Demand Response for Chemical Manufacturing Using Economic

Demand Response for Chemical Manufacturing Demand Response for Chemical Manufacturing

Using Economic MPC Using Economic MPC

David Mendoza-Serrano and Donald J. Chmielewski

Department of Chemical and Biological Engineering Illinois Institute of Technology

Chicago, IL

P1

P2

P3

P4

Utility Plant

S1

S2

S3

S4S5

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

0 0.5 1 1.5 220

30

40

50

time (days)

Inst

an

tan

iou

sP

ro

fit

($/s

ec)

Department of Chemical and Biological EngineeringDepartment of Chemical and Biological Engineering

Illinois Institute of TechnologyIllinois Institute of Technology

Outline Outline

• Introduction to Smart Grid

• Modeling of a Flexible Chemical Plant

- Material Flow Manipulations

- Flexible Utilities (Steam and Electricity)

- Material Storage

• Smart Grid Operation and Revenue



Dispatchable Generation

Consumer Demand Transmission

Energy Storage

Renewable Generation Smart Homes

Smart Buildings Smart

Manufacturing

Overview of the Smart GridOverview of the Smart Grid



RealReal--time Pricing for Electricity time Pricing for Electricity

Historic data from the PJM Western Hub, Day-Ahead prices: June 1, 2001 through June 20, 2001,

http://www.pjm.com/markets-and-operations/energy/day-ahead/day-ahead-historical.aspx

6 6.5 7 7.5 8 8.5 9 9.5 100

20

40

time (days)

En

erg

y V

alu

e

($/M

Wh

r)



RealReal--time Pricing for Electricity time Pricing for Electricity

Historic data from the PJM Western Hub, Day-Ahead prices: June 1, 2001 through June 20, 2001,

http://www.pjm.com/markets-and-operations/energy/day-ahead/day-ahead-historical.aspx

0 2 4 6 8 10 12 14 16 18 200

20

40

60

80

time (days)

En

erg

y V

alu

e

($/M

Wh

r)

6 6.5 7 7.5 8 8.5 9 9.5 100

20

40

time (days)

En

erg

y V

alu

e

($/M

Wh

r)





Energy Storage



Manufacturing

Overview of the Smart GridOverview of the Smart Grid



IGCCIGCC

Gasification Unit

PG Power Block

vH2,G

vcoal

vH2



IGCC with Dispatch CapabilityIGCC with Dispatch Capability

Gasification Unit

PG

Storage Tank

Power Block

vH2,S

vH2,G

vcoal

vH2



Economic MPC for IGCC DispatchEconomic MPC for IGCC Dispatch

0 1 2 3 4 5 6 7 8 9 100

20

40

Energ

y V

alu

e

($/M

Whr)

0 1 2 3 4 5 6 7 8 9 100

500

1000

1500

Genera

ted P

ow

er

(MW

)

0 1 2 3 4 5 6 7 8 9 100

500

1000

Time (days)

H2 in

Sto

rage (

tonnes)



Smart Buildings Smart Buildings

and Thermal Energy Storage and Thermal Energy Storage

Outside

Environment

(T3)

...

Windows

...

Walls

To T3T21T12 T11T11To To

...

Outside

Environment

(T3)

Room

Room

Room

Room

Room

Room

Heat from

BuildingBuilding

Heat from

Environment

Power

Consumption Chiller

Heat to

TES

Thermal

Energy Storage

Heat to

Chiller



Economic MPC for TEC CoordinationEconomic MPC for TEC Coordination

0 20 40 60 80 100 120 140

0

200

400

600

Time (hours)

Hea

t to

C

hil

ler

(kW

T)

0 20 40 60 80 100 120 140

-2000

-1000

0

Time (hours)

En

erg

y i

n

Sto

rag

e (M

Wh

r T)

0 20 40 60 80 100 120 140

0

200

400

600

800

Time (hours)

Hea

t fr

om

R

oo

m (

kW

T)

0 20 40 60 80 100 120 14020

22

24

26

Time (hours)

Tem

per

atu

re

in R

oo

m (

C)

0 20 40 60 80 100 120 140

40

60

80

100

120

140

Time (hours)

Ele

ctri

city

Pri

ce (

$/M

Wh

r)

0 20 40 60 80 100 120 14020

30

40

Time (hours)

Ou

tsid

e

Tem

peratu

re (

C)





Energy Storage



Manufacturing

ObjectiveObjective



Outline Outline

• Introduction to Smart Grid

• Modeling of a Flexible Chemical Plant

- Material Flow Manipulations

- Flexible Utilities (Steam and Electricity)

- Material Storage

• Smart Grid Operation and Revenue



P1

P2

P3

P4

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

ToyToy ExampleExample



Material Balances at Process UnitsMaterial Balances at Process Units

1214

1213

9811

9810

57

56

214

213

9.0

1.0

2.07.0

8.03.0

417.0

583.0

1.075.0

9.025.0

nn

nn

nnn

nnn

nn

nn

nnn

nnn

P1

P2

P3

P4

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16



Material Flow ManipulationsMaterial Flow Manipulations

16

15

12

9

8

5

2

1

n

n

n

n

n

n

n

n

m

P1

P2

P3

P4

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

mn



Material Balances at StreamsMaterial Balances at Streams

P1

P2

P3

P4

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

214

151211

1697

84

53

0

0

0

0

0

nn

nnn

nnn

nn

nn




P1

P2

P3

P4

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

214

151211

1697

84

53

0

0

0

0

0

nn

nnn

nnn

nn

nn

mn m0



Material Flow ConstraintsMaterial Flow Constraints

P1

P2

P3

P4

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

max412

max398

max25

max121

uu

uu

nnn

nnn

0n

,

,



P1

P2

P3

P4

Utility Plant

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

Energy Requirements of Process UnitsEnergy Requirements of Process Units

124

983

52

211

4

5.05.0

5.0

5.05.0

n

nn

n

nn

e

e

e

e



P1

P2

P3

P4

Utility Plant

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

Energy Requirements of Process UnitsEnergy Requirements of Process Units

124

983

52

211

4

5.05.0

5.0

5.05.0

n

nn

n

nn

e

e

e

e ne



P1

P2

P3

P4

Utility Plant

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

Steam Steam UtilitiesUtilities



P1

P2

P3

P4

Utility Plant

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

Electric Grid

Possible Electric UtilitiesPossible Electric Utilities



If energy is steam, conversion efficiency assumed hs = 0.75

If energy is electric, conversion efficiency assume he = 0.95

In vector form,

where

Energy Conversion EfficiencyEnergy Conversion Efficiency

eess eee

Iss h Iee h

,



Energy Balance at UtilitiesEnergy Balance at Utilities

Steam PlantSteam

Bank

Electric

Node

fsp

es1es2es3

es4

ee1ee2ee3

ee4

eg



Possible CoPossible Co--Generation Plant Generation Plant

Steam PlantSteam

Bank

Electric

Node

Co-Generation

Plant

fsp

fcog

es1es2es3

es4

ee1ee2ee3

ee4

eg



Energy Balance at Steam BankEnergy Balance at Steam Bank

Steam PlantSteam

Bank

Electric

Node

Co-Generation

Plant

fsp

fcog

es1es2es3

es4

ee1ee2ee3

ee4

eg

scogcogsspsp eff 1hh 75.0sph

50.0cogsh

T

1

1

1

1

1



Energy Balance at Electric NodeEnergy Balance at Electric Node

Steam PlantSteam

Bank

Electric

Node

Co-Generation

Plant

fsp

fcog

es1es2es3

es4

ee1ee2ee3

ee4

eg

ecogcogeg efe 1h

50.0cogsh

T

1

1

1

1

1

15.0cogeh



Process EconomicsProcess Economics

P1

P2

P3

P4

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

,

,

Steam PlantSteam

Bank

Electric

Node

Co-Generation

Plant

fsp

fcog

es1es2es3

es4

ee1ee2ee3

ee4

eg

[n1 n6 n10 n13 n15 n16]

[-100 200 120 35 50 100]

($/bbl)

nnc

gecogfspf ecfcfc

[fsp fcog eg]

[ 3 3 5.5]

($/GJ)



Process Optimization (RTO)Process Optimization (RTO)

max412

max398

max25

max121

,0,0,0,0

,0,0

0 s.t.

max

uu

uu

efeeff

eemm

ecfcfcc

ecogcogegscogcogsspsp

eess

gecogfspf

e

ffee

m

g

cogsp

es

nnn

nnn

hhh

nn

nnn

11



Baseline SolutionBaseline Solution

then5.5 If ec

****sec/3.26$ gecogfspf ecfcfcc nn

fsp* = 7.21 GJ/sec,

fcog* = 0

eg* = 0



Baseline SolutionBaseline Solution

then5.5 If ec

****sec/3.26$ gecogfspf ecfcfcc nn

sec/48$*nnc

fsp* = 7.21 GJ/sec,

fcog* = 0

eg* = 0



RealReal--time Pricing for Electricitytime Pricing for Electricity

6 6.5 7 7.5 8 8.5 9 9.5 100

20

40

time (days)

En

erg

y V

alu

e

($/M

Wh

r)



RealReal--time Pricing for Electricitytime Pricing for Electricity

6 6.5 7 7.5 8 8.5 9 9.5 100

20

40

time (days)

En

erg

y V

alu

e

($/M

Wh

r)

0 0.5 1 1.5 20

5

10

time (days)

Pric

e o

f E

lectr

icit

y (

$/G

J)



0 0.5 1 1.5 20

5

10

time (days)

Pric

e o

f E

lectr

icit

y (

$/G

J)

0 0.5 1 1.5 2

0

5

10

time (days)F

uel

En

erg

y t

o

Ste

am

Pla

nt

(GJ

/sec)

0 0.5 1 1.5 2

0

5

10

15

time (days)

Fu

el

En

erg

y t

o

Co

-Gen

era

tio

n

Pla

nt

(GJ

/sec)

0 0.5 1 1.5 2-2

0

2

4

time (days)

Po

wer f

ro

m G

rid

(G

J/s

ec)

Electricity

Price ($/GJ)

Fuel to Steam

Plant (GJ/s)

Fuel to Co-Gen

Plant (GJ/s)

Power from

Grid (GJ/s)

Operation with RealOperation with Real--time Pricingtime Pricing



Revenue with RealRevenue with Real--time Pricingtime Pricing

0 0.5 1 1.5 20

5

10

time (days)

Pric

e o

f E

lectr

icit

y (

$/G

J)

0 0.5 1 1.5 2

0

5

10

time (days)

Fu

el

En

erg

y t

o

Ste

am

Pla

nt

(GJ

/sec)

0 0.5 1 1.5 2

0

5

10

15

time (days)

Fu

el

En

erg

y t

o

Co

-Gen

era

tio

n

Pla

nt

(GJ

/sec)

0 0.5 1 1.5 2-2

0

2

4

time (days)

Po

wer f

ro

m G

rid

(G

J/s

ec)

0 0.5 1 1.5 220

30

40

50

time (days)

Inst

an

tan

iou

sP

ro

fit

($/s

ec)

Average profit found to be

$32.3/sec

22.8% increase wrt baseline

$26.3/sec



P1

P2

P3

P4

Utility Plant

S1

S2

S3

S4S5

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

Impact of MaterialImpact of Material Storage Storage




P1

P2

P3

P4

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

214

151211

1697

84

53

0

0

0

0

0

nn

nnn

nnn

nn

nn

m0mn&



Material Balances with StorageMaterial Balances with Storage

2145

1512114

16973

842

531

nn

nnn

nnn

nn

nn

M

M

M

M

M

mn mM

P1

P2

P3

P4

S1

S2

S3

S4S5

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16

max)(0 MtM

&



Process Optimization (RTO)Process Optimization (RTO)

max412

max398

max25

max121

,0,0,0,0

,0,0

0 s.t.

max

uu

uu

efeeff

eemm

ecfcfcc


eess

gecogfspf

e

ffee

m

g

cogsp

es

nnn

nnn

hhh

nn

nnn

11



Process Optimization with StorageProcess Optimization with Storage

max

max412

max398

max25

max121

,0,0,0,0

,0,0

0

s.t.

max

MM

uu

uu

efeeff

eemMm

ecfcfcc


eess

gecogfspf

e

ffee

m

g

cogsp

es

nnn

nnn

hhh

nn

nnn

11



Economic MPCEconomic MPC

max

max412

max398

max25

max121

0,

,0,0,0,0

,0,0

0

s.t.

)]()()()()([1

max

MM

uu

uu

efeeff

eemMm

dttetctfctfctcT


eess

Tt

t

gecogfspf

Me

ffee

m

g

cogsp

es

nnn

nnn

hhh

nn

nnn

11



Literature on EMPC

• Conceptual Development and Stability Issues: Rawlings and Amrit (2009); Diehl, et al. (2011); Huang and Biegler (2011); Heidarinejad, et al. (2012)

• Process Scheduling: Karwana and Keblisb (2007); Baumrucker and Biegler (2010); Lima et al. (2011); Kostina et al. (2011)

• Power Systems: Zavala et al. (2009); Xie and Ilić (2009), Hovgaard, et al. (2011), Omell and Chmielewski (2011)

• HVAC Systems: Braun (1992); Morris et al. (1994); Kintner-Meyer and Emery (1995); Henze et al. (2003); Braun (2007); Oldewurtel et al. (2010), Ma et al. (2012); Mendoza and Chmielewski (2012)



Revisit Example with 2 Storage UnitsRevisit Example with 2 Storage Units

P1

P2

P3

P4

S4S5

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16




and Storageand Storage

0 0.5 1 1.5 20

5

10

time (days)

Pric

e o

f E

lectr

icit

y (

$/G

J)

0 0.5 1 1.5 20

5000

10000

15000

time (days)

Ma

ss i

n

Sto

ra

ge (

bb

l)

M4

M5

0 0.5 1 1.50

1

2

time (days)

Ma

ss F

low

(b

bl/

sec)

n1

n12

n13

n14

P1

P2

P3

P4

S4S5

n1

n2n14n13

n3

n4

n5

n6

n7

n9n8 n10

n11n12

n15

n16





0 0.5 1 1.5 2

0

5

10

time (days)

Fu

el

En

erg

y t

o

Ste

am

Pla

nt

(GJ

/sec)

RTO

EMPC

0 0.5 1 1.5 20

10

20

time (days)

Fu

el

En

erg

y t

o

Co

-Gen

era

tio

n

Pla

nt

(GJ

/sec)

RTO

EMPC

0 0.5 1 1.5 2-4-202468

time (days)

Po

wer f

ro

m G

rid

(G

J/s

ec)

RTO

EMPC

0 0.5 1 1.5 20

5

10

time (days)

Pric

e o

f E

lectr

icit

y (

$/G

J)

0 0.5 1 1.50

1

2

time (days)

Ma

ss F

low

(b

bl/

sec)

n1

n12

n13

n14



Revenue with RealRevenue with Real--time Pricingtime Pricing


EMPC average profit

$34.2/sec

A 30% increase wrt baseline

$26/sec

A 7.2% increase wrt RTO

$32.3/sec

0 0.5 1 1.5 220

30

40

50

time (days)

Inst

an

tan

iou

sP

ro

fit

($/s

ec)

RTO EMPC

0 0.5 1 1.5 20

10

20

time (days)

Fu

el

En

erg

y t

o

Co

-Gen

era

tio

n

Pla

nt

(GJ

/sec)

RTO

EMPC

0 0.5 1 1.5 2-4-202468

time (days)

Po

wer f

ro

m G

rid

(G

J/s

ec)

RTO

EMPC

0 0.5 1 1.5 20

5

10

time (days)

Pric

e o

f E

lectr

icit

y (

$/G

J)

0 0.5 1 1.50

1

2

time (days)

Ma

ss F

low

(b

bl/

sec)

n1

n12

n13

n14



Acknowledgements

• Current and Former Students: Ben Omell David Mendoza-Serrano

Ming-Wei Yang (Taiwan Electric) • Personal Communications Don Bartusiak Jeff Siirola

• Funding: National Science Foundation (CBET – 0967906)



AIChE Workshop on

Smart Grid for the Chemical Process Industry September 25-27, 2013 - Chicago

https://www.aiche.org/conferences/workshop-on-smart-grid-chemical-process-industry/2013

Will explore the opportunities and challenges associated with

demand response in the chemical process industry.

Co-sponsored by

AIChE – Computing and Systems Technology (CAST) Division

and IIT – Wanger Institute for Sustainable Energy Research (WISER)

Collocated with the

Great Lakes Symposium on Smart Grid and the New Energy Economy

(September 23-25, 2013, Co-sponsored by IEEE Power and Energy Society and IIT

Galvin Center for Electricity Innovation)
















AIChE Workshop on

Smart Grid for the Chemical Process Industry September 25-27, 2013 - Chicago

Confirmed Speakers

• Large Industrials and Demand Response in the United States David Heitzer, EDF Energy Services

• Economic Dispatch of a Combined Heat and Power Plant Jong S. Kim and Thomas F. Edgar, University of Texas at Austin

• Flexible and Efficient Operation for Power Generation and Process Industry – A GE Perspective

Aditya Kumar, GE Global Research

• A Distributed Control Framework for Smart Grid Development Jinfeng Liu University of Alberta and Panagiotis D. Christofides University of California, Los Angeles

• Supply Driven-Operation of Processes Alexander Mitsos, Ganzhou Wang and Wolfgang Marquardt, RWTH Aachen University; Amin Ghobeity and Chris Williams, Massachusetts Institute of Technology

• Use of Low Cost Electrical Power in Petrochemical Process Units Dennis O’Brien, Jacobs Consultancy and Donald J. Chmielewski, Illinois Institute of Technology

• Active participation of Industry in the Smart Grid Ernst Scholtz, Xiaoming Feng, and Iiro Harjunkoski, ABB Corporate Research

• Assessing the Benefits of Stochastic Market Clearing Victor M. Zavala, Argonne National Laboratory

• Multiscale Optimization for Demand Side Management of Industrial Power-intensive Processes Qi Zhang Ignacio Grossmann, Carnegie Mellon University



Conclusions

• Numerous Options for Smart Grid Flexibility in

Chemical Plants

• For the given example profit increased by

- 22.6 % with electric utilities and co-generation

- 30.0 % if storage also included

• Operation Can Get Complicated Very Fast!!!!

• Next Question is Capital Cost of Equipment Upgrades

Documents

Demand Response for Chemical Manufacturing Using Economic