Saving Energy in Fractionation Operation. Texas Technology Showcase 2006

Transcription

1 Saving Energy in Fractionation Operation Texas Technology Showcase 2006

2 Presenter Doug White Principal Consultant and Vice President, APC Services Process Systems and Solutions Emerson Process Management Houston, Texas

3 Fractionation Energy Over 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

4 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

5 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

6 Saving Energy in Fractionation Closer Control to Specifications Optimize Energy Usage versus Recovery Minimize Pressure

7 Distillation Column Control Savings Cost Per Year Excess Reflux BPD Stabilizer Column $10/ MM BTU Steam $/ Yr $700,000 $600,000 $500,000 $400,000 $300,000 $200,000 $100,000 $ % Excess Reflux

8 Material Balance

9 Product Value Product Value; $/ Day Optimum is to operate as close to the spec as possible Spec Assumptions: Constant Reflux; No Variability in Control Bottom Product Composition; %

10 Debutanizer Material Balance Effects 12.00% Debutanizer BPD Constant R/D Debutanizer 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% B/F Ratio 0.00% R/D Ratio Material Balance Control Has Strongest Effect on Composition

11 Effect of Variability Standard Analysis Specification Limit Average Composition Frequency of Occurrence y 61% of peak height 14% Mean y(x)= 1 e x mean 2 1 SD 16% of area 2 SD 2% of area Time Composition

12 Effect of Reduced Variability $ PROFIT SPECIFICATION LIMIT POOR CONTROL REDUCED VARIABILITY IMPROVED PROFIT BY CHANGING TARGET

13 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

14 Product Value with Variability Product Value; $/ Day Spec Mean Value Initial Operating Target Initial Variability Bottom Product Composition; %

15 Product Value with Variability Reduced Same Setpoint Product Value; $/ Day New Mean Value Old Mean Value Spec Initial Operating Target Reduced Variability Bottom Product Composition; %

16 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 Bottom Product Composition; %

17 Debutanizer - Net Profit Curve D eb u tan izer B P D 5% B tm C o m p Net Profit, $/ Day D istillate C omposition s, %

18 Debutanizer Optimum Setpoint With Variability Profit, $/ Day Debutanizer BPD 5% Btm Comp Variability Effect on Optimum Setpoint Standard Deviation Distillate Compositon, % Optimum Setpoint Depends on Variability

19 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?

20 Debutanizer Nonlinear Energy Effects Debutanizer BPD 5% Btm Comp Reboiler Cost; $/ Day Distillate Composition, %

21 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

22 Variability Vs Energy Debutanizer BPD 5% Btm Comp; 3% Distil Comp Variability Effect on Energy Usage Energy Cost, $/ Day Distillate Composition Standard Deviation, %

23 Energy Balance Control

24 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

25 Profitability with variability $/ Day Mean Value Profit $/day Assumptions: Constant Bottoms Composition Current Variability Optimum Reflux BPD

26 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

27 Pressure Effects

28 Column Pressure Effect Relativ e Reboiler Cost Per Year Column Pressure Effect Constant Separation BPD Stabilizer $6 $5 $4 $ MM/ Yr $3 $2 $1 $ Pressure, PSIA

29 Summary - Saving Energy in Fractionation Closer Control to Specifications Optimize Energy Usage Minimize Pressure

30 Questions? Comments? More material on subject: