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Cyber-Physical Systems Distributed Control: The
Advanced Electric Power Grid
Mariesa CrowUniversity of Missouri-Rolla
Funded by the Energy Storage Systems Program of the U.S. Department Of Energy (DOE/ESS) through Sandia National Laboratories (SNL).
Issues• Hardware-software co-design• Device placement and control
– Decentralized– Steady-state– Dynamic
• Cyber security• Reliability
33
vv
Transmission LineGenerationFACTS
Wind Power
Energy Storage
Solar Power
Energy Storage
FACTS Device
Distributed Decisions
Power Electronics
Communications
Sensing and monitoring Inputs
Power Electronics
Power Electronics
Distributed controland fault/attack detection
FACTS Power System Model
FACTS Power System
num_generatorsnum_lines
num_FACTSnum_busestotal_power
supply_power()reconfigure()
run_FACTS_placement()
Voltage stability, no overloads, flow balance,
availability
Service Provider(Utility)
providesinitiates
Contin-gency
typenamecause
affects : Event
Eve
nt R
ecep
tor
controls : Event
Attributes
Methods
Constraints
First Decomposition
FACTS Device
manipulates
setpoint
change_setpoint(newSetpoint)control_power_line()reconfigure()
flow balance
Neighbors limits, monitors
places
Placement
locations
compute_locations()
Placement is optimized
Power Transmission System
flowscapacitiesgenerationsloads
AG[For each line-capacity <= flow <= capacity{checked by FACTS}]------------------------------AG[For each bussum of lines.flow is 0.{checked by FACTS}]------------------------------AG[For each loadload is greater than or equal to 0.{checked by FACTS}]
supply_power()
affects : Event
uses
provides
initiates
affects :Event
senses
Eve
nt R
ecep
tor
FACTS Device
Power Transmission System
Placement Algorithm
SimulatedPowersystem
Unified Power Flow Controller (UPFC) FACTS
DSP BoardEmbeddedComputer
UPFC PowerElectronics
Simulated Power Transmission System
Simulation Engine Hardware in the LoopLine
3332
31 30
35
80
78
747966 7
5
77
7672
8281
8683
84 85
156 157 161162
vv
167165
15815915544
45160
166
163
5 11
6
8
9
1817
43
7
14
12 13
138139
15
19
16
112
114
115
118
119
103
107108
110
102
104
109
142
376463
56153 145151
15213649
4847
146154
150149
143
4243
141140
50
57
230 kV345 kV500 kV
36
69
Simulation Engine
(multiprocessor)
UPFC
UPFCUPFC
Machine 1
D/A output
A/D input
UPFC 1
Programmable load
Machine 2
Machine 3
Power System Simulation Engine
Programmable load
Programmable load
UPFC 2
UPFC 3
D/A output
A/D input
D/A output
A/D input
FACTS Interaction Laboratory
HIL Line
UPFC
Simulation
Engine
Manual power flow control
Manual power flow control
Placement for steady-state performance
Placement for dynamic performance
Long term control (MF & SQP)
agent based long term control
Line overload cascading failure
scenarios
dynamic cascading failure scenarios
Closed-loop long term control
Cascading failure scenarios
Closed loop dynamic control
Closed loop multi-device
Dynamic nonlinear control
Visualization
prev
ious
wor
k
IEEE 118 Bus Test System
Manual Power Flow Control
4 5 6 7 8 9 10-460
-440
-420
-400
-380
-360
-340
-320
-300
-280
-260
time (seconds)
P1 a
nd P
2 (W)
10 11 12 13 14 15-0.75
-0.7
-0.65
-0.6
-0.55
-0.5
-0.45
time (secods)
P1 a
nd P
2 (pu)
10 11 12 13 14 150.9595
0.96
0.9605
0.961
0.9615
0.962
0.9625
0.963
0.9635
0.964
time (seconds)
bus
volta
ge (p
u)
10 11 12 13 14 15-0.08
-0.075
-0.07
-0.065
-0.06
-0.055
-0.05
time (seconds)
bus
angl
e (ra
d)
actual UPFC power flows
measured andfiltered intosimulation
simulatedbus voltages
& angles
Note induced low frequency oscillations
Manual power flow control
Placement for steady-state performance
Placement for dynamic performance
Long term control (MF & SQP)
agent based long term control
Line overload cascading failure
scenarios
dynamic cascading failure scenarios
Closed-loop long term control
Cascading failure scenarios
Closed loop dynamic control
Closed loop multi-device
Dynamic nonlinear control
Visualization
prev
ious
wor
k
Closed-loop long term control
• Which setting yield the lowest PI over all possible contingencies?
Manual power flow control
Placement for steady-state performance
Placement for dynamic performance
Long term control (MF & SQP)
agent based long term control
Line overload cascading failure
scenarios
dynamic cascading failure scenarios
Closed-loop long term control
Cascading failure scenarios
Closed loop dynamic control
Closed loop multi-device
Dynamic nonlinear control
Visualization
prev
ious
wor
k
Manual power flow control
Placement for steady-state performance
Placement for dynamic performance
Long term control (MF & SQP)
agent based long term control
Line overload cascading failure
scenarios
dynamic cascading failure scenarios
Closed-loop long term control
Cascading failure scenarios
Closed loop dynamic control
Closed loop multi-device
Dynamic nonlinear control
Visualization
prev
ious
wor
k
IEEE 118 Bus Test SystemFault then line outage 37-39
G
Riversde 1
Pokagon
2HickryCk
3
NwCarlsl
4
11
8
117
12
SouthBnd
TwinB
rch
Corey
Olive
Olive
Bequine
Breed
9
10
G
FtWayne15
67
Kankakee
JacksnRd
Concord
14
17
30
Sorenson
Sorenson
13
16
GoshenJt
N. E.
37
34
3536
NwLibrty
40 41 42
39
18
19 43
S.Kenton
38
S.TiffinWest End Howard
WLima
Rockhill
EastLima
Sterling
LincolnMcKinley
Adams20
Jay21
22Randolph
113
31
32
29
28
Grant
Delaware
DeerCrk
Deer Crk
Mullin
Outage 37-39a
From 65MuskngumS
Area 2533Haviland
G
Riversde 1
Pokagon
2HickryCk
3
NwCarlsl
4
11
8
117
12
SouthBnd
TwinB
rch
Corey
Olive
Olive
Bequine
Breed
9
10
G
FtWayne15
67
Kankakee
JacksnRd
Concord
14
17
30
Sorenson
Sorenson
13
16
GoshenJt
N. E.
37
34
3536
NwLibrty
40 41 42
39
18
19 43
S.Kenton
38
S.TiffinWest End Howard
WLima
Rockhill
EastLima
Sterling
LincolnMcKinley
Adams20
Jay21
22Randolph
113
31
32
29
28
Grant
Delaware
DeerCrk
Deer Crk
Mullin
Outage 37-39b
From 65MuskngumS
Area 2533Haviland
G
Riversde 1
Pokagon
2HickryCk
3
NwCarlsl
4
11
8
117
12
SouthBnd
TwinB
rch
Corey
Olive
Olive
Bequine
Breed
9
10
G
FtWayne15
67
Kankakee
JacksnRd
Concord
14
17
30
Sorenson
Sorenson
13
16
GoshenJt
N. E.
37
34
3536
NwLibrty
39
40 41 42
18
19 43
S.Kenton
38
S.TiffinWest End Howard
WLima
Rockhill
EastLima
Sterling
LincolnMcKinley
Adams20
Jay21
Randolph22
113
31
32
29
28
Grant
Mullin Delaware
DeerCrk
Deer Crk
Outage 37-39c
From 65MuskngumS
Area 2533Haviland
Simulation of cascading failure
-2 -1 0 1 2 3 4 5 6
-1
-0.5
0
0.5
1
time (seconds)
activ
e po
wer
(pu)
37-40
40-41
40-42
line 37-39 tripline 37-40 trip
line 40-42 tripFault on at t = 0
Line ratings
Comparison
mode A(i) B(i) ω(i) mode A(i) B(i) ω(i)
1 0.02 0 13.05 1 0.02 0 13.042 0.05 0 6.55 2 0.07 0 6.543 0.02 -0.14 6.084 0.04 0 6.1
( )( ) cosiB ti i ix t Ae tω θ= +∑
experimental simulation
190 195 200 205 210
-0.4
-0.2
0
0.2
0.4
0.6
time (seconds)
activ
e po
wer
(pu)
37-40
37-40
40-42
5 10 15 20 25
-0.4
-0.2
0
0.2
0.4
0.6
time (seconds)
activ
e po
wer
(pu)
37-40
37-40
40-42
GUIs for HIL
Manual power flow control
Placement for steady-state performance
Placement for dynamic performance
Long term control (MF & SQP)
agent based long term control
Line overload cascading failure
scenarios
dynamic cascading failure scenarios
Closed-loop long term control
Cascading failure scenarios
Closed loop dynamic control
Closed loop multi-device
Dynamic nonlinear control
Visualization
prev
ious
wor
k
Special Thanks
• Imre Gyuk - DOE Energy Storage Program• Stan Atcitty - Sandia National Laboratories• John Boyes - Sandia National Laboratories
UMR student team• Gosnell, Michael• Lininger, Adam• Ryan, Matthew• Service, Travis• Siever, William• Simsek, Sule• Smorodkina, Ekaterina• Su, Changyi• Sun, Yan• Tang, Han (Carol)• Underwood, Ryan
• Guo, Jianjun• Kalyani, Radha• Li, Xiaomeng• Ma, Hong Tao• Mehraeen, Shahab• Shi, Lisheng• Wang, Keyou• Yazdani, Atousa• Zarghami, Mahyar
Computer Science Electrical Engineering