Christoph Udo Gertig
Institute of Technical Thermodynamics, RWTH Aachen University, Aachen, Germany
Dominik Tillmanns
Institute of Technical Thermodynamics, RWTH Aachen University, Aachen, Germany
Johannes Schilling
Institute of Technical Thermodynamics, RWTH Aachen University, Aachen, Germany
Uwe Bau
Institute of Technical Thermodynamics, RWTH Aachen University, Aachen, Germany
Franz Lanzerath
Institute of Technical Thermodynamics, RWTH Aachen University, Aachen, Germany
Joachim Gross
Institute of Technical Thermodynamics and Thermal Process Engineering, Stuttgart University, Stuttgart, Germany
André Bardow
Institute of Technical Thermodynamics, RWTH Aachen University, Aachen, Germany
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http://dx.doi.org/10.3384/ecp17132101Published in: Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017
Linköping Electronic Conference Proceedings 57:10, p. 101-110
The performance of many chemical and energy con-version processes depends on the choice of the mole-cules used, e.g. as solvents or working fluids. To cap-ture the complex relations between the properties of the molecules used and the process conditions, the selection of suitable molecules should be directly integrated into process design. Solving the resulting challenging integrated design problem is enabled by the Continous-Molecular Targeting – Computer-Aided Molecular Design (CoMT-CAMD) approach. Here, the combinatorial complexity of the molecular decisions is avoided by relaxing molecular parameters in a physically-based thermodynamic model. So far, implementations of CoMT-CAMD were based on procedural programming languages. This impedes reusability and the investigation of process variants as well as the design of complex processes. In order to overcome these shortcomings, we implement the CoMT-CAMD approach based on object-oriented process modeling and thus enable the integrated process and molecular design with Modelica. The resulting approach is demonstrated for the design of a process and the working fluid for a geothermal Organic Rankine Cycle application.
GenOpt, optimization, integrated fluid and process design, computer-aided molecular design, PCSAFT
Claire S. Adjiman, Amparo Galindo and George Jackson. Molecules Matter: the Expanding Envelope of Process Design. Computer Aided Chemical Engineering, 34:55–64, 2014. doi: 10.1016/B978-0-444-63433-7.50007-9.
Junjiang Bao and Li Zhao. A Review of Working Fluid and Expander Selections for Organic Rankine Cycle. Renewable and Sustainable Energy Reviews, 24:325–342, 2013. doi: 10.1016/j.rser.2013.03.040.
André Bardow, Klaas Steur and Joachim Gross. Continuous-Molecular Targeting for Integrated Solvent and Process Design. Industrial & Engineering Chemistry Research, 49(6):2834–2840, 2010. doi: 10.1021/ie901281w.
Jakob Burger, Vasileios Papaioannou, Smitha Gopinath, George Jackson, Amparo Galindo and Claire S. Adjiman. A Hierarchical Mmethod to Integrated Solvent and Process Design of Physical CO2 Absorption Using the SAFT-? Mie Approach. AIChE Journal, 61(10):3249–3269, 2015. doi: 10.1002/aic.14838.
Piero Colonna, Emiliano Casati, Carsten Trapp, Tiemo Mathijssen, Jaakko Larjola, Teemu Turunen-Saaresti and Antti Uusitalo. Organic Rankine Cycle Power Systems. Journal of Engineering for Gas Turbines and Power, 137(10):100801, 2015. doi: 10.1115/1.4029884.
Samira Fazlollahi, Pierre Mandel, Gwenaelle Becker and Francois Maréchal. Methods for Multi-Objective Investment and Operating Optimization of Complex Energy Systems. Energy, 45(1):12–22, 2012. doi: 10.1016/j.energy. 2012.02.046.
Peter Fritzson. Modelica – A Language for Equation-Based Physical Modeling and High Performance Simulation. Applied Parallel Computing, 1541:149-160, 1998. ISSN: 0302-9743.
Rafiqul Gani. Chemical Product Design. Computers & Chemical Engineering, 28(12):2441–2457, 2004. doi: 10.1016/j.compchemeng.2004.08.010.
Smitha Gopinath, George Jackson, Amparo Galindo and Claire S. Adjiman. Outer approximation algorithm with physical domain reduction for computer-aided molecular
and separation process design. AIChE Journal, 62(9):3484–3504, 2016. doi: 10.1002/aic.15411.
Joachim Gross and Gabriele Sadowski. Perturbed-Chain SAFT. Industrial & Engineering Chemistry Research, 40(4):1244–1260, 2001. doi: 10.1021/ie0003887.
Joachim Gross and Gabriele Sadowski. Application of the Perturbed-Chain SAFT Equation of State to Associating Systems. Industrial & Engineering Chemistry Research, 41(22):5510–5515, 2002. doi: 10.1021/ie010954d.
Joachim Gross. An Equation-of-State Contribution for Polar Components. AIChE Journal, 51(9):2556–2568, 2005. doi: 10.1002/aic.10502.
Joachim Gross and Jadran Vrabec. An Equation-of-State Contribution for Polar Components. AIChE Journal, 52(3):1194–1204, 2006. doi: 10.1002/aic.10683.
Florian Heberle and Dieter Brüggemann. Exergy Based Fluid Selection for a Geothermal Organic Rankine Cycle for Combined Heat and Power Generation. Applied Thermal
Engineering, 30(11-12):1326–1332, 2010. doi: 10.1016/j.applthermaleng.2010.02.012.
Matthias Lampe, Marina Stavrou, Hanns M. Bücker, J. Gross and A. Bardow. Simultaneous Optimization of Working Fluid and Process for Organic Rankine Cycles Using PCSAFT. Industrial & Engineering Chemistry Research, 53(21):8821–8830, 2014. doi: 10.1021/ie5006542.
Matthias Lampe, Marina Stavrou, Johannes Schilling, Elmar Sauer, Joachim Gross and André Bardow. Computer-Aided Molecular Design in the Continuous-Molecular Targeting Framework Using Group-Contribution PC-SAFT. Computers & Chemical Engineering, 81:278–287, 2015. doi: 10.1016/j.compchemeng.2015.04.008.
Patrick Linke, Athanasios Papadopoulos and Panos Seferlis. Systematic Methods for Working Fluid Selection and the Design, Integration and Control of Organic Rankine Cycles-A Review. Energies, 8(6):4755–4801, 2015. doi: 10.3390/en8064755.
Modelica Association. Modelica - A Unified Object-Oriented Language for Systems Modeling - Language Specification Version 3.3. URL=” https://www. modelica. org/documents/ ModelicaSpec33. Pdf ”, 2012.
Athanasios I. Papadopoulos and Patrick Linke. Integrated Solvent and Process Selection for Separation and Reactive Separation Systems. Chemical Engineering and Processing:
Process Intensification, 48(5):1047–1060, 2009. doi: 10.1016/j.cep.2009.02.004.
Frances E. Pereira, Emmanuel Keskes, Amparo Galindo, George Jackson and Claire S. Adjiman. Integrated Design of CO2 Capture Processes from Natural Gas. In: Efstratios Pistikopoulos, Michael Georgiadis and Eustathios S. Kikkinides. Editors. Process Systems Engineering: Energy Systems Engineering. Weinheim: Wiley-VCH Verlag GmbH & Co. KG, pp. 231-248, 2008.
Frances E. Pereira, Emmanuel Keskes, Amparo Galindo, George Jackson and Claire S. Adjiman. Integrated Solvent and Process Design Using a SAFT-VR Thermodynamic Description. Computers & Chemical Engineering, 35(3):474–491, 2011. doi: 10.1016/j.compchemeng.2010.06.016.
Richard E. Rosenthal. GAMS – a User’s Guide, GAMS Release 24.6.1. URL: http://www.gams.com/help/topic/gams.doc/userguides/GAMSUsersGuide.pdf. 2016.
Dennis Roskosch and Burak Atakan. Reverse Engineering of Fluid Selection for Thermodynamic Cycles with Cubic Equations of State, Using a Compression Heat Pump as Example. Energy, 81:202–212, 2015. doi: 10.1016/j.energy.2014.12.025.
Nikolaos V. Sahinidis, Mohit Tawarmalani and Minrui Yu. Design of Alternative Refrigerants via Global Optimization. AIChE Journal, 49(7):1761–1775, 2003. doi: 10.1002/aic.690490714.
Elmar Sauer, Marina Stavrou and Joachim Gross. Comparison between a Homo- and a Heterosegmented Group Contribution Approach Based on the Perturbed-Chain Polar Statistical Associating Fluid Theory Equation of State. Industrial & Engineering Chemistry Research, 53(38):14854–14864, 2014. doi: 10.1021/ie502203w.
Marina Stavrou, Matthias Lampe, André Bardow and Joachim Gross. Continuous Molecular Targeting–Computer-Aided Molecular Design (CoMT–CAMD) for Simultaneous Process and Solvent Design for CO2 Capture. Industrial & Engineering Chemistry Research, 53(46):18029–18041, 2014. doi: 10.1021/ie502924h.
Heiko Struebing. Identifying Optimal Solvents for Reactions Using Quantum Mechanics and Computer-Aided Molecular Design. Ph.D. thesis, Imperial CollegeLondon, London, 2011.
Heiko Struebing, Amparo Galindo and Claire S. Adjiman. Optimal Solvent Design for Reactions Using Computer-Aided Molecular Design. URL: http://www.minlp.org/library/problem/mod/index.php?lib=MINLP&i=180&pi=-137. 2011.
Michael Wetter. Design Optimization with GenOpt. Building Energy Simulation, (21):19–28, 2000.
Michael Wetter. Modelica-Based Modelling and Simulation to Support Research and Development in Building Energy and Control Systems. Journal of Building Performance Simulation, 2(2):143–161, 2009. doi: 10.1080/19401490902818259.
Michael Wetter. GenOpt – Generic Optimization Program – User Manual – Version 3.1.1. URL: https:// http://simulationresearch.lbl.gov/GO/download/manual-3-1-1.pdf, 2016.
