smart plant approach to increase plant...

Smart Plant Approach to Increase Plant Profitability

Donald J. Chmielewski

Department of Chemical & Biological Engineering

Illinois Institute of Technology

Miguel J. Bagajewicz

Department of Chemical Engineering

University of Oklahoma

2009 Annual Meeting of the

AIChE

Nashville, TN

Department of Chemical and Biological Engineering


Traditional Plant Operation

Plant Measured Data

Servo-

Loops

MPC

RTO

State

Estimator

Parameter

Estimator

Estimation Units

Set-points

Set-points



Smart Plant Operation

Plant Measured Data

Servo-

Loops

MPC

RTO

State

Estimator

Parameter

Estimator

Estimation Units

Set-points

Set-points

Smart Plant

Supervisor



Smart Plant Topics

• Scheduling and Supervision (Enterprise Wide)

• Fault Detection and Diagnosis (Plant Wide)

• Safe Parking and Emergency Management (Plant

Wide)

• Process Efficiency and Sustainable Operation

(Plant Wide)



Motivating Example (Surge Tank)

q

q(sp)

FT

FC

qin

V



Surge Tank Operating Scenario

q

q(sp)

FT

FC

qin

V

- Inlet flow (qin) is from a reactor and varies with time.

- Exit (q) to a separation unit which demands little variation.

- Tank should not over-flow or run dry.



Surge Tank Operating Scenario

q

q(sp)

FT

FC

qin

V

- Inlet flow: qin = 30 3 m3/min.

- Exit flow q = 30 1 m3/min.

- Tank volume V = 10 10 m3.



Open-Loop Operation

q

q(sp)

FT

FC

qin

V

- Inlet flow: qin = 30 3 m3/min.

- Exit flow q = 30 0 m3/min.

- Tank volume V = 10 10 m3.



Open-Loop Operation

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

Vq

in

q



Open-Loop Operation (Disturbance Scenario b)

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)



Open-Loop Operation

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

Vq

in

q

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

(disturbance a) (disturbance b)



Closed-loop Surge Tank

q(sp)

FT

FC

q

qin

V(sp)

LT

LC

V



Closed-loop Level Control Surge Tank

+ -

qGp(s)Gc(s) +

+

qin Gd(s)

VV(sp)

ssGp /1)(

ssGd /1)(

s

KsGI

cc 11)(

2c

c

K

2I c



Closed-loop Level Control Surge Tank

+ -

qGp(s)Gc(s) +

+

qin Gd(s)

VV(sp)

s

KsGI

cc 11)(

2c

c

K

2I c

Tuning Scenarios:

Case 1: c = 1 min.

Case 2: c = 10 min.

Case 3: c = 50 min.



Closed-Loop Operation (Case 1: c = 1 min )

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

Vq

in

q0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

Vq

in

q



0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

Vq

in

q







0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

Vq

in

q

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)



Extreme Cases

(Over Regulated) (Open-Loop)

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)



Middle Ground

(Over Regulated) (Open-Loop)

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

(c = 10 min )

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)



The Operator’s Plight

Possible scenario

• Shift starts with the following operation (c = 10 min).

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

Vq

in

q




• But, then the disturbance changes to

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

Vq

in

q

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)




• Should the operator re-tune the controller?

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

(c = 10 min )




• Should the operator re-tune the controller?

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

(c = 10 min )

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

(c = 50 min )



Operator’s Plight Re-Examined

• Broader perspective on the process will yield solution.

q(sp)

FT

FC

q

qin

V(sp)

LT

LC

V





• Reconsider the separation unit downstream:

q(sp)

FT

FC

q

qin

V(sp)

LT

LC

V Separation

Unit

Nominal Throughput:

30 m3/min






q(sp)

FT

FC

q

qin

V(sp)

LT

LC

V Separation

Unit

Nominal Throughput:

30 m3/min

Maximum Throughput:

31 m3/min






q(sp)

FT

FC

q

qin

V(sp)

LT

LC

V Separation

Unit

Nominal Throughput:

30 m3/min

Maximum Throughput:

31 m3/min

Exit flow q = 30 1 m3/min.



Operator’s Solution

0 10 20 30 40-5

0

5

10

15

20

25

30

35

time (minutes)

Ta

nk H

old

-up

(m

3)

or

Volu

metr

ic F

low

(m

3/m

in)

(c = 10 min ) • Reselect to the nominal

throughput.

• From 30 m3 / min

to 29 m3 / min

• Obtain guidance from

)( nom

design

nom

actual qqKP



Operator’s Plight

V

EDOR

* *

OSSOP

3129

20

0

Original

Operating Point

q




V

EDOR

*

OSSOP

3129

20

0New BOP

q

*




V

EDOR

* *

OSSOP

3129

20

0

Original

Operating Point

q

V

EDOR

*

OSSOP

3129

20

0New BOP

q

*




V

EDOR

* *

OSSOP

3129

20

0

Original

Operating Point

q

V

EDOR

* *

OSSOP

3129

20

0

New BOP

q



Model Predictive Control

LT

q(sp)

V(nom)

MPC

q(no

m)

V FT

FC

q

FTqin



Operator’s Perspective

• Disturbance characteristics will impact the controller’s ability to meet operational criteria.

• In some cases, adjustment of the controller (re-tuning) will recover performance.

• In other cases, only recourse is modification of nominal operating conditions.



Impact on Smart Plant Operation

• Evolution of disturbance characteristics necessitates the ability to retune controllers.

• To enable such retuning, two technologies are needed:

1. A method to characterize disturbances.

2. A profit focused tuning method that is responsive to disturbance modeling.



Profit View of Smart Plant Operation

Plant Measured Data

Servo-

Loops

MPC

RTO

State

Estimator

Parameter

Estimator

Estimation Units

Set-points

Set-points

Disturbance

Characterization

Reselection of nominal

operating conditions

Retuning

of

controller

smart plant approach to increase plant...

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