1 / 50

Hella Tokos and Zorka Novak Pintarič

COMPUTER AIDED PROCESS ENGINEERING FOR INTEGRATION OF INDUSTRIAL PROCESSES. Hella Tokos and Zorka Novak Pintarič. Outline. Introduction Water network integration Basic formulation Modification of basic mathematical model Results of water network integration Heat integration retrofit

bambi
Download Presentation

Hella Tokos and Zorka Novak Pintarič

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. COMPUTER AIDED PROCESS ENGINEERING FOR INTEGRATION OF INDUSTRIAL PROCESSES HellaTokos and Zorka Novak Pintarič

  2. Outline • Introduction • Water network integration • Basic formulation • Modification of basic mathematical model • Results of water network integration • Heat integration retrofit • Basic formulation • Modification of basic mathematical model • Results of heat integration retrofit • Selection of optimal polygeneration system • Mathematical model for polygeneration • Results of polygeneration

  3. Introduction • In real industrial applications, mathematical models often need several modifications • in order to suit the specific industrial circumstances and • to give useful results for the company. INDUSTRIAL PROBLEM Incorrect balance Data collection Measurements Determination of water balance Determination of heat balance Consulting whit industry Correct balance Additional constraints Modeling Optimization Consulting whit industry PROBLEM SOLUTION

  4. WATER NETWORK integration

  5. Basic formulation (Kim and Smith, 2004) Fig 1. Superstructure for water re-use between batch processes.

  6. Basic formulation (Kim and Smith, 2004) Overall water mass balance: (1) Mass load balance in each operation: (2) Water mass balance in each operation: (3)

  7. Basic formulation (Kim and Smith, 2004) Feasibility constraints on the inlet and outlet concentration: (4) (5) Upper and lower bounds for the water flow: (6)-(7) (8)-(9) (10)-(11)

  8. Basic formulation (Kim and Smith, 2004) Logic constraint for existence or non-existence of a storage tank: (12) Storage tank capacity: (13) • The objective function, is the overall cost of the water network that • involves: • the freshwater cost, • annual investment cost for the storage tank and • annual investment cost for piping.

  9. Modification of the original model • The original model was modified over three main steps: • Water re-use between batch and (semi)continuous processes with moderate contaminant concentration. • Installation of intermediate storage tanks for collection of unused continuous wastewater streams that can be used over the subsequent time intervals. • Installation of a local (on-site) wastewater treatment unit operating in batch or in continuous mode.

  10. Mathematical model extended with continuous streams Fig 2. Superstructure for water re-use between batch and continuous processes.

  11. Mathematical model extended with continuous streams Limiting water mass of the (semi)continuous stream ww: (14) Outlet water mass from the (semi)continuous stream ww: (15)

  12. Mathematical model with storage tanks for continuous streams Fig 3. Superstructure for direct and indirect water re-use between batch and continuous processes.

  13. Mathematical model with storage tanks for continuous streams Mass of wastewater from the (semi)continuous operation ww: (16) Logic constraint for existence or non-existence of a storage tank for (semi)continuous operation ww: (17) Storage tank capacity for wastewater from (semi)continuous operation ww: (18)

  14. Mathematical model with local treatment units Fig 4. Superstructure for water re-use and regeneration re-use in batch/semi-continuous processes.

  15. Mathematical model with local treatment units 1. Batch local treatment units a) Mass balance constraints The mass balance for each operation: (19) Feasibility constraints on the inlet and outlet concentration: (20) Additional equations for upper and lower bounds of water mass purified in localtreatmentunits are: (21)-(22)

  16. Mathematical model with local treatment units The capacity of the local treatment unit: (23) Outlet concentration from local treatment unit: (24)

  17. Mathematical model with local treatment units b) Time schedulingof batch treatment units Fig 5. Treatment time of batch local treatment unit.

  18. TR Δt E, TR E S, TR S tr t t t t nc, tr n nc nc, tr Mathematical model with local treatment units The starting time of purification of wastewater from unit nc in localtreatment unit tr : (25) (26) For processes operating within the same time intervalj : (27) The ending time of the purification is: (28)

  19. TR Δt B, TR A, TR S S, TR E, TR E tr t t t t t t nc,n, tr n nc, tr nc nc, tr nc,n, tr Mathematical model with local treatment units The purification of wastewater from process nc in treatment unit trhas to be completed before process n starts: (29) (30) The waiting times before and after treatment are: (31) (32) The waiting times of unselected treatment connectionsare forced to zero by thefollowing constraints: (33) (34)

  20. TR Δt E S, TR E, TR S tr t t t t nc nc, tr n nc, tr Mathematical model with local treatment units c) Storage tank after treatment unit Constraints used to identify those processes nc that need the installation of a storage tank for purified water after treatment are: (35) (36) The required storage tank capacity after purification is: (37)

  21. TR Δt E S S, TR E, TR tr t t t t nc nc, tr n nc, tr Mathematical model with local treatment units d) Storage tank before treatment unit Constraints used to identify those processes nc that need the installation of a storage tank for purified water before treatment are: (38) (39) The required storage tank capacity before the treatment unitis: (40) 2. Continuous local treatment units The scheduling of the continuous treatment unit only differs from that of the batch treatmentunit, when defining the treatment ending time: (41)

  22. Objective function • The objective function, FObj, is the overall cost of the water network that involves • the freshwater cost, • annual investment costs for the storage tank, • annual investment cost for piping, • annual investment costs for the local treatment unit • and wastewater treatment costs. (42)

  23. Objective function Freshwater cost: (43) Annual investment costs of storage tank installation: (44) Wastewater treatment cost: (45)

  24. Objective function Annual investment cost for piping: (46) • Annual investment costs for the local treatment unit: (47)

  25. Indirect water re-use between continuous and batch processes On-sitewastewatertreatment unit Identification of intra- and inter-daily connections Solution strategy Modifications of the original model Direct water re-use between continuous and batch processes Multi-level design strategy Separated integration of packaging area Separated integration of production area Identification of intra-daily connections FINAL DESIGN

  26. Results of industrial case study • Freshwaterconsumption is reduced by 21% ; • Totalinvestment: 167,460 EUR; Net present value : 892,811 EUR; Paybackperiod: 1.2 a Fig 6. Optimal water network in the production area.

  27. Results of industrial case study Fig 7. Optimal water network in the packaging area. • Freshwaterconsumption reduced by 21,2% ; • Totalinvestment is 23,647 EUR; Net present value: 675, 099 EUR; Paybackperiod: 0,25 a

  28. Results of industrial case study Freshwater consumption reduced by 25% Fig10. Water network in production and packaging area(Monday to Wednesday).

  29. Results of industrial case study Freshwater consumption reduced by 22% Fig11. Water network in production and packagingarea (Thursday).

  30. Results of industrial case study Freshwater consumption reduced by 31 % Fig12. Water network in production and packaging area (Friday).

  31. Results of industrial case study Packaging area Production area Fig13.Final water network in a brewery. • Freshwaterconsumption reduced by 26,5% • Totalinvestment is 828,528EUR; Net present value: 1,486,919 EUR; Paybackperiod: 2.7 a

  32. Heat integration retrofit

  33. Basic formulation (Lee and Reklaitis, 1995) tI i, j LP tP j tE i, j Initial operating schedule tF i, j tCYCLE, MIN CP j Utility savings MILP Tdj Final operating schedule Tsj Fig 14. Schematic diagram of the mathematical model.

  34. Basic formulation (Lee and Reklaitis, 1995) Finishing time of batch i in unit j: (1) Exit time of batch i from unitj: (2) Input time of the next batch in unit j: In-phase stage: Out-of-phase stage: (3)-(4)

  35. Basic formulation (Lee and Reklaitis, 1995) Starting time of the next unit, j + 1: (5) (6) Cycle time for each unitj: (7) (8) The cycle time of the production, has to be greater than or equal to the cycle time required for each unit: (9)

  36. Basic formulation (Lee and Reklaitis, 1995) The repeated cyclic pattern of heat integration matches over the whole production campaignis ensured with the same operating time schedule: (10) Scheduling before heat integration Scheduling after heat integration

  37. Basic formulation (Lee and Reklaitis, 1995) The heat exchange between two streams is possible: (11) The model allows only one-to-one matches between streams: (12) Heat exchanged between the streams: (13) Total utility required for the production of one batch: (14) Objective function: (15)

  38. Modification of the original model • Operations without heat transfer are included • One-to-two matches • Economic objective function in-phase stage in-phase stage out-of-phase stage (16)

  39. Modification of the original model Area of the heat exchanger : (17) Available heat transfer area of the production vessel: (18) Investment of the heat exchanger: (19) Differential cash flow of retrofitted solution: (20) (21) Objective function:

  40. Results of industrial case study Fig15.Schematic diagram of production in the brewhouse before heat integration retrofit a) and after retrofit b).

  41. Results of industrial case study • Two matches were predicted by the optimization model: • heating the adjunct mash by the waste vapour produced during boiling and • heating the mash by the heat released during wort clarification in whirlpool • The heat exchange of the first match can be accomplished by a half-pipe coil jacket on the adjunct mash tun. • Utility savings: 434,690 EUR/a. • Required heat exchange area: 59 m². • Investment: 12,590 EUR. • The net present value is positive at discount rate of 10 %. • The payback period: around 11 days. • The second match was rejected by the company, • it can not satisfy the total heat demand of the mashing stage

  42. POLYGENERATION

  43. Mathematical model for polygeneration Fig16.Superstructure of mathematical model for selecting the optimal polygeneration system.

  44. Mathematical model for polygeneration • Cogeneration system with back-pressure steam turbine Monthly electricity production: (1) Annual electricity production: (2) Increase in fuel consumption: (3) Tax relief on the reduced carbon dioxide emission: (4)

  45. Mathematical model for polygeneration The cash flow: (5) Investment in polygeneration system: (6) • Cogeneration system with back-pressure steam turbine • - increased heat production during heating season (7)

  46. Mathematical model for polygeneration Upper bound of heat production increase: (8) The cash flow: (9) Investment in the polygeneration system: (10)

  47. Mathematical model for polygeneration • Cogeneration system with open-cycle gas turbine The produced “green energy” : (11) The cash flow: (12) • Trigeneration system with back-pressure steam turbine

  48. Mathematical model for polygeneration Logical constraint for the selection of optimal polygeneration system: (13) Objective function: (14)

  49. Results of industrial case study • The optimal polygeneration system is: • Cogeneration system whit a back-pressure steam turbine at a pressure level of 42.2 bar • The heat production would be increased during the heating season by 50 %. • The electricity production would cover 42.5 % of the current brewery’s consumption. • The net present value is positive and the payback period is 3.2 a. • The disadvantage of this solution is that the plant would become dependent on external consumers of surplus heat energy. Fig 17. Cogeneration system with back-pressure steam turbine.

  50. Thank you for your Attention! zorka.novak@uni-mb.si

More Related