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
Illinois Institute of Technology
Traditional Plant Operation
Plant Measured Data
Servo-
Loops
MPC
RTO
State
Estimator
Parameter
Estimator
Estimation Units
Set-points
Set-points
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Smart Plant Operation
Plant Measured Data
Servo-
Loops
MPC
RTO
State
Estimator
Parameter
Estimator
Estimation Units
Set-points
Set-points
Smart Plant
Supervisor
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Motivating Example (Surge Tank)
q
q(sp)
FT
FC
qin
V
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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.
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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.
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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.
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Closed-loop Surge Tank
q(sp)
FT
FC
q
qin
V(sp)
LT
LC
V
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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.
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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
Closed-Loop Operation (Case 1: c = 1 min )
(disturbance a) (disturbance b)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Closed-Loop Operation (Case 1: c = 10 min )
(disturbance a) (disturbance 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)
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)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Closed-Loop Operation (Case 1: c = 50 min )
(disturbance a) (disturbance 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)
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)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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
Department of Chemical and Biological Engineering
Illinois Institute of Technology
The Operator’s Plight
• 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)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
The Operator’s Plight
• 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 )
Department of Chemical and Biological Engineering
Illinois Institute of Technology
The Operator’s Plight
• 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 )
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight Re-Examined
• Broader perspective on the process will yield solution.
q(sp)
FT
FC
q
qin
V(sp)
LT
LC
V
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight Re-Examined
• Broader perspective on the process will yield solution.
• Reconsider the separation unit downstream:
q(sp)
FT
FC
q
qin
V(sp)
LT
LC
V Separation
Unit
Nominal Throughput:
30 m3/min
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight Re-Examined
• Broader perspective on the process will yield solution.
• Reconsider the separation unit downstream:
q(sp)
FT
FC
q
qin
V(sp)
LT
LC
V Separation
Unit
Nominal Throughput:
30 m3/min
Maximum Throughput:
31 m3/min
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight Re-Examined
• Broader perspective on the process will yield solution.
• Reconsider the separation unit downstream:
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.
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight
V
EDOR
* *
OSSOP
3129
20
0
Original
Operating Point
q
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Solution
V
EDOR
*
OSSOP
3129
20
0New BOP
q
*
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Solution
V
EDOR
* *
OSSOP
3129
20
0
Original
Operating Point
q
V
EDOR
*
OSSOP
3129
20
0New BOP
q
*
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Solution
V
EDOR
* *
OSSOP
3129
20
0
Original
Operating Point
q
V
EDOR
* *
OSSOP
3129
20
0
New BOP
q
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Model Predictive Control
LT
q(sp)
V(nom)
MPC
q(no
m)
V FT
FC
q
FTqin
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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.
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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.
Department of Chemical and Biological Engineering
Illinois Institute of Technology
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
Top Related