Mapping of Thermal Energy Integration Retrofit Assessment of Industrial Plants

Luciana Savulescu, Zoé Périn-Levasseur and Marzouk Benali

Prague, Czech Republic, August 25-29, 2012

15th Conference Process Integration, Modelling and Optimisation for Energy Saving

and Pollution Reduction

2

Outline

Sustainability through PI

A Canadian Perspective

Energy Efficiency Strategies

Novel Approach for Energy Assessment

Steam Mapping

Waste Heat Mapping

Conclusions

3

Our Strategy

4

Heat Exchangers creating inefficiencies

Composite CurvesMinimum energy consumptions and saving potential

HEN Retrofit Design

Modified Network Pinch Approach

5

6-103-51-2 11-15 >16Total 53 PI studies funded

2213

6 162

3

Actual Fuel Savings6.6 PJ/year

Implementation rate: 55%Enough to heat

100,000 family homes

NRCan’s PI Incentive Program Participants Across Canada

Economic Activity Water Savings

Production IncreaseEquivalent to < 100,000 cars

GHG Reductions

50 MW

Renewable Electricity

6

Industry Issues

INCREASE THROUGHPUT

7

Energy Efficiency StrategiesTechniques Characteristics

Energy Audit

Equipment-based analysis

Do not account for the interactions within the energy system

Obvious opportunities

Simulation-based Analysis

Complex – large amount of info

Inefficiencies are not indicated

Process Control, Monitoring and Targeting

Link to operations, not design

Low-hanging fruit measures

Process Integration Techniques

Global system-based approach

Account for the interactions within the energy system

Evaluation of savings prior to design

8

H

PI – ApproachHigh Pressure Steam

T

Refrigeration

Heat Pump

Cooling Water

Medium pressure steamLow pressure steam

Pinc

h

High Pressure Steam

T

Refrigeration

Heat Pump

Cooling Water

Medium pressure steamLow pressure steam

Pinc

h

High Pressure Steam

T

Refrigeration

Heat Pump

Cooling Water

Medium pressure steamLow pressure steam

Pinc

h

9

Challenges for PI

Methodology issues

Balance: Simplified assumptions vs. Practical elements to capture the complexity of the process

Application issues

Data gathering and data uncertainties

Highly specialized expertise requirement

Industry issues

Particular plant bottlenecks (operation and economics)

Application and interpretation of composite curves

…. Complementary way ?

10

Steam Mapping

Capture the information on steam use from the process perspective, as it illustrates the cold streams energy demand

Relate the pressure level and the amount of steam consumed with its corresponding process energy load and temperature levels

Mill SimulationMill Engineers

11

Heat Exchanger Network – Composite Curves

Composite curves provide the energy saving targeting 2200 kW

Pinch temperature 50°C to guide the screening of inefficiencies

Indirectly information on the location on heaters

Tem

pera

ture

(°C

)

Energy Load (kW)

Pinch (50°C)Tmin=10°C

QH=2800 kW

QC=800 kW

Heater 3

Heater 1

Heater 2

Effluent/Waste Heat

Base Case 5000 kWEnergy Savings 2200 kW

Tem

pera

ture

(°C

)

Energy Load (kW)

Pinch (50°C)Tmin=10°C

QH=2800 kW

QC=800 kW

Heater 3

Heater 1

Heater 2

Effluent/Waste Heat

Base Case 5000 kWEnergy Savings 2200 kWHot side Cold side

Name

Load

(kW)

Name

Hot Stream

Tin

(°C)

Tout

(°C)

Name

Cold Stream

Tin

(°C)

Tout

(°C)

Heater 1 1000 Steam - - CSH1 10 30

Heater 2 2500 Steam - - CSH2 35 80

Heater 3 1500 Steam - - CSH3 100 120

HEX1 2000 HS1 97 50 CS1 30 65

HEX2 5000 HS2 55 30 CS2 5 35

Effluent 3000 Effluent 45 30 Environment - -

12

Steam Mapping

0.22

0.36

0.18

0.33

0

20

40

60

80

100

120

140

CSH1-Heater 1 CSH2-Heater 2 CSH3-Heater 3

Steam Users

Tem

pera

ture

(°C

)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Econ

omic

Pen

alty

(M$/

year

)

Econ. Zone1 Econ Zone 2 Econ Zone3

50

Zone 1

1800kW36%

Zone 3

1500kW30%

Zone 2

1700kW34%

Preliminary energy target 1800 kW (36%)

Steam use inefficiency in Heater 1 and Heater 2

Heater 1 economic penalty is 0.22 M$/y , assuming a 7$/GJ

Heater 2 economic penalty is 0.18 M$/y

13

Overall steam distribution

Medium pressure steamLow pressure steam

Kraft Process – Steam Demand Mapping

14

Waste Heat Mapping

Represent the process heat sources as energy loads and temperature levels

Facilitate the screening of energy recovery opportunities when combined with the steam mapping diagram

15

Waste Heat Mapping

0

20

40

60

80

100

120

140

160

180

PM1effluent

PM2effluent

RB fluegases

Dryerexhaust

Alcalineffluent

Screenseffluent

PBblowdown

Selected Waste Heat Sources

Tem

pera

ture

(°C

)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Econ

omic

Ben

efit

(M$/

y)

Saving benefit in zone 1 Saving benefit in zone 2 Saving benefit in zone 3

11.1 MW12.5 MW

7 MW

6.3 MW2.5 MW

2.2 MW

1.2 MW

24 MW56%

16.4 MW38%

2.4 MW6%

PM: paper machine, PB: power boiler

50

8.4

4.1

7.6

3.5

2.1

3.5

1.4

3.5

Zone

Zone

Zone 2.8

1.2

1.3

0.3

0.6

0.3

16

Steam and Waste Heat Mapping Assembly

-20

0

20

40

60

80

100

120

140

160

180

200

Pulp dr

yer

PM air p

rehea

ting

BL eva

porat

ionWate

r dea

erator

Bleach

ingPM1 w

hitew

ater

RB air p

rehea

ting

PM1 efflu

ent

PM2 efflu

ent

PB flue g

ases

Dryer e

xhau

stAlca

lin ef

fluen

t

Screen

ing ef

fluen

tPB bl

owdo

wn

Heat demands versus Waste heat sources

Tem

pera

ture

(°C

)

5 MW

25.6 MW 9 MW

6 MW

5 MW 12.5 MW

8.8 MW

11.1 MW

4.3 MW

7 MW

6.3 MW2.5

2.2 MW

1.2 MW

50

PM: paper machine, Bl: black liquor, RB: recovery boiler, PB: power boiler

Steam users Waste heat

MP

MP

MP/LP

LP

LP

MP

LP

17

Thermal mapping provides a novel framework to illustrate:

the global distribution of steam use

current profile without loosing the specifics through merging

rapid screening of steam use inefficiencies as load/economics

the potential and economics of waste energy

the waste heat recovery opportunities

Improve the communication with mill engineers Facilitate the understanding of the PI concepts by industryA way to increase the demand for PI studiesA descriptive framework prior to detailed PI case studies

Benefits of the Visualization

18

Optimal Process and Technology Integration

Data Collection for retrofit

Connect with industry

Implement project

Understand the process

Take decisions

Get closer to sustainability goals

KRAFT PROCESSKRAFT PROCESS NEW BIOREFINERY TECHNOLOGY

NEW BIOREFINERY TECHNOLOGY

UTILITY SYSTEMUTILITY SYSTEM

Biorefinery

19

PI: A Step Towards Sustainability From Research to Implementation

ImplementationImplementationTrainingTrainingCase StudiesCase Studies

DecisionDecision--supportsupport

CommunicationCommunicationData CollectionData Collection

Integration Integration SoftwareSoftware Technologies Technologies

Retrofit SolutionsRetrofit Solutions

IncentivesIncentives

ResearchResearch

0

20

40

60

80

100

120

140

160

180

PM1 effluent PM2 effluent RB fluegases

Dryerexhaust

Ae

Selected Waste Heat Sources

Tem

pera

ture

(°C)

Saving benefit in zone 1 Saving benefit in zone 2 Sav

11.1 MW12.5 MW

7 MW

6.3 MW

24 MW56%

16.4 MW38%

2.4 MW6%

PM: paper machine, PB: power boiler

50

8.4

4.1

7.6

3.5

2.1

3.5

1.4

3.5

Zone

Zone

Zone 2.8

20

Acknowledgments

Financial support

Program on Energy Research and Development of Natural Resources Canada

Thank you for your attention…

Luciana Savulescu, Research ScientistIndustrial Systems OptimizationEmail: luciana.savulescu@nrcan.gc.ca Telephone: +1 (450) 652-0275