Biorefineries. Courtney Waller James Carmer Dianne Wilkes Sarosh Nizami

Transcription

1 Biorefineries Courtney Waller James Carmer Dianne Wilkes Sarosh Nizami

2 Background Biorefinery: Biomass conversion Fuels, power, chemicals [4]

3 Background There is a wide variety of Biomass Feestock in the United States Mass Production of many different chemicals from biomass is not a common practice [8]

4 Background World Energy Problem: Refining Fossil Fuels Releases greenhouse gases, causing global warming

5 Background World Energy Problem: Decreasing fossil fuels [2]

6 Proposal By having ONE refinery that will produce many things from many feedstocks, utilities, power, and energy will be conserved Chemicals that may be used for energy (biodesiel and bio-gasoline) will help solve the world energy problem and decrease the amount of fossil fuels burned

7 Advantages Minimizes Pollution Reduces Waste [5]

8 Products Ethanol Plastics Solvents Adhesives Lubricants Chemical Intermediates [7] [6]

9 But.Its not that simple Many, many different decisions to make when considering constructing and operating a biorefinery! [11]

10 Types of Biorefineries Phase 1: fixed processing capabilities Phase 2: capability to produce various end products and far more processing flexibility Phase 3: mix of biomass feedstocks and yields many products by employing a combination of technologies. [6]

11 Utilities and Biorefineries But would it be more profitable to integrate all processes into one refinery??

12 Utilities and Integrated Biorefineries One power plant for all processes: centralized utilities

13 Utilities and Integrated Biorefineries Overhead is minimized Utilities can be produced and distributed to each process Therefore, it is more profitable!

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15 How many different options? Whether or not to build each process: 2 options for every process: = ,777,216 options!!! Not including: Different Flow Rates Input Options Expansions

16 Narrowing it down Mathematical Model Objective: Maximize the Net Present Value Eliminate processes/products that are the least profitable Select the most profitable processes and their corresponding capacities and production rates throughout the project lifetime

17 Mathematical Model Net Present Value: NPV = ( cash( ) df t The Net Present Worth (NPW) is the total of the present worth of all cash flows minus the present worth of all capital investments.

18 Mathematical Model Fixed Capital and Capacity FC(i) = α (i) Y(i, + β (i) capacity(i, i FC(i) investment αis minimal cost to build a process, β is incremental capacity cost, and Y(i, is binary variable (0 or 1) that determines whether process will be built

19 Mathematical Model capacity(i, Y(i, maxcapacity(i, 0 capacity(i, Y(i, mincapacity(i, 0 j output(i, j, capacity(i, Process may not exceed maximum and minimum capacity requirements If Yi=0, then capacity also is 0; therefore, the process will not be built

20 Mathematical Model input(i, j, = raw(i, j, + k i flow(k,i, j, input(i,j, is the amount of chemical j that is input into process i flow(i,k,j, represents the flow of a chem. j from process i to k raw(i,j, is the amt of raw material to be bought for process i

21 Mathematical Model input(i, j, = f(i, j) jj input(i, jj, output(i, j, = g(i, j) jj output(i, jj, f(i,j) relates amounts of each input needed for each process g(i,j)relates amounts of each product from process i

22 Mathematical Model Mass Balances around each process: output(i,j, output(i, j, = i = sales(i,j, sales(i,j, is the amount of chemical j from process i that is sold i input(i, + k i j, flow(i,k, j,

23 Mathematical Model flow(i, k, j, = γ (i, j, k) output(i, j, materials( = raw_price(j, raw(i, j, i, j γ(i,j,k) defines the possible transfer of products as output of process i to be used as input into process j

24 Review intermediates PROCESS raw materials Build? sales market one Capacity intermediates market two

25 Mathematical Model operatingcost(i, = δ (i) Y(i, + ε (i) δis the minimum operating cost, ε is the incremental operating cost j output(i, j, revenue(j, = price(j, i sales(i, j, sales(i, j, i demand(j,

26 Mathematical Model 1 Y(i, X(i, Y(i, X(i, expansions allowable number of X(i, 0 minexpansion(i, X(i, expansion(i, 0 maxexpansion(i, X(i, expansion(i, expansion(i, -1) t capacity(i, capacity(i, T t t + + =

27 Mathematical Model utilityrequirements(i, u, utilities(i, u, utilities( i, u, utilitycapacity(u, i utilitycapacity(u, - Z(u, maxutilitycapacity(u) 0 utilitycapacity(u, - Z(u, minutilitycapacity(u) 0 FCutilities(u, = a(u) Z(u, + b(u) utilitycapacity(u, utilitycos t(u, = c(i) t' < t t' Z(u, t' ) + d (u) i utilities( i, u,

28 Mathematical Model cash( = revenue(t -1) - operatingc ost(t -1) - investment (t investment ( = FC(i, + i u FCutilitie s(u, -1) - materialco st(t -1) investment ( cash(t NPV = t cash( df -1)

29 Overview intermediate PROCESS raw materials Build? Expand? sales market one market two utilities Capacity intermediates

30 Overview Building/Expansions Capacity Fixed Capital Investment Utilized Capacity Operating Costs Required Utilities Utilitity Capacity/Investment Input/Output Sales Intermediate chemicals

31 GAMS File

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34 Where do the parameters come from? Determine process specifics Equipment Reaction Endothermic/exothermic Required utilities Labor requirements

35 Where do the parameters come from? Graph of FCI vs. Feed Rate αis the y-intercept βis the slope Graph of the Operating Cost vs. Feed Rate δis the y-intercept εis the slope

36 Simulations on the Individual Process From SuperPro & ProII: Feed Rates between 10 to 10,000 kg/hr Equipment costs Utility costs Profitability

37 Reactor Cost vs. Feed Rate $700,000 $600,000 y = x $500,000 Cost ($) $400,000 $300,000 y = FCI Operating Cost electricity $200,000 $100,000 y = x $ kg/year

38 Ethyl Lactate Water Lactic acid Ethanol CSTR Distillation Column The utilities ranged from 8 kwh to 8000 kwh. Equipment Costs ranged from $334,500 to $775,000 Ethyl lactate

39 Ethyl Lactate Costs Cost $ FCI Operating Costs Feed Rate (1000 kg/yr) Operating Costs do not include utilities.

40 Minimum Equipment Size Fermentor was 225 liters. Reactor was 50 liters. CSTR for Dilactide 4.0 ft 3 Distillation Column for Ethyl Lactate 4.0 ft 3

41 Results!!! From more than 16 million options. Run this model in 90 seconds

42 Results: 5 Million Dollar Investment year Ethanol Lactic Dilactide Levullinic Succinic Eth. Lact VAM PVA building expansion Investment: 5 million NPV: 27.9 million

43 Results: 5 Million Dollar Investment dollars (millions) revenue costs time

44 Results: 5 Million Dollar Investment dollars (millions) cash re-investment year

45 Results: 20 Million Dollar Investment Year Ethanol Lactic A Dilactide Levullinic Succinic Eth. Acet VAM PVA building expansion Investment:20 million NPV: 24.5 million

46 Results: 20 Million Dollar Investment dollars (millions) 10 5 cash re-investment year

47 Results: Variable Investment

48 Results: Variable Investment year Ethanol Lact.A Dilactide Levullinic Succinic Ethyl Acet VAM PVA building expansion Investment: 7.5 million NPV: 28.8 million

49 Results: Variable Investment dollars (millions) costs revenue year

50 Results: Variable Investment dollars (millions) cash re-investment year

51 Results: Investment Comparison dollars (millions) investment year

52 Results: Non-integrated Processes Ethanol Lactic A Levullinic building expansion Investment: 5.1 million NPV: 24.1 million

53 Results: Non-integrated Processes

54 Results: Non-integration vs. Integrated dollars (millions) integrated non-integrated year

55 Results: Increasing Prices year Ethanol Lact. A Ethyl Lact Dilactide Levullinic Succinic Syngas Ethyl Acet VAM PVA building expansion Investment: 12.9 million NPV: 83.6 million

56 Results: Increasing Prices dolla rs (m illions ) cash re-investment year

57 Results: Increasing Prices

58 Recommendations Products/waste can be used in the power generation plant instead of purchasing burning material from outside source Location options

59 Conclusion Our model can be used to find optimal operating conditions for a biorefinery!! Biorefineries that can produce a variety of products are more economical and profitable!! [10]

60 Questions?

61 References 1. Dreamstime. Refinery Pollution Earth Trends: The environmental information portal. 05&theme= Energy Kids Page Biorefineries: Current Status, Challenges, and Future Direction. S. Fernando, S. Adhikari, C. Chandrapl, and N. Murali. Energy and Fuels 2006, 20, Cane Harvesters