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Separation Systems Design Under Uncertainty. Final Presentation for REU program August 3, 2006 Jamie Polan Advisors: Professor Linninger Andr é s Malcolm Laboratory for Product and Process Design University of Illinois- Chicago Department of Chemical Engineering. - PowerPoint PPT Presentation
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LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
Separation Systems Design Separation Systems Design Under UncertaintyUnder Uncertainty
Separation Systems Design Separation Systems Design Under UncertaintyUnder Uncertainty
Final Presentation for REU program
August 3, 2006
Jamie Polan
Advisors: Professor Linninger
Andrés Malcolm
Laboratory for Product and Process DesignLaboratory for Product and Process Design
University of Illinois- Chicago
Department of Chemical Engineering
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
MotivationMotivation
• Must consume less energy to reduce dependence on foreign sources
• Could start by decreasing amount of energy in industry (33%)– chemical industry (24%)– petroleum refining industry (10%)
• Separations is a large part of the energy expense of these industries (60%)
Total energy production and consumption 1970 – 2025 (quadrillion Btu)
http://www.eia.doe.gov/oiaf/aeo/production.html
Residential -21%
Industrial -33%Commercial -18%
Transportation -28%Residential - 21%
Industrial - 33%Commercial - 18%
Transportation - 28%
U.S. Energy Consumption by Sector (2004)
http://www.eia.doe.gov/emeu/aer/consump.html
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
Why Distillation?Why Distillation?
• 95% of separations energy used for distillation
• More than 6% of total U.S. energy consumption used for distillation
• Total consumption by U.S.
94.27 quadrillion Btu
• Consumption by distillation
6.03 quadrillion Btu
• If process improved 0.1%, we could save
– 6.03 x 1012 Btu
– Over 1 million barrels of crude oil
– $$70 million/year70 million/year http://news.bbc.co.uk/1/hi/sci/tech/4669260.stm
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
DistillationDistillation
• Common method of separation in chemical and petroleum refining industries
• Uses concept of relative volatility
– tendency to vaporize
– more volatile = higher vapor pressure at operating temperature
• Very energy intensive– 40,000 distillation columns
– >200 different processes
• Optimizing process will increase efficiency & minimize energy waste
http://www.energyinst.org.uk/education/coryton/page7.htm
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
How to Improve the Process of DistillationHow to Improve the Process of Distillation
• Steady state process behavior is well-known; less is known about
performance of dynamic systems
• Study the dynamic process to see how uncertainty affects
– performance
– cost
– energy required
• Show effects of uncertainty with integrated design and control
• Considering control is necessary to perform a realistic uncertainty
analysis
More energy efficient columns in real life situations by considering
the effects of dynamics and uncertainty in the design stage
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
Distillation ColumnDistillation Column
Rectifying
Section
Stripping
Section
Purify light component
Purify heavy component
(prevent light component loss to bottoms product)
V
L
Feed
Boilup
Reboiler
Bottoms
Product
Reflux
Condenser
Distillate
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
Total amount in
LN-1xN-1 + VN+1yN+1
Material Balance
= Total amount out
= LNxN + VNyN
yN = α xN
1 + (α – 1) xN
Vapor Liquid Equilibrium
Tray BalanceTray Balance
LN-1xN-1
LNxN VN+1yN+1
VNyN
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
Case Study – Dynamic Column ModelCase Study – Dynamic Column Model
• Components– hexane
– p-xylene
• Inputs– Temperature - 70°F
– Pressure – 1 atm (1.01325 bar)
– Feed rate basis – 5 kmol/hr
– Feed compositions» zh = 0.4
» zx = 0.6
• Aim: Using Matlab, study how different sources of uncertainty affect the operation and cost of a dynamic column
Reflux
Feed
Condenser
Distillate
Boilup
Reboiler
Bottoms Product
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
Controlled ColumnControlled Column
ControlControlFeed
B
Reflux D
Boilup
0 1000 2000 30000.997
0.998
0.999
xd
measured
predicted
set point
0 1000 2000 3000
0.005
0.01
0.015
Time Step
xb
identification Identification + control
0 1000 2000 30007.725
7.73
7.735
7.74
Bo
ilu
p
0 1000 2000 3000
1.06
1.08
1.1
Refl
ux
Time Step
identification Identification + control
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
Sensitivity Studies of Design and Uncertainty Sensitivity Studies of Design and Uncertainty Effects on CostEffects on Cost
• Changing design affects mainly capital cost– More trays, higher capital cost
• Uncertain process parameters affect operating cost– Feed composition
» Lower zF, higher operating cost
– Relative volatility» Lower α, higher operating cost
• Uncertainty in both zF and α leads to significantly higher costs– Avg. operating cost variation - $3,700
– 40,000 columns
– Over $135 million total
• This cost could be diminished if these sources of uncertainty were considered while designing columns
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
Conclusions/Conclusions/Future DirectionsFuture Directions
• Improve operating cost model
– better correlation of cost to energy requirements
• Develop systematic design methodology
– predict column performance, cost, & energy requirements
when many variables are uncertain
• Study other parameter variations
– heat quality
– tray efficiency
http://www.eia.doe.gov/kids/energyfacts/
• More energy efficient columns can be obtained by considering the
effects of dynamics and uncertainty in the design stage
• Design & uncertainty greatly affect costs
– More trays - higher capital cost
– Feed less concentrated in light component - higher operating cost
– Lower relative volatility – higher operating cost
• Many types of uncertainty should be studied simultaneously
– With both lower zF and α, millions of dollars are lost to uncertainty
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
ReferencesReferencesAnnual Energy Outlook 2003. Energy Information Association, DOE, 2003.
http://tonto.eia.doe.gov/FTPROOT/forecasting/0383(2003).pdfBansal, Vikrant, John D. Perkins, and Efstratios N. Pistikopoulos, A Case Study in Simultaneous Design
and Control Using Rigorous, Mixed-Integer Dynamic Optimization Models, Ind. Eng. Chem. Res. 2002, 41, 760-778.
Bequette, B. Wayne, Process Dynamics: Modeling, Analysis, and Simulation, Prentice Hall PTR, New Jersey, 1998.
Doherty, M.F. and M.F. Malone. Conceptual Design of Distillation Systems. McGraw-Hill, 2001.Douglas, James M. Conceptual Design of Chemical Processes. McGraw Hill, 1988.Eldridge, R. Bruce and A. Frank Seibert. Hybrid Separations/Distillation Technology: Research
Opportunities for Energy and Emissions Reduction, 2005.Energy and Environmental Profile of the U.S. Petroleum Refining Industry. U.S. DOE/OIT, December 1998.
http://www.eia.doe.gov/emeu/mecs/iab98/petroleum/sector.htmlFelder, Richard M. and Ronald W. Rousseau. Elementary Principles of Chemical Processes, 3rd ed. John
Wiley & Sons, New York, 2000.Malcolm, A. and A. A. Linninger, Integrating systems design and control using dynamic flexibility analysis,
submitted to I&ECR, 2006.Manufacturing Energy Consumption Survey. Energy Information Administration, DOE, 2001.
http://www.eia.doe.gov/emeu/mecs/iab98/petroleum/energy_use.htmlNIST – National Institute of Standards and Technology – Chemistry WebBook Database. Accessed Wed,
May 31, 2006.Perry, Robert H., Don W. Green. Perry's Chemical Engineers' Handbook. The McGraw-Hill Companies, Inc.,
1999.Seader, J.D. and Ernest J. Henley. Separation Process Principles. John Wiley & Sons, Inc., New York, 1998.World Crude Oil Prices. Energy Information Association, DOE, 2006. http://
tonto.eia.doe.gov/dnav/pet/pet_pri_wco_k_w.htm
LPPD LPPD Jamie Polan, LPPD ◦ Chicago, Illinois ◦ REU, Summer 2006
AcknowledgementsAcknowledgements
• Supplement from NSF DMI 0328134 “CLEAN CHEMICAL MANUFACTURING UNDER UNCERTAINTY” PI Andreas A. Linninger
• Professor Andreas Linninger
• Andrés Malcolm
• LPPD
http://www.schoolscience.co.uk/petroleum/index.html