cyber-physical systems distributed control: the … · cyber-physical systems distributed control:...

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


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







scenarios







Visualization

prev

ious

wor

k


• Which setting yield the lowest PI over all possible contingencies?







scenarios







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


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


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







scenarios







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

cyber-physical systems distributed control: the … · cyber-physical systems distributed control:...

Documents