Saving Energy in Fractionation Operation Texas Technology Showcase 2006
Presenter Doug White Principal Consultant and Vice President, APC Services Process Systems and Solutions Emerson Process Management Houston, Texas
Fractionation Energy Over 40000 distillation/ fractionation columns in the US alone Consume 40% - 60% of the total energy used in chemical and refining plants Consume 19% of the total energy used in manufacturing plants in the US Reference: Office of Industrial Technology: Energy Efficiency and Renewable Energy; US Department of Energy Washington, DC Distillation Column Modeling Tools
Presentation Objectives Present general approaches to saving energy in fractionation/ distillation through improved control Present techniques for economic analysis that recognize non-linear character of distillation operation and effects of product blending
Case Study PC FC LC FC Feed, F 20,000 BPD $60/ Bbl C3 25% nc4 25% nc5 25% nc6 25% LC TC Reflux, R FC Steam AR 10$/MMBTU Distillate, D < 3%C5 ;$60/ Bbl >3%C5; $40/ Bbl Bottoms, B < 5%C4; $80/ Bbl > 5%C4; $60/ Bbl AC Reboiler, E
Saving Energy in Fractionation Closer Control to Specifications Optimize Energy Usage versus Recovery Minimize Pressure
Distillation Column Control Savings Cost Per Year Excess Reflux 20000 BPD Stabilizer Column $10/ MM BTU Steam $/ Yr $700,000 $600,000 $500,000 $400,000 $300,000 $200,000 $100,000 $0 5 10 25 50 % Excess Reflux
Material Balance
Product Value Product Value; $/ Day Optimum is to operate as close to the spec as possible Spec Assumptions: Constant Reflux; No Variability in Control 0.5 1.0 1.5 2.0 2.5 Bottom Product Composition; %
Debutanizer Material Balance Effects 12.00% Debutanizer 20000 BPD Constant R/D Debutanizer 20000 BPD Constant B/F 10.00% B 10.00% Composition, % 8.00% 6.00% 4.00% 2.00% D Compositon, % 8.00% 6.00% 4.00% 2.00% D B 0.00% 9 9.5 10 10.5 11 11.5 B/F Ratio 0.00% 3 3.2 3.4 3.6 3.8 4 4.2 4.4 R/D Ratio Material Balance Control Has Strongest Effect on Composition
Effect of Variability Standard Analysis Specification Limit Average Composition Frequency of Occurrence y 61% of peak height 14% Mean y(x)= 1 e 2 1 2 x mean 2 1 SD 16% of area 2 SD 2% of area Time Composition
Effect of Reduced Variability $ PROFIT SPECIFICATION LIMIT POOR CONTROL REDUCED VARIABILITY IMPROVED PROFIT BY CHANGING TARGET
Reduced Variability Options PV distribution for original control Original Set Point Upper Limit 2-Sigma 2-Sigma New Set Point value PV distribution for improved control Extra margin without improved control 2-Sigma 2-Sigma
Product Value with Variability Product Value; $/ Day Spec Mean Value Initial Operating Target Initial Variability 0.5 1.0 1.5 2.0 2.5 Bottom Product Composition; %
Product Value with Variability Reduced Same Setpoint Product Value; $/ Day New Mean Value Old Mean Value Spec Initial Operating Target Reduced Variability 0.5 1.0 1.5 2.0 2.5 Bottom Product Composition; %
Product Value with Variability Product Value; $/ Day New Mean Value Spec Profit Increase Old Value Reduced Variability For any given standard deviation it is possible to calculate the optimum setpoint. 0.5 1.0 1.5 2.0 2.5 Bottom Product Composition; %
Debutanizer - Net Profit Curve D eb u tan izer 20000 B P D 5% B tm C o m p 2 5 0000 2 0 0000 Net Profit, $/ Day 1 5 0000 1 0 0000 5 0000 0 0.0 0 1.0 0 2.0 0 3.0 0 4.0 0 5.0 0 6.0 0 D istillate C omposition s, %
Debutanizer Optimum Setpoint With Variability Profit, $/ Day 250000 225000 200000 175000 Debutanizer 20000 BPD 5% Btm Comp Variability Effect on Optimum Setpoint Standard Deviation 0 0.3 0.6 150000 0 0.5 1 1.5 2 2.5 3 Distillate Compositon, % Optimum Setpoint Depends on Variability
Effect of Blending Column Product Shipped Product Proposition: Since actual specification is on shipped product rather than column product directly, small excursions over the specification don t matter and can be handled by blending. Is this correct?
Debutanizer Nonlinear Energy Effects Debutanizer 20000 BPD 5% Btm Comp 18000 16000 Reboiler Cost; $/ Day 14000 12000 10000 8000 6000 4000 2000 0 0.00 1.00 2.00 3.00 4.00 5.00 6.00 Distillate Composition, %
Non-Linear Effects Energy Cost Expected Value For nonlinear relationship, the expected value of the energy cost is NOT at the value equivalent to the median of the composition; It s value depends on the standard deviation of the composition Probability Distribution More Pure Composition Less Pure
Variability Vs Energy Debutanizer 20000 BPD 5% Btm Comp; 3% Distil Comp Variability Effect on Energy Usage Energy Cost, $/ Day 13200 13100 13000 12900 12800 12700 12600 12500 12400 12300 0 0.2 0.4 0.6 0.8 1 Distillate Composition Standard Deviation, %
Energy Balance Control
Profitability Product Value, $/day High Energy Cost, $/day $/ Day Low Energy Cost, $/day Low Energy Cost Profit $/day High Energy Cost Optimum Low Energy Cost Optimum Reflux High Energy Cost Profit $/day
Profitability with variability $/ Day Mean Value Profit $/day Assumptions: Constant Bottoms Composition Current Variability Optimum Reflux BPD
Profitability with variability $/ Day Profit Increase Old Value New Value Reduced Variability; Same Mean Profit $/day Assumptions: Constant Bottoms Composition For locally quadratic objective function the benefits of reduced variability can be calculated analytically Optimum Reflux BPD
Pressure Effects
Column Pressure Effect Relativ e Reboiler Cost Per Year Column Pressure Effect Constant Separation 20000 BPD Stabilizer $6 $5 $4 $ MM/ Yr $3 $2 $1 $0 100 120 140 160 180 200 Pressure, PSIA
Summary - Saving Energy in Fractionation Closer Control to Specifications Optimize Energy Usage Minimize Pressure
Questions? Comments? doug.white@emersonprocess.com More material on subject: http://www.emersonprocess.com/solutions/services/aat