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A user workflow for combining process simulation and pinch analysis considering ecological factors

  • Benjamin H. Y. Ong , Edward J. Lucas , Donald G. Olsen EMAIL logo , Simon Roth and Beat Wellig
Published/Copyright: April 29, 2021
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Chemical Product and Process Modeling
From the journal Chemical Product and Process Modeling Volume 17 Issue 4

Abstract

This paper aims to develop an innovative and practical method to accelerate Pinch Analysis problems using a combination of process integration, process simulation tools, and life cycle assessment techniques to design effective industrial energy efficiency measures rapidly. Data extraction and analysis is accelerated using the workflow, reducing pinch analysis duration, and therefore cost. This lowers financial barriers and is expected to help facilitate an increase in the number of conducted pinch analyses each year. An innovative ecological targeting step has been included in the workflow, which represents the option for end-users to further their CO2 savings, once energy targeting has been completed on a purely cost basis. It is expected that optimizing for costs first will enable the implementation of heat recovery solutions in industry. The methodology is applied to an example case study, and the learnings from industrial application is reported.

Keywords: heat exchanger network; life cycle analysis; process integration; process optimization; process simulation
Corresponding author: Donald G. Olsen, Lucerne University of Applied Sciences and Arts, Competence Center Thermal Energy Systems and Process Engineering, Technikumstrasse 21, 6048, Horw, Switzerland, E-mail:

Funding source: Swiss Innovation Agency Innosuisse

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This research project is financially supported by the Swiss Innovation Agency Innosuisse and is part of the SCCER EIP. Further support is provided by the Lucerne University of Applied Sciences and Arts, Switzerland.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

Appendix

Table 4:

Life cycle inventory of brazed plate heat exchanger production.

Activity name Geography Unit Brazed plate heat exchanger production Comment
Geography RER
Unit m2
Reference product Brazed plate heat exchanger production RER m2 A
Inputs from technosphere Market for steel, chromium steel 18/8, hot rolled GLO kg 0.9·m HEX (A) [29, 30, 33]
Metal working, average for chromium steel product manufacturing RER kg 0.9·m HEX (A) [33]
Market for copper GLO kg 0.1·m HEX (A) [29, 30, 33]
Market for sheet rolling, copper GLO kg 0.1·m HEX (A) [33]
Metal working, average for copper product manufacturing RER kg 0.1·m HEX (A) [33]
Table 5:

Life cycle inventory of brazed plate heat exchanger, at plant.

Activity name Geography Unit Brazed plate heat exchanger, at plant Comment
Geography CH
Unit m2
Reference product Brazed plate heat exchanger, at plant CH m2 A
Inputs from technosphere Brazed plate heat exchanger production RER m2 A
Market for corrugated board box RER kg 0.56·10−6 kg/mm2·A P (A) m ccb (A), [29, 30, 33, 38]
Market for packaging film, low density polyethylene GLO kg 0.925·10−6 kg/mm3·0.023 mm·3·A P (A) m pf (A) [29, 30, 33, 39], three layers
Market for transport, freight, lorry, unspecified RER tkm (m HEX (A) + m ccb (A) + m pf (A))/1000 kg/t·2000 km Reference [33], transport from Sweden to Switzerland
Market for waste polyethylene CH kg m pf (A) [33]
Table 6:

Life cycle inventory of operation, brazed plate heat exchanger.

Activity name Geography Unit Operation, brazed plate heat exchanger Comment
Geography CH
Unit Year
Reference product Operation, brazed plate heat exchanger CH year LT
Inputs from technosphere Brazed plate heat exchanger, at plant RER m2 A
Table 7:

Brazed plate heat exchanger specifications [28], [31].

Manufacturer Model Weight Height Width Length
(kg) (mm) (mm) (mm)
Alfa laval CB10/CBH10 0.13 + 0.04·n 191.5 73.5 7 + 2.16·n
CB11/CBH11 0.132 + 0.04·n 192 74 7.4 + 2.14·n
CB16/CBH16 0.14 + 0.04·n 209.5 73.5 7 + 2.16·n
CB18/CBH18 0.22 + 0.07·n 315.5 73.5 7 + 2.16·n
CB20 0.6 + 0.08·n 324 94 8 + 1.5·n
CB30/CBH30/CBP30 1.2 + 0.11·n 313 113 13 + 2.31·n
CB60/CBH60 2.1 + 0.18·n 527 113 13 + 2.32·n
CB62/CBH62 2.1 + 0.18·n 529 113 13 + 1.98·n
CB65/CBH65 2.1 + 0.14·n 535 120.5 11.5 + 1.4·n
CB110/CBH110/CBP110 4.82 + 0.35 · n 768 191 15 + 2.56·n
CB112/CBH112/CBP112/CBXP112 4.82 + 0.35·n 616 191 16 + 2.07·n
CB200/CBH200 12 + 0.6·n 742 324 11 + 2.7·n
CB300/CBH300 21 + 1.26·n 990 366 11 + 2.62·n
CB400 24 + 1.35·n 990 390 14 + 2.56·n
CB410 30 + 1.14·n 793 490 14.2 + 2.17·n
CBXP27 2 + 0.13·n 310 111 13 + 2.4·n
CBXP52 2.5 + 0.22·n 526 111 14 + 2.37·n
SWEP B5T 0.50 + 0.044·n 193 76 4.00 + 2.24·n
B10T 1.15 + 0.096·n 289 119 4.00 + 2.24·n
B12 1.12 + 0.12·n 287 117 4.40 + 2.34·n
B15T 1.25 + 0.104·n 468 76 4.00 + 2.24·n
B16 1.48 + 0.12·n 376 119 4.00 + 2.24·n
B28 2.09 + 0.164·n 526 119 4.00 + 2.24·n
B30 5.88 + 0.18·n 243.50 243.50 14.00 + 2.12·n
B35T 15.76 + 0.256·n 393 243 22.00 + 2.26·n
B60 16.16 + 0.47·n 374 364 16.00 + 2.14·n
B65 27.44 + 1.03·n 864 363 17.00 + 2.32·n
B80 2.09 + 0.164·n 526 119 4.00 + 2.24·n
B315 6.98 + 0.312·n 392.50 242.50 10.00 + 2.86·n
B633 80.33 + 1.224·n 830 537 61.38 + 2.39·n
B649 79.45 + 1.941·n 1232 537 45.08 + 2.09·n
Table 8:

Environmental impacts of utility systems based on eco-invent 3.5, cut-off system model [33].

Category Technology Unit Geography Cumulative energy demand total (mJ eq) Cumulative energy demand non-renewable (mJ eq) Cumulative energy demand renewable (mJ eq) CO2 equivalent (kg CO2 eq) Eco-points (UBP)
Heat Hard coal Hard coal industrial furnace 1–10 MW mJ RER w/o CH 1.28 1.26 0.02 0.138 119.6
Coke Coal coke industrial furnace 1–10 MW mJ RoW 1.34 1.32 0.02 0.153 208.9
Diesel Heat and power co-generation, 200 kW electrical, SCR-NOx reduction mJ CH 0.44 0.44 0.00 0.032 23.3
Light fuel oil Industrial furnace 1 MW mJ CH 1.37 1.36 0.01 0.090 70.1
Heavy fuel oil Industrial furnace 1 MW mJ CH 1.28 1.27 0.01 0.092 78.8
Natural gas Boiler modulating > 100 kW mJ RER w/o CH 1.25 1.24 0.00 0.069 42.5
Boiler condensing modulating > 100 kW mJ RER w/o CH 1.17 1.17 0.00 0.065 39.9
Heat and power co-generation, 200 kW electrical, lean burn mJ CH 0.48 0.48 0.00 0.030 18.9
Heat and power co-generation, 500 kW electrical, lean burn mJ CH 0.46 0.46 0.00 0.029 17.9
Heat and power co-generation, 1 MW electrical, lean burn mJ CH 0.44 0.44 0.00 0.028 17.2
Industrial furnace > 100 kW mJ RER w/o CH 1.26 1.25 0.00 0.070 43.0
Industrial furnace low-NOx > 100 kW mJ RER w/o CH 1.37 1.36 0.01 0.075 47.4
Market, district or industrial mJ CH 0.46 0.46 0.00 0.029 18.0
Other than natural gas Market, district or industrial mJ CH 0.05 0.03 0.02 0.002 2.4
Propane Industrial furnace > 100 kW mJ RoW 1.19 1.19 0.01 0.088 62.9
Solar/electric Hot water tank, flat plate, multiple dwelling MJ CH 2.39 1.55 0.84 0.024 66.2
Solar/gas Hot water tank, flat plate, multiple dwelling mJ CH 1.23 0.93 0.30 0.055 36.8
Steam Energy carrier, chemical industry mJ RER 1.56 1.52 0.04 0.103 73.8
Market, chemical industry mJ RER 1.56 1.52 0.04 0.103 73.8
Straw Furnace, 300 kW mJ GLO 0.17 0.09 0.07 0.010 57.2
Organic, furnace 300 kW mJ GLO 0.34 0.09 0.25 0.009 81.7
Waste Municipal waste incineration, generic market, district or industrial mJ CH 0.00 0.00 0.00 0.000 0.5
Wood chips Heat and power co-generation, 2000 kW mJ CH 0.88 0.03 0.85 0.003 26.6
Heat and power co-generation, 2000 kW, state-of-the-art 2014 mJ CH 0.88 0.03 0.85 0.003 21.7
Heat and power co-generation, 6667 kW mJ CH 0.72 0.02 0.69 0.002 19.3
Heat and power co-generation, 6667 kW, state-of-the-art 2014 mJ CH 0.72 0.02 0.69 0.002 16.0
Heat and power co-generation, 6667 kW, state-of-the-art 2014, label-certified mJ CH 0.72 0.02 0.69 0.002 16.0
Wood chips from industry Furnace 300 kW mJ CH 0.90 0.25 0.65 0.014 62.7
Furnace 300 kW, state-of-the-art 2014 mJ CH 0.85 0.23 0.61 0.013 46.8
Furnace 1000 kW mJ CH 0.90 0.25 0.65 0.013 56.2
Furnace 1000 kW, state-of-the-art 2014 mJ CH 0.85 0.23 0.61 0.012 46.2
Furnace 5000 kW mJ CH 0.90 0.25 0.65 0.013 51.5
Furnace 5000 kW, state-of-the-art 2014 mJ CH 0.84 0.23 0.61 0.012 38.0
Wood chips from post-consumer wood Furnace 300 kW mJ GLO 0.08 0.08 0.01 0.006 30.0
Softwood chips from forest Furnace 300 kW mJ CH 1.31 0.08 1.23 0.006 46.2
Furnace 300 kW, state-of-the-art 2014 mJ CH 1.23 0.08 1.15 0.006 31.3
Furnace 1000 kW mJ CH 1.31 0.08 1.23 0.006 38.5
Furnace 1000 kW, state-of-the-art 2014 mJ CH 1.23 0.08 1.15 0.005 29.6
Furnace 5000 kW mJ CH 1.36 0.08 1.28 0.005 34.1
Furnace 5000 kW, state-of-the-art 2014 mJ CH 1.23 0.07 1.15 0.004 26.3
Hardwood chips from forest Furnace 300 kW mJ CH 1.36 0.08 1.28 0.006 48.3
Furnace 300 kW, state-of-the-art 2014 mJ CH 1.28 0.08 1.20 0.006 33.3
Furnace 1000 kW mJ CH 1.37 0.08 1.28 0.006 42.1
Furnace 1000 kW, state-of-the-art 2014 mJ CH 1.28 0.08 1.20 0.005 33.0
Furnace 5000 kW MJ CH 1.36 0.08 1.28 0.005 37.4
Furnace 5000 kW, state-of-the-art 2014 mJ CH 1.23 0.08 1.15 0.004 26.6
Cooling energy Natural gas Cogen unit with absorption chiller 100 kW mJ CH 2.07 2.00 0.06 0.113 86.0
Market mJ GLO 2.44 2.40 0.04 0.148 114.1
Table 9:

Life cycle inventory of cooling water.

Activity name Geography Unit Cooling energy, from tap water Comment
Geography CH
Unit MJ
Reference product Cooling energy, from tap water CH mJ 1
Inputs from technosphere Market for tap water CH kg 1000 kJ/mJ/(4.2 kJ/(kg·K)·5 K)·1 mJ [33]

References

1. Kaiser, T, Maus, K, Schmitz, R, Faust, A-K, Eckmanns, A, Pulfer, M, et al.. Federal energy research masterplan for the period from 2017 to 2020; 2015. Available from: www.energieforschung.ch.Search in Google Scholar

2. The Intergovernmental Panel on Climate Change. Geneva: The Intergovernmental Panel on Climate Change; 2020. Available from: https://www.ipcc.ch/.Search in Google Scholar

3. Bundesamt für Energie BFE. Schweizerische Gesamtenergiestatistik 2019. Bern, Switzerland: Bundesamt für Energie; 2020.Search in Google Scholar

4. El-Halwagi, MM. Pollution prevention through process integration: systematic design tools. New York: Academic Press; 1997.Search in Google Scholar

5. Linnhoff, B, Flower, JR. Synthesis of heat exchanger networks: I. Systematic generation of energy optimal networks. AIChE J 1978;24:633–43.10.1002/aic.690240411Search in Google Scholar

6. Klemeš, JJ, Varbanov, PS, Walmsley, TG, Jia, X. New directions in the implementation of pinch methodology (PM). Renew Sustain Energy Rev 2018;98:439–68. https://doi.org/10.1016/j.rser.2018.09.030.Search in Google Scholar

7. Varbanov, PS, Walmsley, TG, Klemeš, JJ, Seferlis, P, Sabev Varbanov, P, Yong, JY, et al.. Data extraction for heat integration and total site analysis: a review. Chem Eng Trans 2019;76:67–72. https://doi.org/10.3303/CET1976012.Search in Google Scholar

8. Klemes, JJ, editor. Handbook of process integration (PI): minimisation of energy and water use, waste and emissions. Cambridge: Woodhead Publishing; 2013.Search in Google Scholar

9. Kemp, IC. Some aspects of the practical application of pinch technology methods. TransI Chem E 1991;69:10.Search in Google Scholar

10. Klemeš, JJ, Varbanov, PS. Implementation and pitfalls of process integration. Chem Eng Trans 2010;21:1369–74. https://doi.org/10.3303/CET1021229.Search in Google Scholar

11. Bergamini, R, Nguyen, T-V, Bühler, F, Elmegaard, B. Development of a simplified process integration methodology for application in medium-size industries. In: Proceedings of ECOS 2016: 29th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems; 2016.Search in Google Scholar

12. Wen, Y, Shonnard, DR. Environmental and economic assessments of heat exchanger networks for optimum minimum approach temperature. Comput Chem Eng 2003;27:1577–90. https://doi.org/10.1016/S0098-1354(03)00097-8.Search in Google Scholar

13. Papoulias, SA, Grossmann, IE. A structural optimization approach in process synthesis—II: heat recovery networks. Comput Chem Eng 1983;7:707–21. https://doi.org/10.1016/0098-1354(83)85023-6.Search in Google Scholar

14. López-Maldonado, LA, Ponce-Ortega, JM, Segovia-Hernández, JG. Multiobjective synthesis of heat exchanger networks minimizing the total annual cost and the environmental impact. Appl Therm Eng 2011;31:1099–113. https://doi.org/10.1016/j.applthermaleng.2010.12.005.Search in Google Scholar

15. Vaskan, P, Guillén-Gosálbez, G, Jiménez, L. Multi-objective design of heat-exchanger networks considering several life cycle impacts using a rigorous MILP-based dimensionality reduction technique. Appl Energy 2012;98:149–61. https://doi.org/10.1016/j.apenergy.2012.03.018.Search in Google Scholar

16. Ravagnani, MASS, Mano, TB, Carvalho, EP, Silva, AP, Costa, CBB. Multi-objective heat exchanger networks synthesis considering economic and environmental optimization. Comput Aided Chem Eng 2014;33:1579–84. https://doi.org/10.1016/B978-0-444-63455-9.50098-2.Search in Google Scholar

17. Mano, TB, Jiménez, L, Ravagnani, MASS. Incorporating life cycle assessment eco-costs in the optimization of heat exchanger networks. J Clean Prod 2017;162:1502–17. https://doi.org/10.1016/j.jclepro.2017.06.154.Search in Google Scholar

18. Mano, TB, Guillén-Gosálbez, G, Jiménez, L, Ravagnani, MASS. Synthesis of heat exchanger networks with economic and environmental assessment using fuzzy-analytic hierarchy process. Chem Eng Sci 2019;195:185–200. https://doi.org/10.1016/j.ces.2018.11.044.Search in Google Scholar

19. Furman, KC, Sahinidis, NV. A critical review and annotated bibliography for heat exchanger network synthesis in the 20th century. Ind Eng Chem Res 2002;41:2335–70. https://doi.org/10.1021/ie010389e.Search in Google Scholar

20. Linnhoff, B. Process integration Gothenburg-20 years later. Historical overview of early development. Gothenburg, Sweden: International Process Integration Jubilee Conference, Chalmers University; 2013.Search in Google Scholar

21. Linnhoff, B, Akinradewo, CG. Linking process simulation and process integration. Comput Chem Eng 1999;23:S945–53. https://doi.org/10.1016/s0098-1354(99)80229-4.Search in Google Scholar

22. Brunner, F, Krummenacher, P. Einführung in die Prozessintegration mit der Pinch-Methode, Handbuch für die Analyse von kontinuierlichen Prozessen und Batch-Prozessen. Zweite Auflage 2017:1–175.Search in Google Scholar

23. Linnhoff, B, Townsend, DW, Boland, D, Hewitt, GF, Thomas, BEA, Guy, AR, et al.. A user guide on process integration for the efficient use of energy. London: The Institue of Chemical Engineers; 1982.Search in Google Scholar

24. Linnhoff, B, Hindmarsh, E. The pinch design method for the heat exchanger networks. Chem Eng Sci 1983;38:745–63.10.1016/0009-2509(83)80185-7Search in Google Scholar

25. Shenoy, U. Heat exchanger network synthesis-process optimization by energy and resource analysis. Houston, USA: Gulf Publishing Company; 1995.Search in Google Scholar

26. Kemmler, A, Spillmann, T. Analyse des schweizerischen Energieverbrauchs 2000-2019 nach Verwendungszwecken. Bern, Switzerland: Bundesamt für Energie; 2020.Search in Google Scholar

27. Guthörl, D. Life cycle assessment of energy efficiency measures in industrial processes: the role of embedded energy. Dublin: Dublin Institute of Technology; 2016.Search in Google Scholar

28. Alfa Laval. Brazed plate heat exchangers. Products; 2015. Available from: https://www.alfalaval.com/products/heat-transfer/plate-heat-exchangers/brazed-plate-heat-exchangers/.Search in Google Scholar

29. Alfa Laval. Environmental product declaration: brazed plate heat exchanger. Lund: Alfa Laval; 2016:2 p.Search in Google Scholar

30. SWEP International AB. Environmental product declaration: brazed plate heat exchangers. Landskrona, Sweden: SWEP International AB; 2017:1–6 pp.Search in Google Scholar

31. SWEP International AB. Process industry. Products; 2019. Available from: https://www.swep.kr/.Search in Google Scholar

32. Frischknecht, R. LCI modelling approaches applied on recycling of materials in view of environmental sustainability, risk perception and eco-efficiency. Int J Life Cycle Assess 2010;15:666–71. https://doi.org/10.1007/s11367-010-0201-6.Search in Google Scholar

33. Wernet, G, Bauer, C, Steubing, B, Reinhard, J, Moreno-Ruiz, E, Weidema, B. The ecoinvent database version 3 (part I): overview and methodology. Int J Life Cycle Assess 2016:1218–1230.10.1007/s11367-016-1087-8Search in Google Scholar

34. Althaus, H-J, Bauer, C, Doka, G, Dones, R, Frischknecht, R, Hellweg, S, et al.. Implementation of life cycle impact assessment methods. St. Gallen, Switzerland: Swiss Centre for Life Cycle Inventories; 2010.Search in Google Scholar

35. Linnhoff, B, Ahmad, S. Supertargeting: optimum synthesis of energy management systems. J Energy Resour Technol 1989;111:121. https://doi.org/10.1115/1.3231413.Search in Google Scholar

36. Chemstations. Chemstations | offering CHEMCAD chemical process simulation software; 2020. Available from: https://www.chemstations.com/.Search in Google Scholar

37. Olsen, D. Pinch software development; 2013.Search in Google Scholar

38. FEFCO. Corrugated board production. European Database for Corrugated Board Life Cycle Studies; 2019. Available from: https://www.fefco.org/lca.Search in Google Scholar

39. PlasticsEurope. Polyolefins. About plastics; 2020. Available from: https://www.plasticseurope.org/en/about-plastics/what-are-plastics/large-family/polyolefins#:∼:text=Polyolefins are a family of,popular plastics in use today.Search in Google Scholar
Received: 2021-01-15
Accepted: 2021-04-07
Published Online: 2021-04-29

© 2021 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. CPPM special issue in honour of Emeritus Professor W.Y. “Bill” Svrcek
  4. Research Articles
  5. Asphaltene precipitation from heavy oil mixed with binary and ternary solvent blends
  6. Kinetic modeling of biosurfactant production by Bacillus subtilis N3-1P using brewery waste
  7. A user workflow for combining process simulation and pinch analysis considering ecological factors
  8. An improved Wilson equation for phase equilibrium K values estimation
  9. Process model correlating Athabasca bitumen thermally cracked at edge of coking induction zone
  10. Flexible digital twins from commercial off-the-shelf software solutions: a driver for energy efficiency and decarbonisation in process industries?
https://doi.org/10.1515/cppm-2021-0004
Keywords for this article
heat exchanger network; life cycle analysis; process integration; process optimization; process simulation

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. CPPM special issue in honour of Emeritus Professor W.Y. “Bill” Svrcek
  4. Research Articles
  5. Asphaltene precipitation from heavy oil mixed with binary and ternary solvent blends
  6. Kinetic modeling of biosurfactant production by Bacillus subtilis N3-1P using brewery waste
  7. A user workflow for combining process simulation and pinch analysis considering ecological factors
  8. An improved Wilson equation for phase equilibrium K values estimation
  9. Process model correlating Athabasca bitumen thermally cracked at edge of coking induction zone
  10. Flexible digital twins from commercial off-the-shelf software solutions: a driver for energy efficiency and decarbonisation in process industries?
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