Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter January 12, 2016

Modeling and Simulation Environments for Sustainable Low-Carbon Energy Production – A Review

  • Aldric Tumilar , Manish Sharma , Dia Milani and Ali Abbas EMAIL logo


This paper reviews research trends in modeling for low-carbon energy production. The focus is on two currently significant low-carbon energy processes; namely, bioenergy and post-combustion carbon capture (PCC) processes. The fundamentals of these two processes are discussed and the role of modeling and simulation tools (MSTs) is highlighted. The most popular modeling software packages are identified and their use in the literature is analyzed. Among commercially available packages, it is found that no single software package can handle all process development needs such as, configuration studies, techno-economic analysis, exergy optimization, and process integration. This review also suggests that optimal modeling results reported in literature can be viewed as optimal at the individual plant level, but sub-optimal for plant superstructure level. This review has identified key gaps pertinent to developing hybrid models that describe integrated energy production processes. ASPEN Plus is found to be dominant for modeling both bioenergy and PCC processes for both steady-state and dynamic modes respectively.


The authors wish to acknowledge financial assistance provided through Australian National Low Emissions Coal Research and Development (ANLEC R&D). ANLEC R&D is supported by Australian Coal Association Low Emissions Technology Limited and the Australian Government through the Clean Energy Initiative.


1. Lipkowski A, Kijenski J, Walisiewicz-Niedbalska W, Rozycki K, Pawlak I. New biofuel component and method of obtaining new biofuel components. Application: WO, 09 2007.Search in Google Scholar

2. Hettenhaus J. Achieving sustainable production of agricultural biomass for biorefinery feedstock. Ind Biotechnol 2006;2:257–75.10.1089/ind.2006.2.257Search in Google Scholar

3. Anthrop D. Analysis highlights limits on energy promise of biofuels. Oil Gas J 2007;105:25–9.Search in Google Scholar

4. AspenHysys. Aspen Technology, Inc. AspenTeck, Massachusetts, USA, 2008, in Google Scholar

5. Fassler P. Too good to be used as fuel? Sulzer Technical Review 2006;88:14–16.Search in Google Scholar

6. AspenTech. Aspen Technology, Inc. AspenTeck, MA, USA, 1981 in Google Scholar

7. Demirbas A. Current technologies for the thermo-conversion of biomass into fuels and chemicals. Energy Sources 2004;26:715–30.10.1080/00908310490445562Search in Google Scholar

8. PSE, UK. gproms, PSE, UK 2013, in Google Scholar

9. Himmelblau D, Beck R. Combined chemicals and energy production from biomass pyrolysis. Prog Thermochem Biomass Convers 2000;2:1197–206.10.1002/9780470694954.ch97Search in Google Scholar

10. Pons M. Introduction to cape-open 2005.Search in Google Scholar

11. GI Virtual Materials.Vmgsim process simulator, version 6.52011.Search in Google Scholar

12. AspenTech. Aspen One v7.3, AspenTech, USA 2013, in Google Scholar

13. Peters M, Timmerhaus K, West R. Plant design and economics for chemical engineers, 5th ed. New York: Mcgraw-Hill, Inc, 2003.Search in Google Scholar

14. Hirsch R, Bezdek R, Wendling R. Peaking of world oil production and its mitigation. AIChE J 2006;52:2–8.10.1016/B978-012369495-9/50003-8Search in Google Scholar

15. Cameron I, Hangos K. Process modelling and model analysis, vol 4. San Diego, USA: Academic Press, 2001.Search in Google Scholar

16. Gani R, Cameron A, Lucia Iand, Sin G, Georgiadis M. Process systems engineering, 2. modeling and simulation. Ullmann’s Encyclopedia of Industrial Chemistry 2000.Search in Google Scholar

17. Marchetti M, Rao A, Vickery D, et al. Mixed mode simulation-adding equation oriented convergence to a sequential modular simulation tool. Comput Aided Chem Eng 2001;9:231–6.10.1016/S1570-7946(01)80034-1Search in Google Scholar

18. Ng K. Design and development of solids processes a process systems engineering perspective. Powder Technol 2002;126:205–10.10.1016/S0032-5910(02)00091-8Search in Google Scholar

19. Perry R, Green D, Maloney J, Abbott M, Ambler C, Amero R. Perry’s chemical engineers’ handbook, vol 7. New York: McGraw-Hill, 1997.Search in Google Scholar

20. Leis J, Kramer M. Sensitivity analysis of systems of differential and algebraic equations. Comput Chem Eng 1985;9:93–6.10.1016/0098-1354(85)87008-3Search in Google Scholar

21. Schwier D, Püttmann A, Hartge E, Gruhn G, Werther J. Sensitivity analysis in the simulation of complex solids processes. Comput Aided Chem Eng 2006;21:601–6.10.1016/S1570-7946(06)80111-2Search in Google Scholar

22. Kofke D. Gibbs-Duhem integration: a new method for direct evaluation of phase coexistence by molecular simulation. Mol Phys 1993;78:1331–6.10.1080/00268979300100881Search in Google Scholar

23. Panagiotopoulos A. Direct determination of phase coexistence properties of fluids by Monte Carlo simulation in a new ensemble. Mol Phys 1987;61:813–26.10.1080/00268978700101491Search in Google Scholar

24. Panagiotopoulos A, Quirke N, Stapleton M, Tildesley D. Phase equilibria by simulation in the Gibbs ensemble: alternative derivation, generalization and application to mixture and membrane equilibria. Mol Phys 1988;63:527–45.10.1080/00268978800100361Search in Google Scholar

25. Ge J, Wu G, Todd B, Sadus R. Equilibrium and nonequilibrium molecular dynamics methods for determining solid–liquid phase coexistence at equilibrium. J Chem Phys 2003;119:11017–23.10.1063/1.1623476Search in Google Scholar

26. Lsal M, Vacek V. Direct evaluation of solid–liquid equilibria by molecular dynamics using Gibbs-Duhem integration. Mol Simul 1997;19:43–61.10.1080/08927029708024137Search in Google Scholar

27. Chen B, Siepmann J, Klein M. Direct Gibbs ensemble Monte Carlo simulations for solid-vapor phase equilibria: applications to Lennard-Jonesium and carbon dioxide. J Phys Chem B 2001;105:9840–8.10.1021/jp011950pSearch in Google Scholar

28. Valleau J. A thermodynamic-scaling study of Gibbs-ensemble Monte Carlo. Mol Simul 2003;29:627–42.10.1080/0892702031000103167Search in Google Scholar

29. Kuresawa I. Solid-Liquid Equilibrium in multi solute systems. PhD diss., Georgia Institute of Technology, 2004.Search in Google Scholar

30. Maity S, Gayen K, De S, Ganguly S. Modeling and simulation of solid-liquid equilibrium: Model validation using solubility data and sensitivity study for polyethylene system. In 1st National Conference of Research Scholar and Young Scientists, Indian Institute of Technology, Kharagpur, India, 2004.Search in Google Scholar

31. Aden A, Ruth M, Ibsen K, Jechura J, Neeves K, Sheehan J, et al. Lignocellulosic biomass to ethanol process design and economics utilizing co-current dilute acid prehydrolysis and enzymatic hydrolysis for corn Stover. 2002.10.2172/15001119Search in Google Scholar

32. Wooley R, Putsche V. Development of an ASPEN PLUS physical property database for biofuels components. Citeseer, 1996. Report No. NREL/MP-425-20685.10.2172/257362Search in Google Scholar

33. Magnusson H. Process simulation in Aspen Plus of an integrated ethanol and CHP plant, Ph.D. thesis, Master Thesis in Energy Engineering, 2006.Search in Google Scholar

34. Shapouri H, Gallagher P, Nefstead W, Schwartz R, Noe S, Conway R. 2008 energy balance for the corn-ethanol industry, Technical report, United States Department of Agriculture, Office of Chief Economist, Office of Energy Policy and New Uses, 2008.Search in Google Scholar

35. Reid R, Sherwood T. The properties of gases and liquids: their estimation and correlation. New York: McGraw-Hill, 1966.Search in Google Scholar

36. Raman R. Chemical process computations. New York, USA: Kluwer Academic Pub, 1985.Search in Google Scholar

37. Kenig E, Grak A. Reactive absorption, in integrated chemical processes: synthesis, operation, analysis, and control. Weinheim, FRG: Wiley-VCH Verlag GmbH Co. KGaA, 2005, doi: 10.1002/3527605738.ch9.Search in Google Scholar

38. Luo X, Knudsen J, De Montigny D, Sanpasertparnich T, Idem R, Gelowitz D, et al. Comparison and validation of simulation codes against sixteen sets of data from four different pilot plants. Energy Procedia 2009;1:1249–56.10.1016/j.egypro.2009.01.164Search in Google Scholar

39. Bollas G, Chen C, Barton P. Refined electrolyte-NRTL model: activity coefficient expressions for application to multi-electrolyte systems. AIChE J 2008;54:1608–24.10.1002/aic.11485Search in Google Scholar

40. Chapman W, Gubbins K, Jackson G, Radosz M. Saft: equation-of-state solution model for associating fluids. Fluid Phase Equilib 1989;52:31–8.10.1016/0378-3812(89)80308-5Search in Google Scholar

41. Chen Y, Mutelet F, Jaubert J. Modeling the solubility of carbon dioxide in imidazolium-based ionic liquids with the PC-SAFT equation of state. J Phys Chem B 2012;116:14375–88.10.1021/jp309944tSearch in Google Scholar

42. Rodriguez J, Mac Dowell N, Llovell F, Adjiman C, Jackson G, Galindo A. Modelling the fluid phase behaviour of aqueous mixtures of multifunctional alkanolamines and carbon dioxide using transferable parameters with the SAFT-VR approach. Mol Phys 2012;110:1325–48.10.1080/00268976.2012.665504Search in Google Scholar

43. Mac Dowell N, Samsatli N, Shah N. Dynamic modelling and analysis of an amine-based post-combustion CO2 capture absorption column. Int J Greenhouse Gas Control 2013;12:247–58.10.1016/j.ijggc.2012.10.013Search in Google Scholar

44. Pahlavanzadeh H, Baygi S. Modeling CO2 solubility in aqueous methyldiethanolamine solutions by perturbed chain-SAFT equation of state. J Chem Thermodyn 2013;59:214–21.10.1016/j.jct.2012.12.021Search in Google Scholar

45. Delrue F, Setier P, Sahut C, Cournac L, Roubaud A, Peltier G, et al. An economic, sustainability, and energetic model of biodiesel production from microalgae. Bioresour Technol 2012;111:191–200.10.1016/j.biortech.2012.02.020Search in Google Scholar

46. Demirbas A. Progress and recent trends in biofuels. Prog Energy Combust Sci 2007;33:1–18.10.1016/j.pecs.2006.06.001Search in Google Scholar

47. Lal R. Crop residues as soil amendments and feedstock for bioethanol production. Waste Manage 2008;28:747–58.10.1016/j.wasman.2007.09.023Search in Google Scholar

48. Alcantara R, Amores J, Canoira L, Fidalgo E, Franco M, Navarro A. Catalytic production of biodiesel from soy-bean oil, used frying oil and tallow. Biomass Bioenergy 2000;18:515–27.10.1016/S0961-9534(00)00014-3Search in Google Scholar

49. Demirbas A. Production of biodiesel from algae oils. Energy Sources, Part A 2008;31:163–8.10.1080/15567030701521775Search in Google Scholar

50. Collard F-X, Blin J. A review on pyrolysis of biomass constituents: mechanisms and composition of the products obtained from the conversion of cellulose, hemicelluloses and lignin. Renewable Sustainable Energy Rev 2014;38:594–608.10.1016/j.rser.2014.06.013Search in Google Scholar

51. Murugan S, Gu S. Research and development activities in pyrolysis–contributions from Indian scientific community–a review. Renewable Sustainable Energy Rev 2015;46:282–95.10.1016/j.rser.2015.02.050Search in Google Scholar

52. Goldstein I, et al. Organic chemicals from biomass, 2000.Search in Google Scholar

53. Motasemi F, Afzal MT. A review on the microwave-assisted pyrolysis technique. Renewable Sustainable Energy Rev 2013;28:317–30.10.1016/j.rser.2013.08.008Search in Google Scholar

54. Patra TK, Sheth PN. Biomass gasification models for downdraft Gasifier: a state-of-the-art review. Renewable Sustainable Energy Rev 2015;50:583–93.10.1016/j.rser.2015.05.012Search in Google Scholar

55. Dannemand Andersen P, Christensen J, Kossmann J, Koukios E. Emerging and future bioenergy technologies, 2003.Search in Google Scholar

56. Mann M, Spath P. Technoeconomic analysis and life cycle assessment of an integrated biomass gasification combined cycle system. In: A.V. Bridgewater, D.G.B. Boocock, editor. Developments in thermochemical biomass conversion. Netherlands: Springer, 1997:1567–81.Search in Google Scholar

57. Chatterjee C, Pong F, Sen A. Chemical conversion pathways for carbohydrates. Green Chem 2015;17:40–71.10.1039/C4GC01062KSearch in Google Scholar

58. Aresta M, Dibenedetto A, Carone M, Colonna T, Fragale C. Production of biodiesel from macroalgae by supercritical CO2 extraction and thermochemical liquefaction. Environ Chem Lett 2005;3:136–9.10.1007/s10311-005-0020-3Search in Google Scholar

59. Demirbas A. Biomass resources for energy and chemical industry. Energy Edu Sci Technol 2000;5:21–45.Search in Google Scholar

60. Christy PM, Gopinath L, Divya D. A review on anaerobic decomposition and enhancement of biogas production through enzymes and microorganisms. Renewable Sustainable Energy Rev 2014;34:167–73.10.1016/j.rser.2014.03.010Search in Google Scholar

61. Boyles D. Bio-energy: technology, thermodynamics, and costs, vol. 1. Southampton, England: Ellis Horwood, 1984.Search in Google Scholar

62. Hall C. Biomass as an alternative fuel, 1981.Search in Google Scholar

63. Dale M, Moelhman M. Enzymatic simultaneous saccharification and fermentation (SSF) of biomass to ethanol in a pilot 130 liter multistage continuous reactor separator. W. Lafayette, IN: Bio-Process Innovation, Inc., 2005.Search in Google Scholar

64. Schell D, Walter E. Simultaneous saccharification and fermentation of corn stover hydrolysate to ethanol. Biotech Symp Fuels Chem 1991;72.Search in Google Scholar

65. Spindler P, Wyman CE. Key parameters in simultaneous saccharification and fermentation of biomass to ethanol. Biotech Symp Fuels Chem 1991;74.Search in Google Scholar

66. Alabdulkarem A, Mortazavi A, Hwang Y, Radermacher R, Rogers P. Optimization of propane pre-cooled mixed refrigerant LNG plant. Appl Therm Eng 2011;31:1091–8.10.1016/j.applthermaleng.2010.12.003Search in Google Scholar

67. Chen J, Adomaitis R. An object-oriented framework for modular chemical process simulation with semiconductor processing applications. Comput Chem Eng 2006;30:1354–80.10.1016/j.compchemeng.2006.03.002Search in Google Scholar

68. Quintero J, Cardona C. Process simulation of fuel ethanol production from lignocellulosics using aspen plus. Ind Eng Chem Res 2011;50:6205–12.10.1021/ie101767xSearch in Google Scholar

69. Robinson P, Luyben W. Simple dynamic Gasifier model that runs in aspen dynamics. Ind Eng Chem Res 2008;47:7784–92.10.1021/ie800227nSearch in Google Scholar

70. Sanders S. High-accuracy predictive modelling of biotreatment systems. gPROMS Technology Brief 2005.Search in Google Scholar

71. Bharadwaj A, Diwekar U, Robinson A, Arunachalam V, Bannerjee R. Renewables: The energy for the 21st century world, in World Resnewable Energy Congress VI, 2000.Search in Google Scholar

72. Omosun A, Bauen A, Brandon N, Adjiman C, Hart D. Modelling system efficiencies and costs of two biomass-fuelled SOFC systems. J Power Sources 2004;131:96–106.10.1016/j.jpowsour.2004.01.004Search in Google Scholar

73. Zhang W, Zeng G, Chen X, Yu Z. Pretreatment technology of biomass entrained flow gasification. Chin J Process Eng 2007;7:747.Search in Google Scholar

74. Zhang J. Simulation on recovery of refinery dry gas by means of shallow-cool oil-absorption technology. Shiyou Huagong 2014;43:1069–75.Search in Google Scholar

75. She Y, Emerson S, Vanderspurt T. Modeling and simulation of hydrogen production from biomass through hydrolysis and liquid-phase reforming processes, in ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, volume 231, AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA, volume 231, 2006.Search in Google Scholar

76. Mussati M, Aguirre P, Fuentes M, Scenna N. Aspects on methanogenic biofilm reactor modeling. Lat Am Appl Res 2006;36:173–80.Search in Google Scholar

77. Arifin S, Chien I, et al. Combined pre-concentrator/recovery column design for ethanol dehydration process, in The 2007 Spring National Meeting, 2007.10.1021/ie061446cSearch in Google Scholar

78. Zhijiu A, Honggang C, Guoqing Y, et al. Comparative analysis of superclaus and sub dew point process. Chem Eng Oil Gas 2010;6:010.Search in Google Scholar

79. Selvam P, Wolff D, Melo H, Pandey A, Soccol C, Josh V, et al. Process, cost modeling and simulations for integrated project development of biomass for fuel and protein. J Sci Ind Res 1998;57:567–74.Search in Google Scholar

80. Galbe M, Zacchi G. Simulation of ethanol production processes based on enzymatic hydrolysis of woody biomass. Comput Chem Eng 1994;18:S687–S691.10.1016/0098-1354(94)80112-6Search in Google Scholar

81. Wang J. A systematic modeling approach for cellular systems and its application to transport and catabolism of four carbohydrates in Escherichia Coli K-12. Stuttgart, Germany: VDI-Verlag, 2002.Search in Google Scholar

82. Alzate C, Toro O. Energy consumption analysis of integrated flowsheets for production of fuel ethanol from lignocellulosic biomass. Energy 2006;31:2447–59.10.1016/ in Google Scholar

83. Wu M, Wu Y, Wang M. Energy and emission benefits of alternative transportation liquid fuels derived from switchgrass: a fuel life cycle assessment. Biotechnol Prog 2006;22:1012–24.10.1021/bp050371pSearch in Google Scholar PubMed

84. Olivier JG, Janssens-Maenhout G, Peters JA. Trends in global CO2 emissions: 2012 Report, PBL Netherlands Environmental Assessment Agency Hague, 2012.Search in Google Scholar

85. Damm D, Fedorov A. Conceptual study of distributed CO2 capture and the sustainable carbon economy. Energy Convers Manage 2008;49:1674–83.10.1016/j.enconman.2007.11.011Search in Google Scholar

86. IEA. World energy outlook 2009 edition. Climate Change Excerpt, 2009.Search in Google Scholar

87. Kaldi J. Overview of climate change, GHG emissions and the CSS value change, in Introduction to Geological Storage of CO2 Workshop, 34th International Geological Congress, Brisbane, Australia, 2012.Search in Google Scholar

88. C. A. C. Technology. Assessing post-combustion capture for coal fired power stations in app countries, Technical report, CSIRO, final report to the Department of Resources, Energy and Tourism, EP116217, 2012.Search in Google Scholar

89. Sreenivasulu B, Gayatri D, Sreedhar I, Raghavan K. A journey into the process and engineering aspects of carbon capture technologies. Renewable Sustainable Energy Rev 2015;41:1324–50.10.1016/j.rser.2014.09.029Search in Google Scholar

90. Wibberley L, Palfreyman D, Scaife P and C. R. C. for Coal in Sustainable Development (Australia). Retro-fitting post combustion capture. Qld: QCAT Technology Transfer Centre Pullenvale, 2008.Search in Google Scholar

91. Cousins A, Wardhaugh L, Feron P. A survey of process flow sheet modifications for energy efficient CO2 capture from flue gases using chemical absorption. Int J Greenhouse Gas Control 2011;5:605–19.10.1016/j.ijggc.2011.01.002Search in Google Scholar

92. Khalilpour R, Abbas A. Hen optimization for efficient retrofitting of coal-fired power plants with post-combustion carbon capture. Int J Greenhouse Gas Control 2011;5:189–99.10.1016/j.ijggc.2010.10.006Search in Google Scholar

93. Le Moullec Y, Kanniche M. Screening of flowsheet modifications for an efficient monoethanolamine (MEA) based post-combustion CO2 capture. Int J Greenhouse Gas Control 2011;5:727–40.10.1016/j.ijggc.2011.03.004Search in Google Scholar

94. Mokhtar M, Ali M, Khalilpour R, Abbas A, Shah N, Al Hajaj A, et al. Solar-assisted post-combustion carbon capture feasibility study. Appl Energy 2012;92:668–76.10.1016/j.apenergy.2011.07.032Search in Google Scholar

95. Chikukwa A, Enaasen N, Kvamsdal H, Hillestad M. Dynamic modeling of post-combustion CO2 capture using amines–a review. Energy Procedia 2012;23:82–91.10.1016/j.egypro.2012.06.063Search in Google Scholar

96. Giglmayr I, Pogoreutz M, Nixdorf M. Comparison of software for thermodynamic process calculation. Results of the VGB research project No. 177. VGB PowerTech 2001;81:44–51.Search in Google Scholar

97. Alie C, Douglas P, Croiset E. Simulation and optimization of a coal-fired power plant with integrated CO2 capture using mea scrubbing, in GHGT-8 Conference, 2006.Search in Google Scholar

98. Romeo L, Bolea I, Escosa J. Integration of power plant and amine scrubbing to reduce CO2 capture costs. Appl Therm Eng 2008;28:1039–46.10.1016/j.applthermaleng.2007.06.036Search in Google Scholar

99. Ahn H, Luberti M, Liu Z, Brandani S. Process simulation of aqueous MEA plants for post-combustion capture from coal-fired power plants. Energy Procedia 2013;37:1523–31.10.1016/j.egypro.2013.06.028Search in Google Scholar

100. Lawal A, Wang M, Stephenson P, Obi O. Demonstrating full-scale post-combustion CO2 capture for coal-fired power plants through dynamic modelling and simulation. Fuel 2012;101:115–28.10.1016/j.fuel.2010.10.056Search in Google Scholar

101. Cifre P, Brechtel K, Hoch S, Garca H, Asprion N, Hasse H, et al. Integration of a chemical process model in a power plant modelling tool for the simulation of an amine based CO2 scrubber. Fuel 2009;88:2481–8.10.1016/j.fuel.2009.01.031Search in Google Scholar

102. Kohl A, Nielsen R. Gas purification. Texas, USA: Gulf Professional Publishing, 1997.Search in Google Scholar

103. Kvamsdal H, Jakobsen J, Hoff K. Dynamic modeling and simulation of a CO2 absorber column for post-combustion CO2 capture. Chem Eng Process Process Intensifi 2009;48:135–44.10.1016/j.cep.2008.03.002Search in Google Scholar

104. Karimi M. Simulator comparison, joint seminar on CO2 absorption fundamentals, 2009.Search in Google Scholar

105. Karimi M, Hillestad M, Svendsen H. Capital costs and energy considerations of different alternative stripper configurations for post combustion CO2 capture. Chem Eng Res Design 2011;89:1229–36.10.1016/j.cherd.2011.03.005Search in Google Scholar

106. Ahmadi F. Assessing the Performance of Aspen Plus and Promax for the Simulation of CO2 Capture Plants, Ph.D. thesis, Faculty of Graduate Studies and Research, University of Regina, 2012.Search in Google Scholar

107. ErikØi L. Comparison of ASPEN HYSYS and Aspen Plus simulation of CO2 absorption into mea from atmospheric gas. Energy Procedia 2012;23:360–9.10.1016/j.egypro.2012.06.036Search in Google Scholar

108. Tobiesen F, Hillestad M, Kvamsdal H, Chikukwa A. A general column model in CO2SIM for transient modelling of CO2 absorption processes. Energy Procedia 2012;23:129–39.10.1016/j.egypro.2012.06.071Search in Google Scholar

109. Parvareh F, Sharma M, Qadir A, Milani D, Khalilpour R, Chiesa M, et al. Integration of solar energy in coal-fired power plants retrofitted with carbon capture: a review. Renewable Sustainable Energy Rev 2014;38:1029–44.10.1016/j.rser.2014.07.032Search in Google Scholar

110. Milani D. Modelling Framework of Solar Assisted Dehumidification System to Generate Freshwater from “Thin Air”, Ph.D. thesis, The University of Sydney, 2012.Search in Google Scholar

111. Parvareh F, Milani D, Sharma M, Chiesa M, Abbas A. Solar repowering of pcc-retrofitted power plants; solar thermal plant dynamic modelling and control strategies. Sol Energy 2015;119:507–30.10.1016/j.solener.2015.06.034Search in Google Scholar

112. Stoddard M, Faas S, Chiang C, Dirks J. Solergy; a computer code for calculating the annual energy from central receiver power plants, Technical report, Sandia National Labs., Livermore, CA (USA); Sandia National Labs., Albuquerque, NM (USA); Pacific Northwest Lab., Richland, WA (USA), 1987.10.2172/6500458Search in Google Scholar

113. Chen C, Tremblay D, Bhat C. A rate-based process modeling study of CO2 capture with aqueous amine solutions using aspenONE process engineering, in Clearwater Coal Conference, Clearwater Florida, 2008.Search in Google Scholar

114. Honeywell. Unisim design suite, Honeywell website, 2013, in Google Scholar

115. Bryan Research Engineering Inc. Promax, Bryan Research Engineering, Inc, USA, 2013. in Google Scholar

116. Hasse H, Bessling B, Böttcher R. OPEN Chemasim™: breaking paradigms in process simulation. Comput Aided Chem Eng 2006;21:255–60.10.1016/S1570-7946(06)80055-6Search in Google Scholar

117. Kvamsdal H, Chikukwa A, Hillestad M, Zakeri A, Einbu A. A comparison of different parameter correlation models and the validation of an MEA-based absorber model. Energy Procedia 2011;4:1526–33.10.1016/j.egypro.2011.02.021Search in Google Scholar

118. Optimized Gas Treating Inc USA. Protreat, Optimized Gas Treating Inc, USA, 2013 in Google Scholar

119. MathWorks. Matlab, Mathematical Computing Software for Engineers and Scientists. MA, 2008. in Google Scholar

120. Dickey B. Test results from a concentrated solar microturbine Brayton cycle integration, in ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition, American Society of Mechanical Engineers, 2011:1031–6.10.1115/GT2011-45918Search in Google Scholar

121. Prölß K, Tummescheit H, Velut S, Åkesson J. Dynamic model of a post-combustion absorption unit for use in a non-linear model predictive control scheme. Energy Procedia 2011;4:2620–7.10.1016/j.egypro.2011.02.161Search in Google Scholar

122. Endat O. Endat thermal power plant simulations, Endat Oy, Finland, 2013. in Google Scholar

123. Popov D. An option for solar thermal repowering of fossil fuel fired power plants. Sol Energy 2011;85:344–9.10.1016/j.solener.2010.11.017Search in Google Scholar

124. Barigozzi G, Bonetti G, Franchini G, Perdichizzi A, Ravelli S. Thermal performance prediction of a solar hybrid gas turbine. Sol Energy 2012;86:2116–27.10.1016/j.solener.2012.04.014Search in Google Scholar

125. Camporeale S, Fortunato B, Saponaro A Repowering of a Rankine cycle power plant by means of concentrating solar collectors, in ASME 2011 Turbo Expo: Turbine Technical Conference and Exposition, American Society of Mechanical Engineers, 2011:163–70.10.1115/GT2011-45736Search in Google Scholar

126. Kelly B, Hermann U, Hale M. Optimization studies for integrated solar combined cycle systems. Sol Eng: the Power to Choose, ASME Forum, Wahington DC, 2001;393–8.10.1115/SED2001-150Search in Google Scholar

127. Rheinländer J, Perz E, Goebel O. Performance simulation of integrated water and power systems-software tools IPSEpro and RESYSpro for technical, economic and ecological analysis. Desalination 2003;157:57–64.10.1016/S0011-9164(03)00383-7Search in Google Scholar

128. Bolland O, Undrum H. A novel methodology for comparing CO2 capture options for natural gas-fired combined cycle plants. Adv Environ Res 2003;7:901–11.10.1016/S1093-0191(02)00085-0Search in Google Scholar

129. GE, Gate cycle, GE Power & Water, 2013, in Google Scholar

130. ASIMPTOTE. Cycle-tempo, ASIMPTOTE, 2011. in Google Scholar

131. Derbal-Mokrane H, Bouaichaoui S, El Gharbi N, Belhamel M, Benzaoui A. Modeling and numerical simulation of an integrated solar combined cycle system in Algeria. Procedia Eng 2012;33:199–208.10.1016/j.proeng.2012.01.1194Search in Google Scholar

132. Bockamp S, Griestop T, Fruth M, Ewert M, Lerchenmüller H, Mertins M, et al. Solar thermal power generation, in Power-Gen Europe, 2003.Search in Google Scholar

133. Rezaei S, Witzig A, Pfeiffer M, Lacoste B, Wolf A. Modeling and analyzing solar cooling systems in Polysun, in Proc. 3rd International Conference for Solar Air-Conditioning, OTTI, Palermo, Italy, 2009.Search in Google Scholar

134. Duffie J, Beckman W. Solar engineering of thermal process. New York, USA: John Wiley& Sons Inc., 1991.Search in Google Scholar

135. Alpert D, Kolb G. Performance of the solar one power plant as simulated by the solergy computer code, Technical report, Sandia National Labs. Albuquerque, NM (USA), 1988.10.2172/7102875Search in Google Scholar

136. Beccali M, Finocchiaro P, Nocke B. Energy performance evaluation of a demo solar desiccant cooling system with heat recovery for the regeneration of the adsorption material. Renewable Energy 2012;44:40–52.10.1016/j.renene.2011.12.021Search in Google Scholar

137. Hu E, Yang Y, Nishimura A, Yilmaz F, Kouzani A. Solar thermal aided power generation. Appl Energy 2010;87:2881–5.10.1016/j.apenergy.2009.10.025Search in Google Scholar

138. Li Z, Khalilpour R, Abbas A. Efficient configuration/design of solvent-based post-combustion carbon capture. Comput Aided Chem Eng 2012;31:815–19.10.1016/B978-0-444-59507-2.50155-4Search in Google Scholar

139. Miller D, Eslick J, Lee A, Morinelly J. A modular framework for the analysis and optimization of power generation systems with CCS. Energy Procedia 2011;4:2082–9.10.1016/j.egypro.2011.02.091Search in Google Scholar

140. Harkin T, Hoadley A, Hooper B. Optimisation of power stations with carbon capture plants–the trade-off between costs and net power. J Cleaner Prod 2012;34:98–109.10.1016/j.jclepro.2011.12.032Search in Google Scholar

141. Solovyev B, Lewin D. A steady-state resiliency index for nonlinear processes: 2 applications. Ind Eng Chem Res 2004;43:6453–62.10.1021/ie030674tSearch in Google Scholar

142. Ersoz A, Olgun H, Ozdogan S. Reforming options for hydrogen production from fossil fuels for PEM fuel cells. J Power Sources 2006a;154:67–73.10.1016/j.jpowsour.2005.02.092Search in Google Scholar

143. Ersoz A, Olgun H, Ozdogan S. Simulation study of a proton exchange membrane (PEM) fuel cell system with autothermal reforming. Energy 2006b;31:1490–500.10.1016/ in Google Scholar

144. Ersoz A, Ozdogan S, Caglayan E, Olgun H. Simulation of biomass and/or coal gasification systems integrated with fuel cells. J Fuel Cell Sci Technol 2006c;3:422–7.10.1115/1.2349523Search in Google Scholar

145. Huang C, Ali T, et al. Analysis of sulfur–iodine thermochemical cycle for solar hydrogen production. Part I: decomposition of sulfuric acid. Solar Energy 2005a;78:632–46.10.1016/j.solener.2004.01.007Search in Google Scholar

146. Huang L, Jin B, Lant P, Zhou J. Simultaneous saccharification and fermentation of potato starch wastewater to lactic acid by Rhizopus oryzae and Rhizopus arrhizus. Biochem Eng J 2005b;23:265–76.10.1016/j.bej.2005.01.009Search in Google Scholar

147. Singh D, Croiset E, Douglas P, Douglas M. Techno-economic study of CO2 capture from an existing coal-fired power plant: MEA scrubbing vs. O2/CO2 recycle combustion. Energy Convers Manage 2003;44:3073–91.10.1016/S0196-8904(03)00040-2Search in Google Scholar

148. Jimenez L, Basualdo M, Gómez J, Toselli L, Rosa M. Nonlinear dynamic modeling of multicomponent batch distillation: a case study. Braz J Chem Eng 2002;19:307–17.10.1590/S0104-66322002000300006Search in Google Scholar

149. Pasanen A. Phenomenon-driven process design methodology. VTT Publications, 2001:4–8.Search in Google Scholar

150. Gosling I. Process simulation and modeling for industrial bioprocessing: tools and techniques. Ind Biotechnol 2005;1:106–9.10.1089/ind.2005.1.106Search in Google Scholar

151. Intelligen, Inc. Superpro designer, 2008. in Google Scholar

152. Iordanidis A, Kechagiopoulos P, Voutetakis S, Lemonidou A, Vasalos I. Autothermal sorption-enhanced steam reforming of bio-oil/biogas mixture and energy generation by fuel cells: concept analysis and process simulation. Int J Hydrogen Energy 2006;31:1058–65.10.1016/j.ijhydene.2005.10.003Search in Google Scholar

153. Nichols T, Barnes C, Lauerhass L, Taylor D. Selection of steady-state process simulation software to optimize treatment of radioactive and hazardous waste. 2001.10.2172/911462Search in Google Scholar

Received: 2015-7-6
Revised: 2015-12-14
Accepted: 2015-12-14
Published Online: 2016-1-12
Published in Print: 2016-6-1

©2016 by De Gruyter

Downloaded on 26.9.2023 from
Scroll to top button