529
  64.5
0
0
 0
337
0
7.5
0
 85
0
 17
321
10
118
 9.5
0
 10
 15
1
0
0
10
6
 1.5
0
5
0
1
0
175
0
0
0
 100
0
20
0
0
5
0
 30
0
3
0
1
4
0.5
 15
 0.75
 9.75
0
0
0
 25
0
 1700
5
 17
0
1
117
0
0
10
26
0.5
0
0
0
1
5
385  117
48 23.5  586  351  25
 55  2120 95  40  1170 382  50
 61 101
 60  31
500
300  35
 15
 1.5  1.5
1
5
3
0
5
5
60
0.5
10
1
0
0
9.5
95
 10
 0.5
5
1
0
11700
0
0
 100
0
0
 12
 14.25  1989
0  t1   1020 
 
 9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0  t6   0 
 3  t7   0 
 

0
 3  t8   0 
 
0
 15 t9   2210 





 2465
0
 5  t10
  

 50  3  t11    754 
0
0  t12    130 

  
0
0  t13   145 
0
0  t14   0 
60
156
 12
0
0
0
26
1
0
 241.5 2849
 64
0
260

  163.5 1667
 120

 26
97
  13.5
  90
10
0

 85
0
 0
 0
0
29

5
0
 0
  162
3042
430

 1125.5  11893 850

 2600 115
 231
 8
 26
 25

529
 50
  64.5
0
0
 0
60
156
 12
0
0
0
26
337
 17
321
10
118
 9.5
0
0
 10
 15
1
0
0
10
7.5
6
 1.5
0
5
0
1
0
0
175
0
0
0
 100
 85
0
20
0
0
5
0
0  t1   1020 
 
 9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0  t6   0 
 3  t7   0 
 

0
 3  t8   0 
 
0
 15 t9   2210 



0
 5  t10   2465
  

 50  3  t11    754 
0
0  t12    130 
  

0
0  t13   145 
0
0  t14   0 
 14.25  1989  1
0
 30
0.5
0
 25
 15
 1700
0
0
 0.75
 17
3
5
 9.75
1
0
0
1
0
117
0
4
0
0
10
• Other Measurement equations have similar form
0
0
 1.5
1
17
0
26
0.5
0
385  117
48
 55  2120 95
 61 101
 60
 15
1
 1.5
5
60
5
 12
0
0
1
0
0
5
23.5  586  351  25
 40  1170 382  50
 31
500
300  35
 1.5
5
3
0
0.5
10
1
0
 1.5
1
17
0
0
9.5
95
 10
 0.5
5
0
1
0
11700
0
0
 100
0
0
 241.5 2849
 64
0
260

  163.5 1667
 120

97
 26
  13.5
  90
10
0

0
 85
 0
 0
0
29

5
0
 0
  162
3042
430

 1125.5  11893 850

 2600 115
 231
 8
 26
 25

529
 50
  64.5
 0
0
0
Envisioned Benefits
•
•
•
•
60
156
337
 17
0
 10
7.5
6
0
0
 85
0
 12
0
0
321
10
118
 15
1
0
 1.5
0
5
175
0
0
20
0
0
0
26
26
385
 9.5
0
0.5
 117
0
10
0
48
0
1
1
23.5
0
 100
0
 586
0
3
0
5
1
0
4
0
5
 351  25
 15
 0.75
 9.75
 1700
 17
1
0
0
0
9.5
117
0
1
0
 55  2120 95  40  1170
500
 61 101
 60  31
1
5
 15
 1.5  1.5
382
300
3
 50
 35
0
95
 10
 0.5
11700
0
0
5
 12
1
17
0
0
5
0
 100
0
60
0
5
0
0.5
 1.5
10
1
0  t1   1020 
 
 9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0
0  t6   0 
10
 3  t7   0 
   

0
 3  t8   0 
 
0
 15 t9   2210 



0
 5  t10   2465
  

 50  3  t11    754 
0
0  t12    130 
  

0
0  t13   145 
0
0  t14   0 
0
 14.25  1989  1
 30
0.5
0
 25
0
5
0
Direct State Estimation
More robust– No more iterations
N reliance
No
li
on the
h initial
i i i l guess
Faster– Perhaps
p limited onlyy byy the
communication links’ latency
• A much more “dynamic”
dynamic assessment of the
system conditions and behavior
• Potential for ultimate use in closed-loop
closed loop
and automatic control of power systems
0
 241.5 2849
 64
0
260

  163.5 1667
 120

97
 26
  13.5
  90
10
0

0
 85
 0
 0
0
29

5
0
 0
  162
3042
430

 1125.5  11893 850

 2600 115
 231
 8
 26
 25

 50
529
  64.5
0
0
 0
241.5
 64

163.5

 13.5
 90

 0
 0

 0
 162

.5
1125

 231
 8

 64.5
 0
337
0
7.5
0
 85
0
 17
321
10
118
 9.5
0
 10
 15
1
0
0
10
6
 1.5
0
5
0
1
0
175
0
0
0
 100
0
20
0
0
5
0
 30
0
3
0
1
4
0.5
 15
 0.75
 9.75
0
0
0
 25
0
 1700
5
 17
0
1
117
0
0
10
26
0.5
0
0
0
1
5
385  117
48 23.5  586  351  25
 55  2120 95  40  1170 382  50
 61 101
 60  31
500
300  35
 15
 1.5  1.5
1
5
3
0
5
5
60
0.5
10
1
0
0
9.5
95
 10
 0.5
5
1
0
11700
0
0
 100
0
0
 12
0
0
 1.5
1
17
0
 14.25  1989
0  t1   1020 
 
 9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0  t6   0 
 3  t7   0 
 

0
 3  t8   0 
 
0
 15 t9   2210 





 2465
0
 5  t10
  

 50  3  t11    754 
0
0  t12    130 

  
0
0  t13   145 
0
0  t14   0 
60
156
 12
0
0
0
26
1
2849
0
60
337
0
7.5
0  t1   1020
 
9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0
5 1
0
117 0 0  t6   0 
0
0
10 3  t7   0 
100 0 4
  

0
0 5
0
0 3  t8   0 
1
 
0
0 15 t9   2210
586 351 25 9.5



1170 382 50 95 11700 0 5  t10 2465
  

500 300 35 10
0 50 3  t11  754
5
3
0 0.5
0
0 0  t12  130





10
1
0
5 100 0 0  t13  145 
1
17 0
0
0
0 0  t14  0 
0
0
260 156 17 10 6
0
1667 120 12 321 15 1.5 175
0
0
97 26 0
10
1
10
0
0 118 0
5
0
0
85
0
29
5
0
3042 430
11893 850
0
26
26
385
55
2600
26
529
0
61 101 60 31
15 1 1.5 1.5
5 60 5 0.5
0 1.5
12 0
115
25
50
0
9.5
0
0.5
117
2120
0
0
10 1
0 1
48 23.5
95 40
85
0
14.25 1989 1
0 30 0.5
0 25
20 0
15 1700 0
0
3 0.75 17 5
0
0 9.75 1
0
0
 241.5 2849
 64
0
260

  163.5 1667
 120

 26
97
  13.5
  90
10
0

 85
0
 0
 0
0
29

5
0
 0
  162
3042
430

 1125.5  11893 850

 2600 115
 231
 8
 26
 25

529
 50
  64.5
0
0
 0
60
156
 12
0
0
0
26
337
 17
321
10
118
 9.5
0
0
 10
 15
1
0
0
10
26
0.5
0
385  117
48
 55  2120 95
 61 101
 60
 15
1
 1.5
5
60
5
 12
0
0
7.5
6
 1.5
0
5
0
1
0
0
175
0
0
0
 100
 85
0
20
0
0
5
0
0  t1   1020 
 
 9  t2   676 
0  t3   348 
  

0  t4   60 
0  t5   25 
  

0  t6   0 
 3  t7   0 
 

0
 3  t8   0 
 
0
 15 t9   2210 



0
 5  t10   2465
  

 50  3  t11    754 
0
0  t12    130 
  

0
0  t13   145 
0
0  t14   0 
 14.25  1989  1
0
 30
0.5
0
 25
 15
 1700
0
0
 0.75
 17
3
5
 9.75
1
0
0
1
0
117
0
4
0
0
10
1
0
0
5
23.5  586  351  25
 40  1170 382  50
 31
500
300  35
 1.5
5
3
0
0.5
10
1
0
 1.5
1
17
0
0
9.5
95
 10
 0.5
5
0
1
0
11700
0
0
 100
0
A Historic Perspective
100+ Years
Set-Point
Coordinated
Automatic
uo
c
Single Machine MW Injection
Control
Single Load
1880s
Set-Point
Coordinated
Automatic
MVAR Injection
Control
Set-Point
Coordinated
Automatic (Closed
Loop)
High-Bandwidth
MW/MVAr
Injection/Flow
Control;
SAPC, SAVC, SAC
Ideal
Control
Performance
Year 2000
24