Approximate Dynamic Programming and Reinforcement Learning for Nonlinear Optimal Control of Power Systems November 4, 2003 Ronald Harley Georgia Institute.

Post on 20-Dec-2015

221 Views

Category:

Documents

2 Downloads

Preview:

Click to see full reader

Transcript

Approximate Dynamic Programming and Reinforcement Learning for Nonlinear

Optimal Control of Power Systems

November 4, 2003

Ronald HarleyGeorgia Institute of Technology

ECS-0231632ECS-0080764

Kumar VenayagamoorthyUniversity of Missouri-Rolla

Adaptive Critic Design: Nonlinear Optimal Control

PlantInformaton

UtilityFunction (U)

Optimal cost-to-gofunction (J)

Critic Networks :To minimize the value (of derivatives)

of J with respect to the states

Derivatives via BP

Model Network(Identifier) : To learnthe dynamics of plant

Model Network

Action Network :To find optimal control

u

Plant

Control

Reinforcement Learning

0

* )()(k

k ktUtJ

STATCOM Control

Simulation Results

100ms SC at PCC,

Line Voltage , Generator Terminal VoltageV

The simplified schematic of the SSSC (160 MVA, 15KV VL-L)

Optimal control for FACTS devicesInternal control for static series synchronous

compensator (SSSC)

Series VSI

SynchronousGenerator

V dc

Inf. bus

v s v rv c

is v x

Turbine-Governor

AVR -Exciter

rexe

SSSC

+

GTO

Control

DHPNCCONVC

idc

Optimal control for FACTS devicesInternal control for SSSC (CONVC)

PI Based internal controller (CONVC) for the SSSC

Synchrnouslyrotating reference

transformations

kk ip

+

+

ˆ(tan

ˆˆ

1

22

cd

cq

dc

cqcd

v

V

vvm

Vdc *

Vdc

+-

id

PI- Vdc

iq

- s

kk ip

iq

PI- iq

cqv̂

+iq*

Vdc

s

kk ip

PI- ip

ip

cdv̂+id*

-

ia ib ic

m

+

GTO gate controlof series VSI

+

P*Q*

Vdc

id

Vectorphase-locked

loop

va

vb

vc

Real and reactivecurrent computation

V r

V'dc

Publication: N.G. Hingorani and L. Gyugyi, “Understanding FACTS-Concepts and Technology of Flexible AC Transmission Systems”, IEEE Press, New York, 2000.

Optimal control for FACTS devicesCase study: 100 ms three phase short circuit test at

receiving-end (infinite-bus)

Rotor angle

0 1 2 3 4 5 620

30

40

50

60

70

80

90

100

110

120

130

Time [s]

d [D

egre

e]

Uncompensated

CONVC

DHPNC

Schematic single-line diagram showing an SCRC with external controller (160 MVA, 15KV VL-L)

Optimal control for FACTS devicesExternal control for series capacitive reactance

compensator (SCRC)

SynchronousGenerator Inf. bus

v s

is

SCRC

v r 0

re2xe2

re1xe1Turbine-

Governor

AVR -Exciter

CsT1

1

Internal Controlof SCRC

VoltageSourceInverter

V dc

v c

+GTO

W

WC

sT1

sTK

X C

Filtering DampingController

CsT1

1

External Control

+

+

Line #1

Line #2

*CX

CX

Optimal control for FACTS devicesDHP based external controller (DHPEC)

Schematic single-line diagram showing the DHP based external controller (DHPEC)

SynchronousGenerator

Inf. bus

vs

is

SCRC

re2 xe2

re1 xe1Turbine-Governor

AVR -Exciter

Internal Controlof SCRC

VoltageSourceInverter

Vdc

vc

+GTO

XC

+

+

Line #1

Line #2

*CX

CX

vr

DHP basedexternal controller

(DHPEC)

Optimal control for FACTS devicesCase study: Step changes X*C [pu]

0 5 10 15 20 25-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

Time [s]

[ra

d/s

]

Fixed XC*

KC=1.5

DHPC

Speed deviation

Application in Multi-Machine power system

FACTS(SCRC)

Gen 31600 MVA

Gen 15000 MVA

Gen 22200 MVA 200 km

AREA 1 AREA 2

T1

T2

T3

T4

T5

T6

500 kV 500 kV 500 kV500 kV 13.2 kV

13.2 kV

13.2 kV

13.8 kV

115 kV

Line 1

Line 2

Line 3

Line 4

Line 5

Z 1

Z 2

1

2

34 5

610

7

DHPNC-G

CONVC-GS1

DHPEC-S

CONVEC-SS2 3

11Industrial load

Residentialload

115 kV 13.8 kV

8 9

Large-scale multi-machine power system

A UPFC in the POWER SYSTEM

InfiniteBusShunt

InverterSeries

InverterVd

c

SeriesInverterControl

ShuntInverterControl

V1

Vdcref

R1, L1

V2V1

V1ref

Z1Synch

Generator

Governor

AVR

Exciter

+

-

UPFC

Z1

V1ref

Vdc

Pref

Pinj

Qinj

Q ref

1 2

Pout,

Qout

Verr

Vdcerr Perr

Qerr

R2, L2

Vr

TurbinePref

Neurocontroller

Neuroidentifier

Q

P

ed

eq

Neurocontroller

Neuroidentifier

Vdc

V

epd

epq

5 6 7 8 9 10 11-50

0

50

100

150

200

250

Time (sec)

Load

Ang

le(°

)

UPFC

PI

5 6 7 8 9 10 11-50

0

50

100

150

200

250

Time (sec)

Load

Ang

le(°

)

UPFC

PI

NC

PI

Responses of the Generator for a 180 ms 3- phase Short Circuit at bus 2 at P=0.8 p.u & Q=0.15 p.u

Load angle

Speed response

4 5 6 7 8 9 10 110.96

0.98

1

1.02

1.04

1.06

1.08

1.1

Time (sec)

Spe

ed (

Pu)

UPFC

PI

4 5 6 7 8 9 10 110.96

0.98

1

1.02

1.04

1.06

1.08

1.1

Time (sec)

Spe

ed (

pu)

UPFC

PI

NC

PI

Micro-Machine Research Lab. at the University of Natal, Durban, South Africa

Gen. #1: Trans. Line Impedance Increase

10 10.5 11 11.5 12 12.5 13 13.5 14 14.5 1520

25

30

35

40

Time in seconds

Load

ang

le in

deg

rees

DHP_CONV

CONV_PSS_CONVCON_CONV

10 10.5 11 11.5 12 12.5 13 13.5 14 14.5

0.97

0.98

0.99

1

1.01

Time in seconds

Ter

min

al v

olta

ge in

pu

DHP_CONV

CONV_PSS_CONV

CONV_CONV

top related